From 6e703015111a934c66c36de978065c5ee746d314 Mon Sep 17 00:00:00 2001
From: Huaxin Gao <huaxing@us.ibm.com>
Date: Mon, 4 May 2020 08:02:45 -0700
Subject: [PATCH 01/19] [SPARK-31636][SQL][DOCS] Remove HTML syntax in SQL
 reference

---
 docs/_data/menu-sql.yaml                      |  20 +-
 docs/sql-ref-ansi-compliance.md               |   8 +-
 docs/sql-ref-datatypes.md                     |   4 +-
 docs/sql-ref-functions-udf-aggregate.md       | 101 +++----
 docs/sql-ref-functions-udf-hive.md            |  12 +-
 docs/sql-ref-functions-udf-scalar.md          |  28 +-
 docs/sql-ref-identifier.md                    |  43 ++-
 docs/sql-ref-literals.md                      | 256 ++++++++---------
 docs/sql-ref-null-semantics.md                |  44 +--
 docs/sql-ref-syntax-aux-analyze-table.md      |  64 ++---
 docs/sql-ref-syntax-aux-cache-cache-table.md  |  98 +++----
 docs/sql-ref-syntax-aux-cache-clear-cache.md  |  16 +-
 docs/sql-ref-syntax-aux-cache-refresh.md      |  24 +-
 .../sql-ref-syntax-aux-cache-uncache-table.md |  31 +--
 docs/sql-ref-syntax-aux-conf-mgmt-reset.md    |  10 +-
 docs/sql-ref-syntax-aux-conf-mgmt-set.md      |  31 +--
 docs/sql-ref-syntax-aux-describe-database.md  |  21 +-
 docs/sql-ref-syntax-aux-describe-function.md  |  30 +-
 docs/sql-ref-syntax-aux-describe-query.md     |  44 ++-
 docs/sql-ref-syntax-aux-describe-table.md     |  62 ++---
 docs/sql-ref-syntax-aux-refresh-table.md      |  31 +--
 ...l-ref-syntax-aux-resource-mgmt-add-file.md |  21 +-
 ...ql-ref-syntax-aux-resource-mgmt-add-jar.md |  20 +-
 ...-ref-syntax-aux-resource-mgmt-list-file.md |  14 +-
 ...l-ref-syntax-aux-resource-mgmt-list-jar.md |  14 +-
 docs/sql-ref-syntax-aux-show-columns.md       |   2 +-
 docs/sql-ref-syntax-aux-show-create-table.md  |  27 +-
 docs/sql-ref-syntax-aux-show-databases.md     |  32 +--
 docs/sql-ref-syntax-aux-show-functions.md     |  59 ++--
 docs/sql-ref-syntax-aux-show-partitions.md    |  47 ++--
 docs/sql-ref-syntax-aux-show-table.md         |  56 ++--
 docs/sql-ref-syntax-aux-show-tables.md        |  41 ++-
 docs/sql-ref-syntax-aux-show-tblproperties.md |  51 ++--
 docs/sql-ref-syntax-aux-show-views.md         |  45 ++-
 docs/sql-ref-syntax-ddl-alter-database.md     |  17 +-
 docs/sql-ref-syntax-ddl-alter-table.md        | 249 +++++++----------
 docs/sql-ref-syntax-ddl-alter-view.md         | 124 ++++-----
 docs/sql-ref-syntax-ddl-create-database.md    |  39 +--
 docs/sql-ref-syntax-ddl-create-function.md    |  87 +++---
 ...-ref-syntax-ddl-create-table-datasource.md | 100 +++----
 ...-ref-syntax-ddl-create-table-hiveformat.md |  99 +++----
 docs/sql-ref-syntax-ddl-create-table-like.md  |  73 +++--
 docs/sql-ref-syntax-ddl-create-table.md       |  10 +-
 docs/sql-ref-syntax-ddl-create-view.md        |  82 +++---
 docs/sql-ref-syntax-ddl-drop-database.md      |  42 ++-
 docs/sql-ref-syntax-ddl-drop-function.md      |  49 ++--
 docs/sql-ref-syntax-ddl-drop-table.md         |  37 ++-
 docs/sql-ref-syntax-ddl-drop-view.md          |  41 ++-
 docs/sql-ref-syntax-ddl-repair-table.md       |  25 +-
 docs/sql-ref-syntax-ddl-truncate-table.md     |  43 ++-
 docs/sql-ref-syntax-dml-insert-into.md        |  90 +++---
 ...tax-dml-insert-overwrite-directory-hive.md |  75 ++---
 ...f-syntax-dml-insert-overwrite-directory.md |  74 +++--
 ...l-ref-syntax-dml-insert-overwrite-table.md |  87 +++---
 docs/sql-ref-syntax-dml-insert.md             |   8 +-
 docs/sql-ref-syntax-dml-load.md               |  67 ++---
 docs/sql-ref-syntax-dml.md                    |   4 +-
 docs/sql-ref-syntax-qry-explain.md            |  58 ++--
 docs/sql-ref-syntax-qry-sampling.md           |  18 +-
 docs/sql-ref-syntax-qry-select-clusterby.md   |  33 +--
 docs/sql-ref-syntax-qry-select-cte.md         |  35 +--
 ...sql-ref-syntax-qry-select-distribute-by.md |  33 +--
 docs/sql-ref-syntax-qry-select-groupby.md     | 261 +++++++++---------
 docs/sql-ref-syntax-qry-select-having.md      |  54 ++--
 docs/sql-ref-syntax-qry-select-hints.md       |  56 ++--
 .../sql-ref-syntax-qry-select-inline-table.md |  32 +--
 docs/sql-ref-syntax-qry-select-join.md        | 185 ++++++-------
 docs/sql-ref-syntax-qry-select-like.md        |  51 ++--
 docs/sql-ref-syntax-qry-select-limit.md       |  39 ++-
 docs/sql-ref-syntax-qry-select-orderby.md     |  82 +++---
 docs/sql-ref-syntax-qry-select-setops.md      |  26 +-
 docs/sql-ref-syntax-qry-select-sortby.md      |  84 +++---
 docs/sql-ref-syntax-qry-select-tvf.md         |  35 +--
 docs/sql-ref-syntax-qry-select-usedb.md       |  23 +-
 docs/sql-ref-syntax-qry-select-where.md       |  37 ++-
 docs/sql-ref-syntax-qry-select.md             | 209 +++++++-------
 docs/sql-ref-syntax-qry-window.md             |  89 +++---
 docs/sql-ref-syntax-qry.md                    |  35 +--
 78 files changed, 1935 insertions(+), 2469 deletions(-)

diff --git a/docs/_data/menu-sql.yaml b/docs/_data/menu-sql.yaml
index dfe4cfab2a2ab..57fc493dad2f2 100644
--- a/docs/_data/menu-sql.yaml
+++ b/docs/_data/menu-sql.yaml
@@ -156,22 +156,22 @@
                   url: sql-ref-syntax-qry-select-distribute-by.html
                 - text: LIMIT Clause 
                   url: sql-ref-syntax-qry-select-limit.html
+                - text: Common Table Expression
+                  url: sql-ref-syntax-qry-select-cte.html
+                - text: Inline Table
+                  url: sql-ref-syntax-qry-select-inline-table.html
                 - text: JOIN
                   url: sql-ref-syntax-qry-select-join.html
                 - text: Join Hints
                   url: sql-ref-syntax-qry-select-hints.html
+                - text: LIKE Predicate
+                  url: sql-ref-syntax-qry-select-like.html
                 - text: Set Operators
                   url: sql-ref-syntax-qry-select-setops.html
                 - text: TABLESAMPLE
                   url: sql-ref-syntax-qry-sampling.html
                 - text: Table-valued Function
                   url: sql-ref-syntax-qry-select-tvf.html
-                - text: Inline Table
-                  url: sql-ref-syntax-qry-select-inline-table.html
-                - text: Common Table Expression
-                  url: sql-ref-syntax-qry-select-cte.html
-                - text: LIKE Predicate
-                  url: sql-ref-syntax-qry-select-like.html
                 - text: Window Function
                   url: sql-ref-syntax-qry-window.html
             - text: EXPLAIN
@@ -213,20 +213,20 @@
               subitems:
                 - text: SHOW COLUMNS 
                   url: sql-ref-syntax-aux-show-columns.html
+                - text: SHOW CREATE TABLE
+                  url: sql-ref-syntax-aux-show-create-table.html
                 - text: SHOW DATABASES
                   url: sql-ref-syntax-aux-show-databases.html
                 - text: SHOW FUNCTIONS
                   url: sql-ref-syntax-aux-show-functions.html
+                - text: SHOW PARTITIONS
+                  url: sql-ref-syntax-aux-show-partitions.html
                 - text: SHOW TABLE
                   url: sql-ref-syntax-aux-show-table.html
                 - text: SHOW TABLES
                   url: sql-ref-syntax-aux-show-tables.html
                 - text: SHOW TBLPROPERTIES
                   url: sql-ref-syntax-aux-show-tblproperties.html
-                - text: SHOW PARTITIONS 
-                  url: sql-ref-syntax-aux-show-partitions.html
-                - text: SHOW CREATE TABLE
-                  url: sql-ref-syntax-aux-show-create-table.html
                 - text: SHOW VIEWS
                   url: sql-ref-syntax-aux-show-views.html
             - text: CONFIGURATION MANAGEMENT
diff --git a/docs/sql-ref-ansi-compliance.md b/docs/sql-ref-ansi-compliance.md
index 6cf16535eecf8..b4b307f4ac2a0 100644
--- a/docs/sql-ref-ansi-compliance.md
+++ b/docs/sql-ref-ansi-compliance.md
@@ -66,7 +66,7 @@ This means that in case an operation causes overflows, the result is the same wi
 On the other hand, Spark SQL returns null for decimal overflows.
 When `spark.sql.ansi.enabled` is set to `true` and an overflow occurs in numeric and interval arithmetic operations, it throws an arithmetic exception at runtime.
 
-{% highlight sql %}
+```sql
 -- `spark.sql.ansi.enabled=true`
 SELECT 2147483647 + 1;
   java.lang.ArithmeticException: integer overflow
@@ -78,7 +78,7 @@ SELECT 2147483647 + 1;
 +----------------+
 |     -2147483648|
 +----------------+
-{% endhighlight %}
+```
 
 ### Type Conversion
 
@@ -89,7 +89,7 @@ On the other hand, `INSERT INTO` syntax throws an analysis exception when the AN
 Currently, the ANSI mode affects explicit casting and assignment casting only.
 In future releases, the behaviour of type coercion might change along with the other two type conversion rules.
 
-{% highlight sql %}
+```sql
 -- Examples of explicit casting
 
 -- `spark.sql.ansi.enabled=true`
@@ -130,7 +130,7 @@ SELECT * FROM t;
 +---+
 |  1|
 +---+
-{% endhighlight %}
+```
 
 ### SQL Functions
 
diff --git a/docs/sql-ref-datatypes.md b/docs/sql-ref-datatypes.md
index 0d49f6f882228..64c0d0c118a0e 100644
--- a/docs/sql-ref-datatypes.md
+++ b/docs/sql-ref-datatypes.md
@@ -751,7 +751,7 @@ Specifically:
 
 #### Examples
 
-{% highlight sql %}
+```sql
 SELECT double('infinity') AS col;
 +--------+
 |     col|
@@ -824,4 +824,4 @@ SELECT COUNT(*), c2 FROM test GROUP BY c2;
 |        2|-Infinity|
 |        3| Infinity|
 +---------+---------+
-{% endhighlight %}
\ No newline at end of file
+```
diff --git a/docs/sql-ref-functions-udf-aggregate.md b/docs/sql-ref-functions-udf-aggregate.md
index 3fde94d6bc4bf..da3182149410b 100644
--- a/docs/sql-ref-functions-udf-aggregate.md
+++ b/docs/sql-ref-functions-udf-aggregate.md
@@ -27,46 +27,35 @@ User-Defined Aggregate Functions (UDAFs) are user-programmable routines that act
 
 A base class for user-defined aggregations, which can be used in Dataset operations to take all of the elements of a group and reduce them to a single value.
 
- * IN - The input type for the aggregation.
- * BUF - The type of the intermediate value of the reduction.
- * OUT - The type of the final output result.
+  ***IN*** - The input type for the aggregation.
+
+  ***BUF*** - The type of the intermediate value of the reduction.
+
+  ***OUT*** - The type of the final output result.
+
+* **bufferEncoder: Encoder[BUF]**
 
-<dl>
-  <dt><code><em>bufferEncoder: Encoder[BUF]</em></code></dt>
-  <dd>
     Specifies the Encoder for the intermediate value type.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>finish(reduction: BUF): OUT</em></code></dt>
-  <dd>
+
+* **finish(reduction: BUF): OUT**
+
     Transform the output of the reduction.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>merge(b1: BUF, b2: BUF): BUF</em></code></dt>
-  <dd>
+
+* **merge(b1: BUF, b2: BUF): BUF**
+
     Merge two intermediate values.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>outputEncoder: Encoder[OUT]</em></code></dt>
-  <dd>
+
+* **outputEncoder: Encoder[OUT]**
+
     Specifies the Encoder for the final output value type.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>reduce(b: BUF, a: IN): BUF</em></code></dt>
-  <dd>
-     Aggregate input value <code>a</code> into current intermediate value. For performance, the function may modify <code>b</code> and return it instead of constructing new object for <code>b</code>.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>zero: BUF</em></code></dt>
-  <dd>
+
+* **reduce(b: BUF, a: IN): BUF**
+
+     Aggregate input value `a` into current intermediate value. For performance, the function may modify `b` and return it instead of constructing new object for `b`.
+
+* **zero: BUF**
+
     The initial value of the intermediate result for this aggregation.
-  </dd>
-</dl>
 
 ### Examples
 
@@ -95,16 +84,16 @@ For example, a user-defined average for untyped DataFrames can look like:
   {% include_example untyped_custom_aggregation java/org/apache/spark/examples/sql/JavaUserDefinedUntypedAggregation.java%}
 </div>
 <div data-lang="SQL"  markdown="1">
-{% highlight sql %}
+```sql
 -- Compile and place UDAF MyAverage in a JAR file called `MyAverage.jar` in /tmp.
 CREATE FUNCTION myAverage AS 'MyAverage' USING JAR '/tmp/MyAverage.jar';
 
 SHOW USER FUNCTIONS;
--- +------------------+
--- |          function|
--- +------------------+
--- | default.myAverage|
--- +------------------+
++------------------+
+|          function|
++------------------+
+| default.myAverage|
++------------------+
 
 CREATE TEMPORARY VIEW employees
 USING org.apache.spark.sql.json
@@ -113,26 +102,26 @@ OPTIONS (
 );
 
 SELECT * FROM employees;
--- +-------+------+
--- |   name|salary|
--- +-------+------+
--- |Michael|  3000|
--- |   Andy|  4500|
--- | Justin|  3500|
--- |  Berta|  4000|
--- +-------+------+
++-------+------+
+|   name|salary|
++-------+------+
+|Michael|  3000|
+|   Andy|  4500|
+| Justin|  3500|
+|  Berta|  4000|
++-------+------+
 
 SELECT myAverage(salary) as average_salary FROM employees;
--- +--------------+
--- |average_salary|
--- +--------------+
--- |        3750.0|
--- +--------------+
-{% endhighlight %}
++--------------+
+|average_salary|
++--------------+
+|        3750.0|
++--------------+
+```
 </div>
 </div>
 
 ### Related Statements
 
- * [Scalar User Defined Functions (UDFs)](sql-ref-functions-udf-scalar.html)
- * [Integration with Hive UDFs/UDAFs/UDTFs](sql-ref-functions-udf-hive.html)
+* [Scalar User Defined Functions (UDFs)](sql-ref-functions-udf-scalar.html)
+* [Integration with Hive UDFs/UDAFs/UDTFs](sql-ref-functions-udf-hive.html)
diff --git a/docs/sql-ref-functions-udf-hive.md b/docs/sql-ref-functions-udf-hive.md
index 97d72c44ef016..d3d2a221c94d8 100644
--- a/docs/sql-ref-functions-udf-hive.md
+++ b/docs/sql-ref-functions-udf-hive.md
@@ -28,7 +28,7 @@ Spark SQL supports integration of Hive UDFs, UDAFs and UDTFs. Similar to Spark U
 Hive has two UDF interfaces: [UDF](https://github.com/apache/hive/blob/master/udf/src/java/org/apache/hadoop/hive/ql/exec/UDF.java) and [GenericUDF](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDF.java).
 An example below uses [GenericUDFAbs](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDFAbs.java) derived from `GenericUDF`.
 
-{% highlight sql %}
+```sql
 -- Register `GenericUDFAbs` and use it in Spark SQL.
 -- Note that, if you use your own programmed one, you need to add a JAR containig it
 -- into a classpath,
@@ -52,12 +52,12 @@ SELECT testUDF(value) FROM t;
 |           2.0|
 |           3.0|
 +--------------+
-{% endhighlight %}
+```
 
 
 An example below uses [GenericUDTFExplode](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDTFExplode.java) derived from [GenericUDTF](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDF.java).
 
-{% highlight sql %}
+```sql
 -- Register `GenericUDTFExplode` and use it in Spark SQL
 CREATE TEMPORARY FUNCTION hiveUDTF
     AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDTFExplode';
@@ -79,12 +79,12 @@ SELECT hiveUDTF(value) FROM t;
 |  3|
 |  4|
 +---+
-{% endhighlight %}
+```
 
 Hive has two UDAF interfaces: [UDAF](https://github.com/apache/hive/blob/master/udf/src/java/org/apache/hadoop/hive/ql/exec/UDAF.java) and [GenericUDAFResolver](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDAFResolver.java).
 An example below uses [GenericUDAFSum](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDAFSum.java) derived from `GenericUDAFResolver`.
 
-{% highlight sql %}
+```sql
 -- Register `GenericUDAFSum` and use it in Spark SQL
 CREATE TEMPORARY FUNCTION hiveUDAF
     AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDAFSum';
@@ -105,4 +105,4 @@ SELECT key, hiveUDAF(value) FROM t GROUP BY key;
 |  b|              3|
 |  a|              3|
 +---+---------------+
-{% endhighlight %}
\ No newline at end of file
+```
\ No newline at end of file
diff --git a/docs/sql-ref-functions-udf-scalar.md b/docs/sql-ref-functions-udf-scalar.md
index 2cb25f275cb59..97f5a89d3fb19 100644
--- a/docs/sql-ref-functions-udf-scalar.md
+++ b/docs/sql-ref-functions-udf-scalar.md
@@ -26,24 +26,18 @@ User-Defined Functions (UDFs) are user-programmable routines that act on one row
 ### UserDefinedFunction
 
 To define the properties of a user-defined function, the user can use some of the methods defined in this class.
-<dl>
-  <dt><code><em>asNonNullable(): UserDefinedFunction</em></code></dt>
-  <dd>
+
+* **asNonNullable(): UserDefinedFunction**
+
     Updates UserDefinedFunction to non-nullable.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>asNondeterministic(): UserDefinedFunction</em></code></dt>
-  <dd>
+
+* **asNondeterministic(): UserDefinedFunction**
+
     Updates UserDefinedFunction to nondeterministic.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>withName(name: String): UserDefinedFunction</em></code></dt>
-  <dd>
+
+* **withName(name: String): UserDefinedFunction**
+
     Updates UserDefinedFunction with a given name.
-  </dd>
-</dl>
 
 ### Examples
 
@@ -57,5 +51,5 @@ To define the properties of a user-defined function, the user can use some of th
 </div>
 
 ### Related Statements
- * [User Defined Aggregate Functions (UDAFs)](sql-ref-functions-udf-aggregate.html)
- * [Integration with Hive UDFs/UDAFs/UDTFs](sql-ref-functions-udf-hive.html)
+* [User Defined Aggregate Functions (UDAFs)](sql-ref-functions-udf-aggregate.html)
+* [Integration with Hive UDFs/UDAFs/UDTFs](sql-ref-functions-udf-hive.html)
diff --git a/docs/sql-ref-identifier.md b/docs/sql-ref-identifier.md
index 89cde21e6fdb6..5b48ece19fb07 100644
--- a/docs/sql-ref-identifier.md
+++ b/docs/sql-ref-identifier.md
@@ -27,54 +27,47 @@ An identifier is a string used to identify a database object such as a table, vi
 
 #### Regular Identifier
 
-{% highlight sql %}
+```sql
 { letter | digit | '_' } [ , ... ]
-{% endhighlight %}
+```
 Note: If `spark.sql.ansi.enabled` is set to true, ANSI SQL reserved keywords cannot be used as identifiers. For more details, please refer to [ANSI Compliance](sql-ref-ansi-compliance.html).
 
 #### Delimited Identifier
 
-{% highlight sql %}
+```sql
 `c [ ... ]`
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>letter</em></code></dt>
-  <dd>
+* **letter**
+
     Any letter from A-Z or a-z.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>digit</em></code></dt>
-  <dd>
+
+* **digit**
+
     Any numeral from 0 to 9.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>c</em></code></dt>
-  <dd>
+
+* **c**
+
     Any character from the character set. Use <code>`</code> to escape special characters (e.g., <code>`</code>).
-  </dd>
-</dl>
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- This CREATE TABLE fails with ParseException because of the illegal identifier name a.b
 CREATE TABLE test (a.b int);
-org.apache.spark.sql.catalyst.parser.ParseException:
-no viable alternative at input 'CREATE TABLE test (a.'(line 1, pos 20)
+  org.apache.spark.sql.catalyst.parser.ParseException:
+  no viable alternative at input 'CREATE TABLE test (a.'(line 1, pos 20)
 
 -- This CREATE TABLE works
 CREATE TABLE test (`a.b` int);
 
 -- This CREATE TABLE fails with ParseException because special character ` is not escaped
 CREATE TABLE test1 (`a`b` int);
-org.apache.spark.sql.catalyst.parser.ParseException:
-no viable alternative at input 'CREATE TABLE test (`a`b`'(line 1, pos 23)
+  org.apache.spark.sql.catalyst.parser.ParseException:
+  no viable alternative at input 'CREATE TABLE test (`a`b`'(line 1, pos 23)
 
 -- This CREATE TABLE works
 CREATE TABLE test (`a``b` int);
-{% endhighlight %}
+```
diff --git a/docs/sql-ref-literals.md b/docs/sql-ref-literals.md
index 0088f79cb7007..d203f3503ef87 100644
--- a/docs/sql-ref-literals.md
+++ b/docs/sql-ref-literals.md
@@ -35,22 +35,19 @@ A string literal is used to specify a character string value.
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 'c [ ... ]' | "c [ ... ]"
-{% endhighlight %}
+```
 
-#### <em>Parameters</em>
+#### Parameters
+
+* **c**
 
-<dl>
-  <dt><code><em>c</em></code></dt>
-  <dd>
-    One character from the character set. Use <code>\</code> to escape special characters (e.g., <code>'</code> or <code>\</code>).
-  </dd>
-</dl>
+    One character from the character set. Use `\` to escape special characters (e.g., `'` or `\`).
 
-#### <em>Examples</em>
+#### Examples
 
-{% highlight sql %}
+```sql
 SELECT 'Hello, World!' AS col;
 +-------------+
 |          col|
@@ -71,7 +68,7 @@ SELECT 'it\'s $10.' AS col;
 +---------+
 |It's $10.|
 +---------+
-{% endhighlight %}
+```
 
 ### Binary Literal
 
@@ -79,29 +76,26 @@ A binary literal is used to specify a byte sequence value.
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 X { 'c [ ... ]' | "c [ ... ]" }
-{% endhighlight %}
+```
+
+#### Parameters
 
-#### <em>Parameters</em>
+* **c**
 
-<dl>
-  <dt><code><em>c</em></code></dt>
-  <dd>
     One character from the character set.
-  </dd>
-</dl>
 
-#### <em>Examples</em>
+#### Examples
 
-{% highlight sql %}
+```sql
 SELECT X'123456' AS col;
 +----------+
 |       col|
 +----------+
 |[12 34 56]|
 +----------+
-{% endhighlight %}
+```
 
 ### Null Literal
 
@@ -109,20 +103,20 @@ A null literal is used to specify a null value.
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 NULL
-{% endhighlight %}
+```
 
 #### Examples
 
-{% highlight sql %}
+```sql
 SELECT NULL AS col;
 +----+
 | col|
 +----+
 |NULL|
 +----+
-{% endhighlight %}
+```
 
 ### Boolean Literal
 
@@ -130,20 +124,20 @@ A boolean literal is used to specify a boolean value.
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 TRUE | FALSE
-{% endhighlight %}
+```
 
 #### Examples
 
-{% highlight sql %}
+```sql
 SELECT TRUE AS col;
 +----+
 | col|
 +----+
 |true|
 +----+
-{% endhighlight %}
+```
 
 ### Numeric Literal
 
@@ -153,46 +147,35 @@ A numeric literal is used to specify a fixed or floating-point number.
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 [ + | - ] digit [ ... ] [ L | S | Y ]
-{% endhighlight %}
+```
 
 #### Parameters
 
-<dl>
-  <dt><code><em>digit</em></code></dt>
-  <dd>
+* **digit**
+
     Any numeral from 0 to 9.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>L</em></code></dt>
-  <dd>
-    Case insensitive, indicates <code>BIGINT</code>, which is a 8-byte signed integer number.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>S</em></code></dt>
-  <dd>
-    Case insensitive, indicates <code>SMALLINT</code>, which is a 2-byte signed integer number.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>Y</em></code></dt>
-  <dd>
-    Case insensitive, indicates <code>TINYINT</code>, which is a 1-byte signed integer number.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>default (no postfix)</em></code></dt>
-  <dd>
+
+* **L**
+
+    Case insensitive, indicates `BIGINT`, which is a 8-byte signed integer number.
+
+* **S**
+
+    Case insensitive, indicates `SMALLINT`, which is a 2-byte signed integer number.
+
+* **Y**
+
+    Case insensitive, indicates `TINYINT`, which is a 1-byte signed integer number.
+
+* **default (no postfix)**
+
     Indicates a 4-byte signed integer number.
-  </dd>
-</dl>
 
 #### Examples
 
-{% highlight sql %}
+```sql
 SELECT -2147483648 AS col;
 +-----------+
 |        col|
@@ -220,56 +203,49 @@ SELECT 482S AS col;
 +---+
 |482|
 +---+
-{% endhighlight %}
+```
 
 #### Fractional Literals
 
 #### Syntax
 
 decimal literals:
-{% highlight sql %}
+```sql
 decimal_digits { [ BD ] | [ exponent BD ] } | digit [ ... ] [ exponent ] BD
-{% endhighlight %}
+```
 
 double literals:
-{% highlight sql %}
+```sql
 decimal_digits  { D | exponent [ D ] }  | digit [ ... ] { exponent [ D ] | [ exponent ] D }
-{% endhighlight %}
+```
 
 While decimal_digits is defined as
-{% highlight sql %}
+```sql
 [ + | - ] { digit [ ... ] . [ digit [ ... ] ] | . digit [ ... ] }
-{% endhighlight %}
+```
 
 and exponent is defined as
-{% highlight sql %}
+```sql
 E [ + | - ] digit [ ... ]
-{% endhighlight %}
+```
 
 #### Parameters
 
-<dl>
-  <dt><code><em>digit</em></code></dt>
-  <dd>
+* **digit**
+
     Any numeral from 0 to 9.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>D</em></code></dt>
-  <dd>
-    Case insensitive, indicates <code>DOUBLE</code>, which is a 8-byte double-precision floating point number.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>BD</em></code></dt>
-  <dd>
-    Case insensitive, indicates <code>DECIMAL</code>, with the total number of digits as precision and the number of digits to right of decimal point as scale.
-  </dd>
-</dl>
+
+* **D**
+
+    Case insensitive, indicates `DOUBLE`, which is a 8-byte double-precision floating point number.
+
+* **BD**
+
+    Case insensitive, indicates `DECIMAL`, with the total number of digits as precision and the number of digits to right of decimal point as scale.
 
 #### Examples
 
-{% highlight sql %}
+```sql
 SELECT 12.578 AS col;
 +------+
 |   col|
@@ -353,7 +329,7 @@ SELECT -3.E-3D AS col;
 +------+
 |-0.003|
 +------+
-{% endhighlight %}
+```
 
 ### Datetime Literal
 
@@ -363,17 +339,17 @@ A Datetime literal is used to specify a datetime value.
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 DATE { 'yyyy' |
        'yyyy-[m]m' |
        'yyyy-[m]m-[d]d' |
        'yyyy-[m]m-[d]d[T]' }
-{% endhighlight %}
-Note: defaults to <code>01</code> if month or day is not specified.
+```
+Note: defaults to `01` if month or day is not specified.
 
 #### Examples
 
-{% highlight sql %}
+```sql
 SELECT DATE '1997' AS col;
 +----------+
 |       col|
@@ -394,13 +370,13 @@ SELECT DATE '2011-11-11' AS col;
 +----------+
 |2011-11-11|
 +----------+
-{% endhighlight %}
+```
 
 #### Timestamp Literal
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 TIMESTAMP { 'yyyy' |
             'yyyy-[m]m' |
             'yyyy-[m]m-[d]d' |
@@ -409,27 +385,23 @@ TIMESTAMP { 'yyyy' |
             'yyyy-[m]m-[d]d[T][h]h:[m]m[:]' |
             'yyyy-[m]m-[d]d[T][h]h:[m]m:[s]s[.]' |
             'yyyy-[m]m-[d]d[T][h]h:[m]m:[s]s.[ms][ms][ms][us][us][us][zone_id]'}
-{% endhighlight %}
-Note: defaults to <code>00</code> if hour, minute or second is not specified. <br><br>
+```
+Note: defaults to `00` if hour, minute or second is not specified.
 `zone_id` should have one of the forms:
-<ul>
-  <li>Z - Zulu time zone UTC+0</li>
-  <li>+|-[h]h:[m]m</li>
-  <li>An id with one of the prefixes UTC+, UTC-, GMT+, GMT-, UT+ or UT-, and a suffix in the formats:
-    <ul>
-      <li>+|-h[h]</li>
-      <li>+|-hh[:]mm</li>
-      <li>+|-hh:mm:ss</li>
-      <li>+|-hhmmss</li>
-    </ul>
-  </li>
-  <li>Region-based zone IDs in the form <code>area/city</code>, such as <code>Europe/Paris</code></li>
-</ul>
-Note: defaults to the session local timezone (set via <code>spark.sql.session.timeZone</code>) if <code>zone_id</code> is not specified.
+* Z - Zulu time zone UTC+0
+* `+|-[h]h:[m]m`
+* An id with one of the prefixes UTC+, UTC-, GMT+, GMT-, UT+ or UT-, and a suffix in the formats:
+  * `+|-h[h]`
+  * `+|-hh[:]mm`
+  * `+|-hh:mm:ss`
+  * `+|-hhmmss`
+* Region-based zone IDs in the form `area/city`, such as `Europe/Paris`
+
+Note: defaults to the session local timezone (set via `spark.sql.session.timeZone`) if `zone_id` is not specified.
 
 #### Examples
 
-{% highlight sql %}
+```sql
 SELECT TIMESTAMP '1997-01-31 09:26:56.123' AS col;
 +-----------------------+
 |                    col|
@@ -450,50 +422,40 @@ SELECT TIMESTAMP '1997-01' AS col;
 +-------------------+
 |1997-01-01 00:00:00|
 +-------------------+
-{% endhighlight %}
+```
 
 ### Interval Literal
 
 An interval literal is used to specify a fixed period of time.
 
-#### Syntax
-{% highlight sql %}
-{ INTERVAL interval_value interval_unit [ interval_value interval_unit ... ] |
-  INTERVAL 'interval_value interval_unit [ interval_value interval_unit ... ]' |
-  INTERVAL interval_string_value interval_unit TO interval_unit }
-{% endhighlight %}
+```sql
+INTERVAL interval_value interval_unit [ interval_value interval_unit ... ] |
+INTERVAL 'interval_value interval_unit [ interval_value interval_unit ... ]' |
+INTERVAL interval_string_value interval_unit TO interval_unit
+```
 
 #### Parameters
 
-<dl>
-  <dt><code><em>interval_value</em></code></dt>
-  <dd>
-    <b>Syntax:</b>
-      <code>
-        [ + | - ] number_value | '[ + | - ] number_value'
-      </code><br>
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>interval_string_value</em></code></dt>
-    <dd>
-      year-month/day-time interval string.
-    </dd>
-</dl>
-<dl>
-  <dt><code><em>interval_unit</em></code></dt>
-  <dd>
-    <b>Syntax:</b><br>
-      <code>
-        YEAR[S] | MONTH[S] | WEEK[S] | DAY[S] | HOUR[S] | MINUTE[S] | SECOND[S] | <br>
-        MILLISECOND[S] | MICROSECOND[S]
-      </code>
-  </dd>
-</dl>
+* **interval_value**
+
+    **Syntax:**
+
+      [ + | - ] number_value | '[ + | - ] number_value'
+
+* **interval_string_value**
+
+     year-month/day-time interval string.
+
+* **interval_unit**
+
+    **Syntax:**
+
+      YEAR[S] | MONTH[S] | WEEK[S] | DAY[S] | HOUR[S] | MINUTE[S] | SECOND[S] |
+      MILLISECOND[S] | MICROSECOND[S]
 
 #### Examples
 
-{% highlight sql %}
+```sql
 SELECT INTERVAL 3 YEAR AS col;
 +-------+
 |    col|
@@ -536,4 +498,4 @@ SELECT INTERVAL '20 15:40:32.99899999' DAY TO SECOND AS col;
 +---------------------------------------------+
 |20 days 15 hours 40 minutes 32.998999 seconds|
 +---------------------------------------------+
-{% endhighlight %}
+```
diff --git a/docs/sql-ref-null-semantics.md b/docs/sql-ref-null-semantics.md
index d1f4f17596bd4..b96a02c43bee7 100644
--- a/docs/sql-ref-null-semantics.md
+++ b/docs/sql-ref-null-semantics.md
@@ -116,7 +116,7 @@ one or both operands are `NULL`:
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Normal comparison operators return `NULL` when one of the operand is `NULL`.
 SELECT 5 > null AS expression_output;
 +-----------------+
@@ -148,7 +148,7 @@ SELECT NULL <=> NULL;
 +-----------------+
 |             true|
 +-----------------+
-{% endhighlight %}
+```
 
 ### Logical Operators <a name="logical-operators"></a>
 
@@ -209,7 +209,7 @@ The following tables illustrate the behavior of logical operators when one or bo
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Normal comparison operators return `NULL` when one of the operands is `NULL`.
 SELECT (true OR null) AS expression_output;
 +-----------------+
@@ -233,7 +233,7 @@ SELECT NOT(null) AS expression_output;
 +-----------------+
 |             null|
 +-----------------+
-{% endhighlight %}
+```
 
 ### Expressions <a name="expressions"></a>
 
@@ -252,7 +252,7 @@ expression are `NULL` and most of the expressions fall in this category.
 
 ##### Examples
 
-{% highlight sql %}
+```sql
 SELECT concat('John', null) AS expression_output;
 +-----------------+
 |expression_output|
@@ -273,7 +273,7 @@ SELECT to_date(null) AS expression_output;
 +-----------------+
 |             null|
 +-----------------+
-{% endhighlight %}
+```
 
 #### Expressions That Can Process Null Value Operands <a name="can-process-null"></a>
 
@@ -296,7 +296,7 @@ returns the first non `NULL` value in its list of operands. However, `coalesce`
 
 ##### Examples
 
-{% highlight sql %}
+```sql
 SELECT isnull(null) AS expression_output;
 +-----------------+
 |expression_output|
@@ -326,7 +326,7 @@ SELECT isnan(null) AS expression_output;
 +-----------------+
 |            false|
 +-----------------+
-{% endhighlight %}
+```
 
 #### Builtin Aggregate Expressions <a name="built-in-aggregate"></a>
 
@@ -346,7 +346,7 @@ the rules of how `NULL` values are handled by aggregate functions.
    
 #### Examples
 
-{% highlight sql %}
+```sql
 -- `count(*)` does not skip `NULL` values.
 SELECT count(*) FROM person;
 +--------+
@@ -387,7 +387,7 @@ SELECT max(age) FROM person where 1 = 0;
 +--------+
 |    null|
 +--------+
-{% endhighlight %}
+```
 
 ### Condition Expressions in WHERE, HAVING and JOIN Clauses <a name="condition-expressions"></a>
 
@@ -398,7 +398,7 @@ For all the three operators, a condition expression is a boolean expression and
 
 #### Examples
 
-{% highlight sql %}
+```sql
 -- Persons whose age is unknown (`NULL`) are filtered out from the result set.
 SELECT * FROM person WHERE age > 0;
 +--------+---+
@@ -466,7 +466,7 @@ SELECT * FROM person p1, person p2
 |   Marry|null|   Marry|null|
 |     Joe|  30|     Joe|  30|
 +--------+----+--------+----+
-{% endhighlight %}
+```
 
 ### Aggregate Operator (GROUP BY, DISTINCT) <a name="aggregate-operator"></a>
 
@@ -477,7 +477,7 @@ standard and with other enterprise database management systems.
 
 #### Examples
 
-{% highlight sql %}
+```sql
 -- `NULL` values are put in one bucket in `GROUP BY` processing.
 SELECT age, count(*) FROM person GROUP BY age;
 +----+--------+
@@ -499,7 +499,7 @@ SELECT DISTINCT age FROM person;
 |  30|
 |  18|
 +----+
-{% endhighlight %}
+```
 
 ### Sort Operator (ORDER BY Clause) <a name="order-by"></a>
 
@@ -509,7 +509,7 @@ the `NULL` values are placed at first.
 
 #### Examples
 
-{% highlight sql %}
+```sql
 -- `NULL` values are shown at first and other values
 -- are sorted in ascending way.
 SELECT age, name FROM person ORDER BY age;
@@ -554,7 +554,7 @@ SELECT age, name FROM person ORDER BY age DESC NULLS LAST;
 |null|   Marry|
 |null|  Albert|
 +----+--------+
-{% endhighlight %}
+```
 
 ### Set Operators (UNION, INTERSECT, EXCEPT) <a name="set-operators"></a>
 
@@ -564,7 +564,7 @@ equal unlike the regular `EqualTo`(`=`) operator.
 
 #### Examples
 
-{% highlight sql %}
+```sql
 CREATE VIEW unknown_age SELECT * FROM person WHERE age IS NULL;
 
 -- Only common rows between two legs of `INTERSECT` are in the 
@@ -612,7 +612,7 @@ SELECT name, age FROM person
 |    Mike|  18|
 |     Dan|  50|
 +--------+----+
-{% endhighlight %}
+```
 
 ### EXISTS/NOT EXISTS Subquery <a name="exists-not-exists"></a>
 
@@ -629,7 +629,7 @@ semijoins / anti-semijoins without special provisions for null awareness.
 
 #### Examples
 
-{% highlight sql %}
+```sql
 -- Even if subquery produces rows with `NULL` values, the `EXISTS` expression
 -- evaluates to `TRUE` as the subquery produces 1 row.
 SELECT * FROM person WHERE EXISTS (SELECT null);
@@ -666,7 +666,7 @@ SELECT * FROM person WHERE NOT EXISTS (SELECT 1 WHERE 1 = 0);
 |   Marry|null|
 |     Joe|  30|
 +--------+----+
-{% endhighlight %}
+```
 
 ### IN/NOT IN Subquery <a name="in-not-in"></a>
 
@@ -692,7 +692,7 @@ and because NOT UNKNOWN is again UNKNOWN.
  
 #### Examples
 
-{% highlight sql %}
+```sql
 -- The subquery has only `NULL` value in its result set. Therefore,
 -- the result of `IN` predicate is UNKNOWN.
 SELECT * FROM person WHERE age IN (SELECT null);
@@ -721,4 +721,4 @@ SELECT * FROM person
 |name|age|
 +----+---+
 +----+---+
-{% endhighlight %}
+```
diff --git a/docs/sql-ref-syntax-aux-analyze-table.md b/docs/sql-ref-syntax-aux-analyze-table.md
index f6a6c5f4bc555..a8e11303432ba 100644
--- a/docs/sql-ref-syntax-aux-analyze-table.md
+++ b/docs/sql-ref-syntax-aux-analyze-table.md
@@ -25,53 +25,39 @@ The `ANALYZE TABLE` statement collects statistics about the table to be used by
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 ANALYZE TABLE table_identifier [ partition_spec ]
     COMPUTE STATISTICS [ NOSCAN | FOR COLUMNS col [ , ... ] | FOR ALL COLUMNS ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
     An optional parameter that specifies a comma separated list of key and value pairs
-    for partitions. When specified, partition statistics is returned.<br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name [ = partition_col_val ] [ , ... ] )
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>[ NOSCAN | FOR COLUMNS col [ , ... ] | FOR ALL COLUMNS ]</em></code></dt>
-    <dd>
-      <ul>
-        <li> If no analyze option is specified, <code>ANALYZE TABLE</code> collects the table's number of rows and size in bytes. </li>
-        <li> <b>NOSCAN</b>
-          <br> Collect only the table's size in bytes ( which does not require scanning the entire table ). </li>
-        <li> <b>FOR COLUMNS col [ , ... ] <code> | </code> FOR ALL COLUMNS</b>
-          <br> Collect column statistics for each column specified, or alternatively for every column, as well as table statistics.
-        </li>
-      </ul>
-     </dd>
-</dl>
+    for partitions. When specified, partition statistics is returned.
+
+    **Syntax:** `PARTITION ( partition_col_name [ = partition_col_val ] [ , ... ] )`
+
+* **[ NOSCAN `|` FOR COLUMNS col [ , ... ] `|` FOR ALL COLUMNS ]**
+
+     * If no analyze option is specified, `ANALYZE TABLE` collects the table's number of rows and size in bytes. </li>
+     * **NOSCAN**
+
+       Collects only the table's size in bytes ( which does not require scanning the entire table ).
+     * **FOR COLUMNS col [ , ... ] `|` FOR ALL COLUMNS**
+
+       Collects column statistics for each column specified, or alternatively for every column, as well as table statistics.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE students (name STRING, student_id INT) PARTITIONED BY (student_id);
 INSERT INTO students PARTITION (student_id = 111111) VALUES ('Mark');
 INSERT INTO students PARTITION (student_id = 222222) VALUES ('John');
@@ -135,4 +121,4 @@ DESC EXTENDED students name;
 |   max_col_len|         4|
 |     histogram|      NULL|
 +--------------+----------+
-{% endhighlight %}
+```
diff --git a/docs/sql-ref-syntax-aux-cache-cache-table.md b/docs/sql-ref-syntax-aux-cache-cache-table.md
index 11f682cc10891..193e209d792b3 100644
--- a/docs/sql-ref-syntax-aux-cache-cache-table.md
+++ b/docs/sql-ref-syntax-aux-cache-cache-table.md
@@ -26,71 +26,57 @@ This reduces scanning of the original files in future queries.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 CACHE [ LAZY ] TABLE table_identifier
     [ OPTIONS ( 'storageLevel' [ = ] value ) ] [ [ AS ] query ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>LAZY</em></code></dt>
-  <dd>Only cache the table when it is first used, instead of immediately.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies the table or view name to be cached. The table or view name may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>OPTIONS ( 'storageLevel' [ = ] value )</em></code></dt>
-  <dd>
-  <code>OPTIONS</code> clause with <code>storageLevel</code> key and value pair. A Warning is issued when a key other than <code>storageLevel</code> is used. The valid options for <code>storageLevel</code> are:
-    <ul>
-      <li><code>NONE</code></li>
-      <li><code>DISK_ONLY</code></li>
-      <li><code>DISK_ONLY_2</code></li>
-      <li><code>MEMORY_ONLY</code></li>
-      <li><code>MEMORY_ONLY_2</code></li>
-      <li><code>MEMORY_ONLY_SER</code></li>
-      <li><code>MEMORY_ONLY_SER_2</code></li>
-      <li><code>MEMORY_AND_DISK</code></li>
-      <li><code>MEMORY_AND_DISK_2</code></li>
-      <li><code>MEMORY_AND_DISK_SER</code></li>
-      <li><code>MEMORY_AND_DISK_SER_2</code></li>
-      <li><code>OFF_HEAP</code></li>
-    </ul>
-    An Exception is thrown when an invalid value is set for <code>storageLevel</code>. If <code>storageLevel</code> is not explicitly set using <code>OPTIONS</code> clause, the default <code>storageLevel</code> is set to <code>MEMORY_AND_DISK</code>.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>query</em></code></dt>
-  <dd>A query that produces the rows to be cached. It can be in one of following formats:
-    <ul>
-      <li>a <code>SELECT</code> statement</li>
-      <li>a <code>TABLE</code> statement</li>
-      <li>a <code>FROM</code> statement</li>
-    </ul>
-   </dd>
-</dl>
+* **LAZY**
+
+    Only cache the table when it is first used, instead of immediately.
+
+* **table_identifier**
+
+    Specifies the table or view name to be cached. The table or view name may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **OPTIONS ( 'storageLevel' [ = ] value )**
+
+    `OPTIONS` clause with `storageLevel` key and value pair. A Warning is issued when a key other than `storageLevel` is used. The valid options for `storageLevel` are:
+     * `NONE`
+     * `DISK_ONLY`
+     * `DISK_ONLY_2`
+     * `MEMORY_ONLY`
+     * `MEMORY_ONLY_2`
+     * `MEMORY_ONLY_SER`
+     * `MEMORY_ONLY_SER_2`
+     * `MEMORY_AND_DISK`
+     * `MEMORY_AND_DISK_2`
+     * `MEMORY_AND_DISK_SER`
+     * `MEMORY_AND_DISK_SER_2`
+     * `OFF_HEAP`
+
+    An Exception is thrown when an invalid value is set for `storageLevel`. If `storageLevel` is not explicitly set using `OPTIONS` clause, the default `storageLevel` is set to `MEMORY_AND_DISK`.
+
+* **query**
+
+    A query that produces the rows to be cached. It can be in one of following formats:
+    * a `SELECT` statement
+    * a `TABLE` statement
+    * a `FROM` statement
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CACHE TABLE testCache OPTIONS ('storageLevel' 'DISK_ONLY') SELECT * FROM testData;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CLEAR CACHE](sql-ref-syntax-aux-cache-clear-cache.html)
- * [UNCACHE TABLE](sql-ref-syntax-aux-cache-uncache-table.html)
- * [REFRESH TABLE](sql-ref-syntax-aux-refresh-table.html)
- * [REFRESH](sql-ref-syntax-aux-cache-refresh.html)
+* [CLEAR CACHE](sql-ref-syntax-aux-cache-clear-cache.html)
+* [UNCACHE TABLE](sql-ref-syntax-aux-cache-uncache-table.html)
+* [REFRESH TABLE](sql-ref-syntax-aux-refresh-table.html)
+* [REFRESH](sql-ref-syntax-aux-cache-refresh.html)
diff --git a/docs/sql-ref-syntax-aux-cache-clear-cache.md b/docs/sql-ref-syntax-aux-cache-clear-cache.md
index 47889691148b7..ee33e6a98296d 100644
--- a/docs/sql-ref-syntax-aux-cache-clear-cache.md
+++ b/docs/sql-ref-syntax-aux-cache-clear-cache.md
@@ -25,19 +25,19 @@ license: |
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 CLEAR CACHE
-{% endhighlight %}
+```
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CLEAR CACHE;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CACHE TABLE](sql-ref-syntax-aux-cache-cache-table.html)
- * [UNCACHE TABLE](sql-ref-syntax-aux-cache-uncache-table.html)
- * [REFRESH TABLE](sql-ref-syntax-aux-refresh-table.html)
- * [REFRESH](sql-ref-syntax-aux-cache-refresh.html)
+* [CACHE TABLE](sql-ref-syntax-aux-cache-cache-table.html)
+* [UNCACHE TABLE](sql-ref-syntax-aux-cache-uncache-table.html)
+* [REFRESH TABLE](sql-ref-syntax-aux-refresh-table.html)
+* [REFRESH](sql-ref-syntax-aux-cache-refresh.html)
diff --git a/docs/sql-ref-syntax-aux-cache-refresh.md b/docs/sql-ref-syntax-aux-cache-refresh.md
index 25f7ede1d324e..82bc12da5d1ac 100644
--- a/docs/sql-ref-syntax-aux-cache-refresh.md
+++ b/docs/sql-ref-syntax-aux-cache-refresh.md
@@ -27,32 +27,30 @@ invalidate everything that is cached.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 REFRESH resource_path
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
- <dt><code><em>resource_path</em></code></dt>
- <dd>The path of the resource that is to be refreshed.</dd>
-</dl>
+* **resource_path**
+
+    The path of the resource that is to be refreshed.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- The Path is resolved using the datasource's File Index.
- 
 CREATE TABLE test(ID INT) using parquet;
 INSERT INTO test SELECT 1000;
 CACHE TABLE test;
 INSERT INTO test SELECT 100;
 REFRESH "hdfs://path/to/table";
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CACHE TABLE](sql-ref-syntax-aux-cache-cache-table.html)
- * [CLEAR CACHE](sql-ref-syntax-aux-cache-clear-cache.html)
- * [UNCACHE TABLE](sql-ref-syntax-aux-cache-uncache-table.html)
- * [REFRESH TABLE](sql-ref-syntax-aux-refresh-table.html)
+* [CACHE TABLE](sql-ref-syntax-aux-cache-cache-table.html)
+* [CLEAR CACHE](sql-ref-syntax-aux-cache-clear-cache.html)
+* [UNCACHE TABLE](sql-ref-syntax-aux-cache-uncache-table.html)
+* [REFRESH TABLE](sql-ref-syntax-aux-refresh-table.html)
diff --git a/docs/sql-ref-syntax-aux-cache-uncache-table.md b/docs/sql-ref-syntax-aux-cache-uncache-table.md
index 95fd91c3c4807..c5a8fbbe08281 100644
--- a/docs/sql-ref-syntax-aux-cache-uncache-table.md
+++ b/docs/sql-ref-syntax-aux-cache-uncache-table.md
@@ -26,32 +26,27 @@ underlying entries should already have been brought to cache by previous `CACHE
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 UNCACHE TABLE [ IF EXISTS ] table_identifier
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies the table or view name to be uncached. The table or view name may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
+* **table_identifier**
+
+    Specifies the table or view name to be uncached. The table or view name may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 UNCACHE TABLE t1;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CACHE TABLE](sql-ref-syntax-aux-cache-cache-table.html)
- * [CLEAR CACHE](sql-ref-syntax-aux-cache-clear-cache.html)
- * [REFRESH TABLE](sql-ref-syntax-aux-refresh-table.html)
- * [REFRESH](sql-ref-syntax-aux-cache-refresh.html)
+* [CACHE TABLE](sql-ref-syntax-aux-cache-cache-table.html)
+* [CLEAR CACHE](sql-ref-syntax-aux-cache-clear-cache.html)
+* [REFRESH TABLE](sql-ref-syntax-aux-refresh-table.html)
+* [REFRESH](sql-ref-syntax-aux-cache-refresh.html)
diff --git a/docs/sql-ref-syntax-aux-conf-mgmt-reset.md b/docs/sql-ref-syntax-aux-conf-mgmt-reset.md
index e7e6dda4e25ee..4caf57a232f89 100644
--- a/docs/sql-ref-syntax-aux-conf-mgmt-reset.md
+++ b/docs/sql-ref-syntax-aux-conf-mgmt-reset.md
@@ -25,17 +25,17 @@ Reset any runtime configurations specific to the current session which were set
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 RESET
-{% endhighlight %}
+```
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Reset any runtime configurations specific to the current session which were set via the SET command to their default values.
 RESET;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SET](sql-ref-syntax-aux-conf-mgmt-set.html)
+* [SET](sql-ref-syntax-aux-conf-mgmt-set.html)
diff --git a/docs/sql-ref-syntax-aux-conf-mgmt-set.md b/docs/sql-ref-syntax-aux-conf-mgmt-set.md
index 330a1a6a399ff..f97b7f2a8efed 100644
--- a/docs/sql-ref-syntax-aux-conf-mgmt-set.md
+++ b/docs/sql-ref-syntax-aux-conf-mgmt-set.md
@@ -25,32 +25,29 @@ The SET command sets a property, returns the value of an existing property or re
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 SET
 SET [ -v ]
 SET property_key[ = property_value ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>-v</em></code></dt>
-  <dd>Outputs the key, value and meaning of existing SQLConf properties.</dd>
-</dl>
+* **-v**
 
-<dl>
-  <dt><code><em>property_key</em></code></dt>
-  <dd>Returns the value of specified property key.</dd>
-</dl>
+    Outputs the key, value and meaning of existing SQLConf properties.
 
-<dl>
-  <dt><code><em>property_key=property_value</em></code></dt>
-  <dd>Sets the value for a given property key. If an old value exists for a given property key, then it gets overridden by the new value.</dd>
-</dl>
+* **property_key**
+
+    Returns the value of specified property key.
+
+* **property_key=property_value**
+
+     Sets the value for a given property key. If an old value exists for a given property key, then it gets overridden by the new value.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Set a property.
 SET spark.sql.variable.substitute=false;
 
@@ -67,8 +64,8 @@ SET spark.sql.variable.substitute;
 +-----------------------------+-----+
 |spark.sql.variable.substitute|false|
 +-----------------------------+-----+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [RESET](sql-ref-syntax-aux-conf-mgmt-reset.html)
+* [RESET](sql-ref-syntax-aux-conf-mgmt-reset.html)
diff --git a/docs/sql-ref-syntax-aux-describe-database.md b/docs/sql-ref-syntax-aux-describe-database.md
index 39a40ddac800f..143fa78b205ca 100644
--- a/docs/sql-ref-syntax-aux-describe-database.md
+++ b/docs/sql-ref-syntax-aux-describe-database.md
@@ -28,23 +28,20 @@ interchangeable.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 { DESC | DESCRIBE } DATABASE [ EXTENDED ] db_name
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>db_name</em></code></dt>
-  <dd>
+* **db_name**
+
     Specifies a name of an existing database or an existing schema in the system. If the name does not exist, an
     exception is thrown.
-  </dd>
-</dl>
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Create employees DATABASE
 CREATE DATABASE employees COMMENT 'For software companies';
 
@@ -89,10 +86,10 @@ DESC DATABASE deployment;
 |              Description|        Deployment environment|
 |                 Location|file:/Users/Temp/deployment.db|
 +-------------------------+------------------------------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
- * [DESCRIBE TABLE](sql-ref-syntax-aux-describe-table.html)
- * [DESCRIBE QUERY](sql-ref-syntax-aux-describe-query.html)
+* [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
+* [DESCRIBE TABLE](sql-ref-syntax-aux-describe-table.html)
+* [DESCRIBE QUERY](sql-ref-syntax-aux-describe-query.html)
diff --git a/docs/sql-ref-syntax-aux-describe-function.md b/docs/sql-ref-syntax-aux-describe-function.md
index 76c9efad2fa7d..a871fb5bfd406 100644
--- a/docs/sql-ref-syntax-aux-describe-function.md
+++ b/docs/sql-ref-syntax-aux-describe-function.md
@@ -28,29 +28,24 @@ metadata information is returned along with the extended usage information.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 { DESC | DESCRIBE } FUNCTION [ EXTENDED ] function_name
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>function_name</em></code></dt>
-  <dd>
+* **function_name**
+
     Specifies a name of an existing function in the system. The function name may be
     optionally qualified with a database name. If `function_name` is qualified with
     a database then the function is resolved from the user specified database, otherwise
-    it is resolved from the current database.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] function_name
-      </code>
-  </dd>
-</dl>
+    it is resolved from the current database.
+
+    **Syntax:** `[ database_name. ] function_name`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Describe a builtin scalar function.
 -- Returns function name, implementing class and usage
 DESC FUNCTION abs;
@@ -107,11 +102,10 @@ DESC FUNCTION EXTENDED explode
 |       10                                                      |
 |       20                                                      |
 +---------------------------------------------------------------+
-
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
- * [DESCRIBE TABLE](sql-ref-syntax-aux-describe-table.html)
- * [DESCRIBE QUERY](sql-ref-syntax-aux-describe-query.html)
+* [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
+* [DESCRIBE TABLE](sql-ref-syntax-aux-describe-table.html)
+* [DESCRIBE QUERY](sql-ref-syntax-aux-describe-query.html)
diff --git a/docs/sql-ref-syntax-aux-describe-query.md b/docs/sql-ref-syntax-aux-describe-query.md
index 07ac39b4431f4..65e101d3dbf13 100644
--- a/docs/sql-ref-syntax-aux-describe-query.md
+++ b/docs/sql-ref-syntax-aux-describe-query.md
@@ -27,38 +27,36 @@ describe the query output.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 { DESC | DESCRIBE } [ QUERY ] input_statement
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>QUERY</em></code></dt>
-  <dd>This clause is optional and may be omitted.</dd>
-  <dt><code><em>input_statement</em></code></dt>
-  <dd>
+* **QUERY**
+    This clause is optional and may be omitted.
+
+* **input_statement**
+
     Specifies a result set producing statement and may be one of the following: 
-    <ul>
-      <li>a <code>SELECT</code> statement</li>
-      <li>a <code>CTE(Common table expression)</code> statement</li>
-      <li>an <code>INLINE TABLE</code> statement</li>
-      <li>a <code>TABLE</code> statement</li>
-      <li>a <code>FROM</code> statement</li>
-    </ul>
-    Please refer to <a href="sql-ref-syntax-qry-select.html">select-statement</a>
+
+    * a `SELECT` statement
+    * a `CTE(Common table expression)` statement
+    * an `INLINE TABLE` statement
+    * a `TABLE` statement
+    * a `FROM` statement`
+
+    Please refer to [select-statement](sql-ref-syntax-qry-select.html)
     for a detailed syntax of the query parameter.
-  </dd>
-</dl>
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Create table `person`
 CREATE TABLE person (name STRING , age INT COMMENT 'Age column', address STRING);
 
 -- Returns column metadata information for a simple select query
-DESCRIBE QUERY select age, sum(age) FROM person GROUP BY age;
+DESCRIBE QUERY SELECT age, sum(age) FROM person GROUP BY age;
 +--------+---------+----------+
 |col_name|data_type|   comment|
 +--------+---------+----------+
@@ -103,10 +101,10 @@ DESCRIBE FROM person SELECT age;
 +--------+---------+----------+
 |     age|      int| Agecolumn|
 +--------+---------+----------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
- * [DESCRIBE TABLE](sql-ref-syntax-aux-describe-table.html)
- * [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
+* [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
+* [DESCRIBE TABLE](sql-ref-syntax-aux-describe-table.html)
+* [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
diff --git a/docs/sql-ref-syntax-aux-describe-table.md b/docs/sql-ref-syntax-aux-describe-table.md
index 63bf056d785cc..4b6e1e8c3461e 100644
--- a/docs/sql-ref-syntax-aux-describe-table.md
+++ b/docs/sql-ref-syntax-aux-describe-table.md
@@ -28,53 +28,43 @@ to return the metadata pertaining to a partition or column respectively.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 { DESC | DESCRIBE } [ TABLE ] [ format ] table_identifier [ partition_spec ] [ col_name ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>format</em></code></dt>
-  <dd>
+* **format**
+
     Specifies the optional format of describe output. If `EXTENDED` is specified
     then additional metadata information (such as parent database, owner, and access time)
     is returned. 
-  </dd>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
+
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
     An optional parameter that specifies a comma separated list of key and value pairs
-    for partitions. When specified, additional partition metadata is returned.<br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name  = partition_col_val [ , ... ] )
-      </code>
-  </dd>  
-  <dt><code><em>col_name</em></code></dt>
-  <dd>
+    for partitions. When specified, additional partition metadata is returned.
+
+    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
+
+* **col_name**
+
     An optional parameter that specifies the column name that needs to be described.
     The supplied column name may be optionally qualified. Parameters `partition_spec`
     and `col_name` are  mutually exclusive and can not be specified together. Currently
-    nested columns are not allowed to be specified.<br><br>
+    nested columns are not allowed to be specified.
     
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] [ table_name. ] column_name
-      </code>
-   </dd>
-</dl>
+    **Syntax:** `[ database_name. ] [ table_name. ] column_name`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Creates a table `customer`. Assumes current database is `salesdb`.
 CREATE TABLE customer(
         cust_id INT,
@@ -183,10 +173,10 @@ DESCRIBE customer salesdb.customer.name;
 |data_type|    string|
 |  comment|Short name|
 +---------+----------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
- * [DESCRIBE QUERY](sql-ref-syntax-aux-describe-query.html)
- * [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
+* [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
+* [DESCRIBE QUERY](sql-ref-syntax-aux-describe-query.html)
+* [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
diff --git a/docs/sql-ref-syntax-aux-refresh-table.md b/docs/sql-ref-syntax-aux-refresh-table.md
index 165ca68309f4a..8d4a804f88671 100644
--- a/docs/sql-ref-syntax-aux-refresh-table.md
+++ b/docs/sql-ref-syntax-aux-refresh-table.md
@@ -27,26 +27,21 @@ lazy manner when the cached table or the query associated with it is executed ag
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 REFRESH [TABLE] table_identifier
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which is either a qualified or unqualified name that designates a table/view. If no database identifier is provided, it refers to a temporary view or a table/view in the current database.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
+* **table_identifier**
+
+    Specifies a table name, which is either a qualified or unqualified name that designates a table/view. If no database identifier is provided, it refers to a temporary view or a table/view in the current database.
+
+    **Syntax:** `[ database_name. ] table_name`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- The cached entries of the table will be refreshed  
 -- The table is resolved from the current database as the table name is unqualified.
 REFRESH TABLE tbl1;
@@ -54,11 +49,11 @@ REFRESH TABLE tbl1;
 -- The cached entries of the view will be refreshed or invalidated
 -- The view is resolved from tempDB database, as the view name is qualified.
 REFRESH TABLE tempDB.view1;   
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CACHE TABLE](sql-ref-syntax-aux-cache-cache-table.html)
- * [CLEAR CACHE](sql-ref-syntax-aux-cache-clear-cache.html)
- * [UNCACHE TABLE](sql-ref-syntax-aux-cache-uncache-table.html)
- * [REFRESH](sql-ref-syntax-aux-cache-refresh.html)
+* [CACHE TABLE](sql-ref-syntax-aux-cache-cache-table.html)
+* [CLEAR CACHE](sql-ref-syntax-aux-cache-clear-cache.html)
+* [UNCACHE TABLE](sql-ref-syntax-aux-cache-uncache-table.html)
+* [REFRESH](sql-ref-syntax-aux-cache-refresh.html)
diff --git a/docs/sql-ref-syntax-aux-resource-mgmt-add-file.md b/docs/sql-ref-syntax-aux-resource-mgmt-add-file.md
index 0028884308890..9203293d0c981 100644
--- a/docs/sql-ref-syntax-aux-resource-mgmt-add-file.md
+++ b/docs/sql-ref-syntax-aux-resource-mgmt-add-file.md
@@ -25,30 +25,29 @@ license: |
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 ADD FILE resource_name
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
- <dt><code><em>resource_name</em></code></dt>
- <dd>The name of the file or directory to be added.</dd>
-</dl>
+* **resource_name**
+
+    The name of the file or directory to be added.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 ADD FILE /tmp/test;
 ADD FILE "/path/to/file/abc.txt";
 ADD FILE '/another/test.txt';
 ADD FILE "/path with space/abc.txt";
 ADD FILE "/path/to/some/directory";
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [LIST FILE](sql-ref-syntax-aux-resource-mgmt-list-file.html)
- * [LIST JAR](sql-ref-syntax-aux-resource-mgmt-list-jar.html)
- * [ADD JAR](sql-ref-syntax-aux-resource-mgmt-add-jar.html)
+* [LIST FILE](sql-ref-syntax-aux-resource-mgmt-list-file.html)
+* [LIST JAR](sql-ref-syntax-aux-resource-mgmt-list-jar.html)
+* [ADD JAR](sql-ref-syntax-aux-resource-mgmt-add-jar.html)
 
diff --git a/docs/sql-ref-syntax-aux-resource-mgmt-add-jar.md b/docs/sql-ref-syntax-aux-resource-mgmt-add-jar.md
index c4020347c1be0..264c50a87ea55 100644
--- a/docs/sql-ref-syntax-aux-resource-mgmt-add-jar.md
+++ b/docs/sql-ref-syntax-aux-resource-mgmt-add-jar.md
@@ -25,28 +25,26 @@ license: |
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 ADD JAR file_name
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
- <dt><code><em>file_name</em></code></dt>
- <dd>The name of the JAR file to be added. It could be either on a local file system or a distributed file system.</dd>
-</dl>
+* **file_name**
+    The name of the JAR file to be added. It could be either on a local file system or a distributed file system.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 ADD JAR /tmp/test.jar;
 ADD JAR "/path/to/some.jar";
 ADD JAR '/some/other.jar';
 ADD JAR "/path with space/abc.jar";
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [LIST JAR](sql-ref-syntax-aux-resource-mgmt-list-jar.html)
- * [ADD FILE](sql-ref-syntax-aux-resource-mgmt-add-file.html)
- * [LIST FILE](sql-ref-syntax-aux-resource-mgmt-list-file.html)
+* [LIST JAR](sql-ref-syntax-aux-resource-mgmt-list-jar.html)
+* [ADD FILE](sql-ref-syntax-aux-resource-mgmt-add-file.html)
+* [LIST FILE](sql-ref-syntax-aux-resource-mgmt-list-file.html)
diff --git a/docs/sql-ref-syntax-aux-resource-mgmt-list-file.md b/docs/sql-ref-syntax-aux-resource-mgmt-list-file.md
index eec98e1fbffb5..9b9a7df7f612f 100644
--- a/docs/sql-ref-syntax-aux-resource-mgmt-list-file.md
+++ b/docs/sql-ref-syntax-aux-resource-mgmt-list-file.md
@@ -25,13 +25,13 @@ license: |
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 LIST FILE
-{% endhighlight %}
+```
 
 ### Examples
 
-{% highlight sql %}
+```sql
 ADD FILE /tmp/test;
 ADD FILE /tmp/test_2;
 LIST FILE;
@@ -42,11 +42,11 @@ file:/private/tmp/test_2
 LIST FILE /tmp/test /some/random/file /another/random/file
 --output
 file:/private/tmp/test
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [ADD FILE](sql-ref-syntax-aux-resource-mgmt-add-file.html)
- * [ADD JAR](sql-ref-syntax-aux-resource-mgmt-add-jar.html)
- * [LIST JAR](sql-ref-syntax-aux-resource-mgmt-list-jar.html)
+* [ADD FILE](sql-ref-syntax-aux-resource-mgmt-add-file.html)
+* [ADD JAR](sql-ref-syntax-aux-resource-mgmt-add-jar.html)
+* [LIST JAR](sql-ref-syntax-aux-resource-mgmt-list-jar.html)
 
diff --git a/docs/sql-ref-syntax-aux-resource-mgmt-list-jar.md b/docs/sql-ref-syntax-aux-resource-mgmt-list-jar.md
index dca4252c90ef2..04aa52c2ad8af 100644
--- a/docs/sql-ref-syntax-aux-resource-mgmt-list-jar.md
+++ b/docs/sql-ref-syntax-aux-resource-mgmt-list-jar.md
@@ -25,13 +25,13 @@ license: |
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 LIST JAR
-{% endhighlight %}
+```
 
 ### Examples
 
-{% highlight sql %}
+```sql
 ADD JAR /tmp/test.jar;
 ADD JAR /tmp/test_2.jar;
 LIST JAR;
@@ -42,11 +42,11 @@ spark://192.168.1.112:62859/jars/test_2.jar
 LIST JAR /tmp/test.jar /some/random.jar /another/random.jar;
 -- output
 spark://192.168.1.112:62859/jars/test.jar
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [ADD JAR](sql-ref-syntax-aux-resource-mgmt-add-jar.html)
- * [ADD FILE](sql-ref-syntax-aux-resource-mgmt-add-file.html)
- * [LIST FILE](sql-ref-syntax-aux-resource-mgmt-list-file.html)
+* [ADD JAR](sql-ref-syntax-aux-resource-mgmt-add-jar.html)
+* [ADD FILE](sql-ref-syntax-aux-resource-mgmt-add-file.html)
+* [LIST FILE](sql-ref-syntax-aux-resource-mgmt-list-file.html)
 
diff --git a/docs/sql-ref-syntax-aux-show-columns.md b/docs/sql-ref-syntax-aux-show-columns.md
index 7229bba23d2bf..b76db252f1a0f 100644
--- a/docs/sql-ref-syntax-aux-show-columns.md
+++ b/docs/sql-ref-syntax-aux-show-columns.md
@@ -21,7 +21,7 @@ license: |
 
 ### Description
 
-Return the list of columns in a table. If the table does not exist, an exception is thrown.
+Returns the list of columns in a table. If the table does not exist, an exception is thrown.
 
 ### Syntax
 
diff --git a/docs/sql-ref-syntax-aux-show-create-table.md b/docs/sql-ref-syntax-aux-show-create-table.md
index 47a5290f1d022..ae8c10e2d0178 100644
--- a/docs/sql-ref-syntax-aux-show-create-table.md
+++ b/docs/sql-ref-syntax-aux-show-create-table.md
@@ -25,26 +25,21 @@ license: |
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 SHOW CREATE TABLE table_identifier
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table or view name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
+* **table_identifier**
+
+    Specifies a table or view name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE test (c INT) ROW FORMAT DELIMITED FIELDS TERMINATED BY ','
     STORED AS TEXTFILE
     TBLPROPERTIES ('prop1' = 'value1', 'prop2' = 'value2');
@@ -60,9 +55,9 @@ SHOW CREATE TABLE test;
    'prop1' = 'value1',
    'prop2' = 'value2')
 +----------------------------------------------------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
- * [CREATE VIEW](sql-ref-syntax-ddl-create-view.html)
+* [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
+* [CREATE VIEW](sql-ref-syntax-ddl-create-view.html)
diff --git a/docs/sql-ref-syntax-aux-show-databases.md b/docs/sql-ref-syntax-aux-show-databases.md
index c84898aa81459..44c0fbbef3929 100644
--- a/docs/sql-ref-syntax-aux-show-databases.md
+++ b/docs/sql-ref-syntax-aux-show-databases.md
@@ -21,35 +21,31 @@ license: |
 
 ### Description
 
-Lists the databases that match an optionally supplied string pattern. If no
+Lists the databases that match an optionally supplied regular expression pattern. If no
 pattern is supplied then the command lists all the databases in the system.
 Please note that the usage of `SCHEMAS` and `DATABASES` are interchangeable
 and mean the same thing.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 SHOW { DATABASES | SCHEMAS } [ LIKE regex_pattern ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>regex_pattern</em></code></dt>
-  <dd>
+* **regex_pattern**
+
     Specifies a regular expression pattern that is used to filter the results of the
     statement.
-    <ul>
-      <li>Only <code>*</code> and <code>|</code> are allowed as wildcard pattern.</li>
-      <li>Excluding <code>*</code> and <code>|</code>, the remaining pattern follows the regular expression semantics.</li>
-      <li>The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.</li>
-    </ul>
-  </dd>
-</dl>
+    * Except for `*` and `|` character, the pattern works like a regular expression.
+    * `*` alone matches 0 or more characters and `|` is used to separate multiple different regular expressions,
+       any of which can match.
+    * The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Create database. Assumes a database named `default` already exists in
 -- the system. 
 CREATE DATABASE payroll_db;
@@ -83,10 +79,10 @@ SHOW SCHEMAS;
 | payments_db|
 |  payroll_db|
 +------------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
- * [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
- * [ALTER DATABASE](sql-ref-syntax-ddl-alter-database.html)
+* [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
+* [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
+* [ALTER DATABASE](sql-ref-syntax-ddl-alter-database.html)
diff --git a/docs/sql-ref-syntax-aux-show-functions.md b/docs/sql-ref-syntax-aux-show-functions.md
index 8a6de402c7f20..2cfca0f34bf77 100644
--- a/docs/sql-ref-syntax-aux-show-functions.md
+++ b/docs/sql-ref-syntax-aux-show-functions.md
@@ -9,7 +9,6 @@ license: |
   The ASF licenses this file to You under the Apache License, Version 2.0
   (the "License"); you may not use this file except in compliance with
   the License.  You may obtain a copy of the License at
- 
      http://www.apache.org/licenses/LICENSE-2.0
  
   Unless required by applicable law or agreed to in writing, software
@@ -29,48 +28,42 @@ clause is optional and supported only for compatibility with other systems.
 
 ### Syntax
 
-{% highlight sql %}
-SHOW [ function_kind ] FUNCTIONS ( [ LIKE ] function_name | regex_pattern )
-{% endhighlight %}
+```sql
+SHOW [ function_kind ] FUNCTIONS [ [ LIKE ] { function_name | regex_pattern } ]
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>function_kind</em></code></dt>
-  <dd>
+* **function_kind**
+
     Specifies the name space of the function to be searched upon. The valid name spaces are :
-    <ul>
-      <li><b>USER</b> - Looks up the function(s) among the user defined functions.</li>
-      <li><b>SYSTEM</b> - Looks up the function(s) among the system defined functions.</li>
-      <li><b>ALL</b> -  Looks up the function(s) among both user and system defined functions.</li>
-    </ul>
-  </dd>
-  <dt><code><em>function_name</em></code></dt>
-  <dd>
+
+    * **USER** - Looks up the function(s) among the user defined functions.
+    * **SYSTEM** - Looks up the function(s) among the system defined functions.
+    * **ALL** -  Looks up the function(s) among both user and system defined functions.
+
+* **function_name**
+
     Specifies a name of an existing function in the system. The function name may be
     optionally qualified with a database name. If `function_name` is qualified with
     a database then the function is resolved from the user specified database, otherwise
-    it is resolved from the current database.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [database_name.]function_name
-      </code>
-  </dd>
-  <dt><code><em>regex_pattern</em></code></dt>
-  <dd>
+    it is resolved from the current database.
+
+    **Syntax:** `[database_name.]function_name`
+
+* **regex_pattern**
+
     Specifies a regular expression pattern that is used to filter the results of the
     statement.
-    <ul>
-      <li>Only <code>*</code> and <code>|</code> are allowed as wildcard pattern.</li>
-      <li>Excluding <code>*</code> and <code>|</code>, the remaining pattern follows the regular expression semantics.</li>
-      <li>The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.</li>
-    </ul>
-  </dd>
-</dl>
+
+    * Except for `*` and `|` character, the pattern works like a regular expression.
+    * `*` alone matches 0 or more characters and `|` is used to separate multiple different regular expressions,
+       any of which can match.
+    * The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- List a system function `trim` by searching both user defined and system
 -- defined functions.
 SHOW FUNCTIONS trim;
@@ -138,8 +131,8 @@ SHOW FUNCTIONS LIKE 't[a-z][a-z][a-z]';
 |    tanh|
 |    trim|
 +--------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
+* [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
diff --git a/docs/sql-ref-syntax-aux-show-partitions.md b/docs/sql-ref-syntax-aux-show-partitions.md
index 592833b23eb09..f937f8f524342 100644
--- a/docs/sql-ref-syntax-aux-show-partitions.md
+++ b/docs/sql-ref-syntax-aux-show-partitions.md
@@ -27,37 +27,28 @@ partition spec.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 SHOW PARTITIONS table_identifier [ partition_spec ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
     An optional parameter that specifies a comma separated list of key and value pairs
-    for partitions. When specified, the partitions that match the partition spec are returned.<br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name [ = partition_col_val ] [ , ... ] )
-      </code>
-  </dd>
-</dl>
+    for partitions. When specified, the partitions that match the partition spec are returned.
+
+    **Syntax:** `PARTITION ( partition_col_name = partition_col_val [ , ... ] )`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- create a partitioned table and insert a few rows.
 USE salesdb;
 CREATE TABLE customer(id INT, name STRING) PARTITIONED BY (state STRING, city STRING);
@@ -109,11 +100,11 @@ SHOW PARTITIONS customer PARTITION (city =  'San Jose');
 +----------------------+
 |state=CA/city=San Jose|
 +----------------------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
- * [INSERT STATEMENT](sql-ref-syntax-dml-insert.html)
- * [DESCRIBE TABLE](sql-ref-syntax-aux-describe-table.html)
- * [SHOW TABLE](sql-ref-syntax-aux-show-table.html)
+* [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
+* [INSERT STATEMENT](sql-ref-syntax-dml-insert.html)
+* [DESCRIBE TABLE](sql-ref-syntax-aux-describe-table.html)
+* [SHOW TABLE](sql-ref-syntax-aux-show-table.html)
diff --git a/docs/sql-ref-syntax-aux-show-table.md b/docs/sql-ref-syntax-aux-show-table.md
index 3f588045790b2..6be6e7eff79ca 100644
--- a/docs/sql-ref-syntax-aux-show-table.md
+++ b/docs/sql-ref-syntax-aux-show-table.md
@@ -32,42 +32,36 @@ cannot be used with a partition specification.
 
 ### Syntax
 
-{% highlight sql %}
-SHOW TABLE EXTENDED [ IN | FROM database_name ] LIKE regex_pattern
+```sql
+SHOW TABLE EXTENDED [ { IN | FROM } database_name ] LIKE regex_pattern
     [ partition_spec ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
- <dt><code><em>IN|FROM database_name</em></code></dt>
-  <dd>
+* **{ IN`|`FROM } database_name**
+
     Specifies database name. If not provided, will use the current database.
-  </dd>
-  <dt><code><em>regex_pattern</em></code></dt>
-  <dd>
+
+* **regex_pattern**
+
     Specifies the regular expression pattern that is used to filter out unwanted tables.
-    <ul>
-       <li> Except for <code>*</code> and <code>|</code> character, the pattern works like a regular expression.</li>
-       <li> <code>*</code> alone matches 0 or more characters and <code>|</code> is used to separate multiple different regular expressions,
-             any of which can match. </li>
-       <li> The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.</li>
-    </ul>
-  </dd>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
+
+    * Except for `*` and `|` character, the pattern works like a regular expression.
+    * `*` alone matches 0 or more characters and `|` is used to separate multiple different regular expressions,
+      any of which can match.
+    * The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.
+
+* **partition_spec**
+
     An optional parameter that specifies a comma separated list of key and value pairs
-    for partitions. Note that a table regex cannot be used with a partition specification.<br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name [ = partition_col_val ] [ , ... ] )
-      </code>
-  </dd>
-</dl>
+    for partitions. Note that a table regex cannot be used with a partition specification.
+
+    **Syntax:** `PARTITION ( partition_col_name = partition_col_val [ , ... ] )`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Assumes `employee` table created with partitioned by column `grade`
 CREATE TABLE employee(name STRING, grade INT) PARTITIONED BY (grade);
 INSERT INTO employee PARTITION (grade = 1) VALUES ('sam');
@@ -152,7 +146,7 @@ SHOW TABLE EXTENDED  LIKE `employe*`;
 +--------+---------+----------+---------------------------------------------------------------+
   
 -- show partition file system details
-SHOW TABLE EXTENDED  IN `default` LIKE `employee` PARTITION (`grade=1`);
+SHOW TABLE EXTENDED  IN default LIKE `employee` PARTITION (`grade=1`);
 +--------+---------+-----------+--------------------------------------------------------------+
 |database|tableName|isTemporary|                         information                          |
 +--------+---------+-----------+--------------------------------------------------------------+
@@ -175,12 +169,12 @@ SHOW TABLE EXTENDED  IN `default` LIKE `employee` PARTITION (`grade=1`);
 +--------+---------+-----------+--------------------------------------------------------------+
 
 -- show partition file system details with regex fails as shown below
-SHOW TABLE EXTENDED  IN `default` LIKE `empl*` PARTITION (`grade=1`);
+SHOW TABLE EXTENDED  IN default LIKE `empl*` PARTITION (`grade=1`);
   Error: Error running query: org.apache.spark.sql.catalyst.analysis.NoSuchTableException:
    Table or view 'emplo*' not found in database 'default'; (state=,code=0)
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
- * [DESCRIBE TABLE](sql-ref-syntax-aux-describe-table.html)
+* [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
+* [DESCRIBE TABLE](sql-ref-syntax-aux-describe-table.html)
diff --git a/docs/sql-ref-syntax-aux-show-tables.md b/docs/sql-ref-syntax-aux-show-tables.md
index 62eb3ddb18b5c..fef9722a444f8 100644
--- a/docs/sql-ref-syntax-aux-show-tables.md
+++ b/docs/sql-ref-syntax-aux-show-tables.md
@@ -28,33 +28,28 @@ current database.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 SHOW TABLES [ { FROM | IN } database_name ] [ LIKE regex_pattern ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>{ FROM | IN } database_name</em></code></dt>
-  <dd>
+* **{ FROM `|` IN } database_name**
+
      Specifies the database name from which tables are listed.
-  </dd>
-  <dt><code><em>regex_pattern</em></code></dt>
-  <dd>
+
+* **regex_pattern**
+
      Specifies the regular expression pattern that is used to filter out unwanted tables. 
-     <ul> 
-          <li> Except for <code>*</code> and <code>|</code> character, the pattern works like a regular expression.</li>
-          <li> <code>*</code> alone matches 0 or more characters and <code>|</code> is used to separate multiple different regular expressions,
-           any of which can match. </li>
-          <li> The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.</li>
-     </ul>
-    
-  </dd>
-</dl>
+
+     * Except for `*` and `|` character, the pattern works like a regular expression.
+     * `*` alone matches 0 or more characters and `|` is used to separate multiple different regular expressions,
+       any of which can match.
+     * The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- List all tables in default database
 SHOW TABLES;
 +--------+---------+-----------+
@@ -101,11 +96,11 @@ SHOW TABLES LIKE 'sam*|suj';
 | default|     sam1|      false|
 | default|      suj|      false|
 +--------+---------+-----------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
- * [DROP TABLE](sql-ref-syntax-ddl-drop-table.html)
- * [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
- * [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
+* [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
+* [DROP TABLE](sql-ref-syntax-ddl-drop-table.html)
+* [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
+* [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
diff --git a/docs/sql-ref-syntax-aux-show-tblproperties.md b/docs/sql-ref-syntax-aux-show-tblproperties.md
index 662aaad069dd9..5b7ddcbcd9534 100644
--- a/docs/sql-ref-syntax-aux-show-tblproperties.md
+++ b/docs/sql-ref-syntax-aux-show-tblproperties.md
@@ -26,37 +26,30 @@ a property key. If no key is specified then all the properties are returned.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 SHOW TBLPROPERTIES table_identifier 
    [ ( unquoted_property_key | property_key_as_string_literal ) ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
+* **table_identifier**
+
     Specifies the table name of an existing table. The table may be optionally qualified
-    with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-  <dt><code><em>unquoted_property_key</em></code></dt>
-  <dd>
+    with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **unquoted_property_key**
+
     Specifies the property key in unquoted form. The key may consists of multiple
-    parts separated by dot.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ key_part1 ] [ .key_part2 ] [ ... ]
-      </code>
-  </dd>   
-  <dt><code><em>property_key_as_string_literal</em></code></dt>
-  <dd>
+    parts separated by dot.
+
+    **Syntax:** `[ key_part1 ] [ .key_part2 ] [ ... ]`
+
+* **property_key_as_string_literal**
+
     Specifies a property key value as a string literal.
-  </dd>
-</dl>
 
 **Note**
 - Property value returned by this statement excludes some properties 
@@ -68,7 +61,7 @@ SHOW TBLPROPERTIES table_identifier
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- create a table `customer` in database `salesdb`
 USE salesdb;
 CREATE TABLE customer(cust_code INT, name VARCHAR(100), cust_addr STRING)
@@ -110,11 +103,11 @@ SHOW TBLPROPERTIES customer ('created.date');
 +----------+
 |01-01-2001|
 +----------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
- * [ALTER TABLE SET TBLPROPERTIES](sql-ref-syntax-ddl-alter-table.html)
- * [SHOW TABLES](sql-ref-syntax-aux-show-tables.html)
- * [SHOW TABLE EXTENDED](sql-ref-syntax-aux-show-table.html)
+* [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
+* [ALTER TABLE SET TBLPROPERTIES](sql-ref-syntax-ddl-alter-table.html)
+* [SHOW TABLES](sql-ref-syntax-aux-show-tables.html)
+* [SHOW TABLE EXTENDED](sql-ref-syntax-aux-show-table.html)
diff --git a/docs/sql-ref-syntax-aux-show-views.md b/docs/sql-ref-syntax-aux-show-views.md
index 29ad6caf140f8..5003c092cabce 100644
--- a/docs/sql-ref-syntax-aux-show-views.md
+++ b/docs/sql-ref-syntax-aux-show-views.md
@@ -29,30 +29,26 @@ list global temporary views. Note that the command also lists local temporary vi
 regardless of a given database.
 
 ### Syntax
-{% highlight sql %}
+```sql
 SHOW VIEWS [ { FROM | IN } database_name ] [ LIKE regex_pattern ]
-{% endhighlight %}
+```
 
 ### Parameters
-<dl>
-  <dt><code><em>{ FROM | IN } database_name</em></code></dt>
-  <dd>
+* **{ FROM `|` IN } database_name**
+
      Specifies the database name from which views are listed.
-  </dd>
-  <dt><code><em>regex_pattern</em></code></dt>
-  <dd>
+
+* **regex_pattern**
+
      Specifies the regular expression pattern that is used to filter out unwanted views.
-     <ul> 
-          <li>Except for <code>*</code> and <code>|</code> character, the pattern works like a regular expression.</li>
-          <li><code>*</code> alone matches 0 or more characters and <code>|</code> is used to separate multiple different regular expressions,
-           any of which can match. </li>
-          <li>The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.</li>
-     </ul>
-  </dd>
-</dl>
+
+     * Except for `*` and `|` character, the pattern works like a regular expression.
+     * `*` alone matches 0 or more characters and `|` is used to separate multiple different regular expressions,
+       any of which can match.
+     * The leading and trailing blanks are trimmed in the input pattern before processing. The pattern match is case-insensitive.
 
 ### Examples
-{% highlight sql %}
+```sql
 -- Create views in different databases, also create global/local temp views.
 CREATE VIEW sam AS SELECT id, salary FROM employee WHERE name = 'sam';
 CREATE VIEW sam1 AS SELECT id, salary FROM employee WHERE name = 'sam1';
@@ -61,8 +57,8 @@ USE userdb;
 CREATE VIEW user1 AS SELECT id, salary FROM default.employee WHERE name = 'user1';
 CREATE VIEW user2 AS SELECT id, salary FROM default.employee WHERE name = 'user2';
 USE default;
-CREATE GLOBAL TEMP VIEW temp1 AS SELECT 1 as col1;
-CREATE TEMP VIEW temp2 AS SELECT 1 as col1;
+CREATE GLOBAL TEMP VIEW temp1 AS SELECT 1 AS col1;
+CREATE TEMP VIEW temp2 AS SELECT 1 AS col1;
 
 -- List all views in default database
 SHOW VIEWS;
@@ -112,11 +108,10 @@ SHOW VIEWS LIKE 'sam|suj|temp*';
 | default     | suj        | false        |
 |             | temp2      | true         |
 +-------------+------------+--------------+
-
-{% endhighlight %}
+```
 
 ### Related statements
-- [CREATE VIEW](sql-ref-syntax-ddl-create-view.html)
-- [DROP VIEW](sql-ref-syntax-ddl-drop-view.html)
-- [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
-- [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
+* [CREATE VIEW](sql-ref-syntax-ddl-create-view.html)
+* [DROP VIEW](sql-ref-syntax-ddl-drop-view.html)
+* [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
+* [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
diff --git a/docs/sql-ref-syntax-ddl-alter-database.md b/docs/sql-ref-syntax-ddl-alter-database.md
index 2d5860c2ea920..fbc454e25fb0c 100644
--- a/docs/sql-ref-syntax-ddl-alter-database.md
+++ b/docs/sql-ref-syntax-ddl-alter-database.md
@@ -29,21 +29,20 @@ for a database and may be used for auditing purposes.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 ALTER { DATABASE | SCHEMA } database_name
     SET DBPROPERTIES ( property_name = property_value [ , ... ] )
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>database_name</em></code></dt>
-  <dd>Specifies the name of the database to be altered.</dd>
-</dl>
+* **database_name**
+
+    Specifies the name of the database to be altered.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Creates a database named `inventory`.
 CREATE DATABASE inventory;
 
@@ -60,8 +59,8 @@ DESCRIBE DATABASE EXTENDED inventory;
 |                 Location|   file:/temp/spark-warehouse/inventory.db|
 |               Properties|((Edit-date,01/01/2001), (Edited-by,John))|
 +-------------------------+------------------------------------------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
+* [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
diff --git a/docs/sql-ref-syntax-ddl-alter-table.md b/docs/sql-ref-syntax-ddl-alter-table.md
index f81585fef3aae..dc3f52344c43a 100644
--- a/docs/sql-ref-syntax-ddl-alter-table.md
+++ b/docs/sql-ref-syntax-ddl-alter-table.md
@@ -29,35 +29,25 @@ license: |
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 ALTER TABLE table_identifier RENAME TO table_identifier
 
 ALTER TABLE table_identifier partition_spec RENAME TO partition_spec
-{% endhighlight %}
+```
 
 #### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
-    Partition to be renamed. <br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name  = partition_col_val [ , ... ] )
-      </code>
-  </dd>
-</dl>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
+    Partition to be renamed.
+
+    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
 
 ### ADD COLUMNS
 
@@ -65,27 +55,23 @@ ALTER TABLE table_identifier partition_spec RENAME TO partition_spec
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 ALTER TABLE table_identifier ADD COLUMNS ( col_spec [ , ... ] )
-{% endhighlight %}
+```
 
 #### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>COLUMNS ( col_spec )</em></code></dt>
-  <dd>Specifies the columns to be added.</dd>
-</dl>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **COLUMNS ( col_spec )**
+
+    Specifies the columns to be added.
+
+    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
 
 ### ALTER OR CHANGE COLUMN
 
@@ -93,38 +79,29 @@ ALTER TABLE table_identifier ADD COLUMNS ( col_spec [ , ... ] )
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 ALTER TABLE table_identifier { ALTER | CHANGE } [ COLUMN ] col_spec alterColumnAction
-{% endhighlight %}
+```
 
 #### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>COLUMN col_spec</em></code></dt>
-  <dd>Specifies the column to be altered or be changed.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>alterColumnAction</em></code></dt>
-   <dd>
-     Change the comment string.<br><br>
-     <b>Syntax:</b>
-        <code>
-            COMMENT STRING
-        </code>     
-   </dd>     
-</dl>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **COLUMNS ( col_spec )**
+
+    Specifies the columns to be added.
+
+    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
+
+* **alterColumnAction**
+
+    Change the comment string.
+
+    **Syntax:** `COMMENT STRING`
 
 ### ADD AND DROP PARTITION
 
@@ -134,34 +111,24 @@ ALTER TABLE table_identifier { ALTER | CHANGE } [ COLUMN ] col_spec alterColumnA
 
 ##### Syntax
 
-{% highlight sql %}
+```sql
 ALTER TABLE table_identifier ADD [IF NOT EXISTS] 
     ( partition_spec [ partition_spec ... ] )
-{% endhighlight %}
+```
      
 ##### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
-    Partition to be added. <br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name  = partition_col_val [ , ... ] )
-      </code>
-  </dd>
-</dl>     
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
+    Partition to be added..
+
+    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
 
 #### DROP PARTITION
 
@@ -169,33 +136,23 @@ ALTER TABLE table_identifier ADD [IF NOT EXISTS]
 
 ##### Syntax
 
-{% highlight sql %}
+```sql
 ALTER TABLE table_identifier DROP [ IF EXISTS ] partition_spec [PURGE]
-{% endhighlight %}
+```
      
 ##### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
-    Partition to be dropped. <br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name  = partition_col_val [ , ... ] )
-      </code>
-  </dd>
-</dl>     
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
+    Partition to be dropped.
+
+    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
      
 ### SET AND UNSET
 
@@ -208,30 +165,28 @@ this overrides the old value with the new one.
 
 ##### Syntax
 
-{% highlight sql %}
+```sql
 -- Set Table Properties 
 ALTER TABLE table_identifier SET TBLPROPERTIES ( key1 = val1, key2 = val2, ... )
 
 -- Unset Table Properties
 ALTER TABLE table_identifier UNSET TBLPROPERTIES [ IF EXISTS ] ( key1, key2, ... )
-{% endhighlight %}
+```
 
 #### SET SERDE
 
-`ALTER TABLE SET` command is used for setting the SERDE or SERDE properties in Hive tables. If a particular property was already set,  
-this overrides the old value with the new one.
+`ALTER TABLE SET` command is used for setting the SERDE or SERDE properties in Hive tables. If a particular property was already set, this overrides the old value with the new one.
 
 ##### Syntax
 
-{% highlight sql %}
+```sql
 -- Set SERDE Properties
 ALTER TABLE table_identifier [ partition_spec ]
     SET SERDEPROPERTIES ( key1 = val1, key2 = val2, ... )
 
 ALTER TABLE table_identifier [ partition_spec ] SET SERDE serde_class_name
     [ WITH SERDEPROPERTIES ( key1 = val1, key2 = val2, ... ) ]
-
-{% endhighlight %}
+```
 
 #### SET LOCATION And SET FILE FORMAT
 
@@ -240,46 +195,34 @@ existing tables.
 
 ##### Syntax
 
-{% highlight sql %}
+```sql
 -- Changing File Format
 ALTER TABLE table_identifier [ partition_spec ] SET FILEFORMAT file_format
 
 -- Changing File Location
 ALTER TABLE table_identifier [ partition_spec ] SET LOCATION 'new_location'
-{% endhighlight %}
+```
 
 #### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
-    Specifies the partition on which the property has to be set.<br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name  = partition_col_val [ , ... ] )
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>SERDEPROPERTIES ( key1 = val1, key2 = val2, ... )</em></code></dt>
-  <dd>Specifies the SERDE properties to be set.</dd>
-</dl>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
+    Specifies the partition on which the property has to be set.
+
+    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
+
+* **SERDEPROPERTIES ( key1 = val1, key2 = val2, ... )**
+
+    Specifies the SERDE properties to be set.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- RENAME table 
 DESC student;
 +-----------------------+---------+-------+
@@ -481,9 +424,9 @@ ALTER TABLE dbx.tab1 SET TBLPROPERTIES ('winner' = 'loser')
 
 -- DROP TABLE PROPERTIES
 ALTER TABLE dbx.tab1 UNSET TBLPROPERTIES ('winner')
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
- * [DROP TABLE](sql-ref-syntax-ddl-drop-table.html)
+* [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
+* [DROP TABLE](sql-ref-syntax-ddl-drop-table.html)
diff --git a/docs/sql-ref-syntax-ddl-alter-view.md b/docs/sql-ref-syntax-ddl-alter-view.md
index c2887692949ea..a34e77decf593 100644
--- a/docs/sql-ref-syntax-ddl-alter-view.md
+++ b/docs/sql-ref-syntax-ddl-alter-view.md
@@ -29,21 +29,16 @@ Renames the existing view. If the new view name already exists in the source dat
 does not support moving the views across databases.
 
 #### Syntax
-{% highlight sql %}
+```sql
 ALTER VIEW view_identifier RENAME TO view_identifier
-{% endhighlight %}
+```
 
 #### Parameters
-<dl>
-  <dt><code><em>view_identifier</em></code></dt>
-  <dd>
-    Specifies a view name, which may be optionally qualified with a database name.<br><br>
-    <b> Syntax:</b>
-      <code>
-        [ database_name. ] view_name
-      </code>
-  </dd>
-</dl>
+* **view_identifier**
+
+    Specifies a view name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] view_name`
 
 #### SET View Properties
 Set one or more properties of an existing view. The properties are the key value pairs. If the properties' keys exist, 
@@ -51,89 +46,70 @@ the values are replaced with the new values. If the properties' keys do not exis
 the properties.
 
 #### Syntax
-{% highlight sql %}
+```sql
 ALTER VIEW view_identifier SET TBLPROPERTIES ( property_key = property_val [ , ... ] )
-{% endhighlight %}
+```
 
 #### Parameters
-<dl>
-  <dt><code><em>view_identifier</em></code></dt>
-  <dd>
-    Specifies a view name, which may be optionally qualified with a database name.<br><br>
-    <b> Syntax:</b>
-      <code>
-        [ database_name. ] view_name
-      </code>
-  </dd>
-  <dt><code><em>property_key</em></code></dt>
-  <dd>
-    Specifies the property key. The key may consists of multiple parts separated by dot.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ key_part1 ] [ .key_part2 ] [ ... ]
-      </code>
-  </dd>
-</dl>
+* **view_identifier**
+
+    Specifies a view name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] view_name`
+
+* **property_key**
+
+    Specifies the property key. The key may consists of multiple parts separated by dot.
+
+    **Syntax:** `[ key_part1 ] [ .key_part2 ] [ ... ]`
 
 #### UNSET View Properties
 Drop one or more properties of an existing view. If the specified keys do not exist, an exception is thrown. Use 
 `IF EXISTS` to avoid the exception. 
 
 #### Syntax
-{% highlight sql %}
+```sql
 ALTER VIEW view_identifier UNSET TBLPROPERTIES [ IF EXISTS ]  ( property_key [ , ... ] )
-{% endhighlight %}
+```
 
 #### Parameters
-<dl>
-  <dt><code><em>view_identifier</em></code></dt>
-  <dd>
-    Specifies a view name, which may be optionally qualified with a database name.<br><br>
-    <b> Syntax:</b>
-      <code>
-        [ database_name. ] view_name
-      </code>
-  </dd>
-  <dt><code><em>property_key</em></code></dt>
-  <dd>
-    Specifies the property key. The key may consists of multiple parts separated by dot.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ key_part1 ] [ .key_part2 ] [ ... ]
-      </code>
-  </dd>
-</dl>
+* **view_identifier**
+
+    Specifies a view name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] view_name`
+
+* **property_key**
+
+    Specifies the property key. The key may consists of multiple parts separated by dot.
+
+    **Syntax:** `[ key_part1 ] [ .key_part2 ] [ ... ]`
 
 #### ALTER View AS SELECT
 `ALTER VIEW view_identifier AS SELECT` statement changes the definition of a view. The `SELECT` statement must be valid,
 and the `view_identifier` must exist.
 
 #### Syntax
-{% highlight sql %}
+```sql
 ALTER VIEW view_identifier AS select_statement
-{% endhighlight %}
+```
 
 Note that `ALTER VIEW` statement does not support `SET SERDE` or `SET SERDEPROPERTIES` properties.
 
 #### Parameters
-<dl>
-  <dt><code><em>view_identifier</em></code></dt>
-  <dd>
-    Specifies a view name, which may be optionally qualified with a database name.<br><br>
-    <b> Syntax:</b>
-      <code>
-        [ database_name. ] view_name
-      </code>
-  </dd>
-  <dt><code><em>select_statement</em></code></dt>
-  <dd>
-    Specifies the definition of the view. Check <a href="sql-ref-syntax-qry-select.html">select_statement</a> for details.
-  </dd>
-</dl>
+* **view_identifier**
+
+    Specifies a view name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] view_name`
+
+* **select_statement**
+
+    Specifies the definition of the view. Check [select_statement](sql-ref-syntax-qry-select.html) for details.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Rename only changes the view name.
 -- The source and target databases of the view have to be the same.
 -- Use qualified or unqualified name for the source and target view.
@@ -218,11 +194,11 @@ DESC TABLE EXTENDED tempdb1.v2;
 |                   View Text|   select * from tempdb1.v1|       |
 |          View Original Text|   select * from tempdb1.v1|       |
 +----------------------------+---------------------------+-------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [describe-table](sql-ref-syntax-aux-describe-table.html)
- * [create-view](sql-ref-syntax-ddl-create-view.html)
- * [drop-view](sql-ref-syntax-ddl-drop-view.html)
- * [show-views](sql-ref-syntax-aux-show-views.html)
+* [describe-table](sql-ref-syntax-aux-describe-table.html)
+* [create-view](sql-ref-syntax-ddl-create-view.html)
+* [drop-view](sql-ref-syntax-ddl-drop-view.html)
+* [show-views](sql-ref-syntax-aux-show-views.html)
diff --git a/docs/sql-ref-syntax-ddl-create-database.md b/docs/sql-ref-syntax-ddl-create-database.md
index 0ef0dfbdaed2b..8c0951253bf37 100644
--- a/docs/sql-ref-syntax-ddl-create-database.md
+++ b/docs/sql-ref-syntax-ddl-create-database.md
@@ -25,35 +25,38 @@ Creates a database with the specified name. If database with the same name alrea
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 CREATE { DATABASE | SCHEMA } [ IF NOT EXISTS ] database_name
     [ COMMENT database_comment ]
     [ LOCATION database_directory ]
     [ WITH DBPROPERTIES ( property_name = property_value [ , ... ] ) ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-    <dt><code><em>database_name</em></code></dt>
-    <dd>Specifies the name of the database to be created.</dd>
+* **database_name**
 
-    <dt><code><em>IF NOT EXISTS</em></code></dt>
-    <dd>Creates a database with the given name if it doesn't exists. If a database with the same name already exists, nothing will happen.</dd>
+    Specifies the name of the database to be created.
 
-    <dt><code><em>database_directory</em></code></dt>
-    <dd>Path of the file system in which the specified database is to be created. If the specified path does not exist in the underlying file system, this command creates a directory with the path. If the location is not specified, the database will be created in the default warehouse directory, whose path is configured by the static configuration spark.sql.warehouse.dir.</dd>
+* **IF NOT EXISTS**
 
-    <dt><code><em>database_comment</em></code></dt>
-    <dd>Specifies the description for the database.</dd>
+    Creates a database with the given name if it doesn't exists. If a database with the same name already exists, nothing will happen.
 
-    <dt><code><em>WITH DBPROPERTIES ( property_name=property_value [ , ... ] )</em></code></dt>
-    <dd>Specifies the properties for the database in key-value pairs.</dd>
-</dl>
+* **database_directory**
+
+    Path of the file system in which the specified database is to be created. If the specified path does not exist in the underlying file system, this command creates a directory with the path. If the location is not specified, the database will be created in the default warehouse directory, whose path is configured by the static configuration spark.sql.warehouse.dir.
+
+* **database_comment**
+
+    Specifies the description for the database.
+
+* **WITH DBPROPERTIES ( property_name=property_value [ , ... ] )**
+
+    Specifies the properties for the database in key-value pairs.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Create database `customer_db`. This throws exception if database with name customer_db
 -- already exists.
 CREATE DATABASE customer_db;
@@ -76,9 +79,9 @@ DESCRIBE DATABASE EXTENDED customer_db;
 |                 Location|     hdfs://hacluster/user|
 |               Properties|   ((ID,001), (Name,John))|
 +-------------------------+--------------------------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
- * [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
+* [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
+* [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
diff --git a/docs/sql-ref-syntax-ddl-create-function.md b/docs/sql-ref-syntax-ddl-create-function.md
index e3f21f70f7c18..e66df5352b1b5 100644
--- a/docs/sql-ref-syntax-ddl-create-function.md
+++ b/docs/sql-ref-syntax-ddl-create-function.md
@@ -33,68 +33,57 @@ aggregate functions using Scala, Python and Java APIs. Please refer to
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 CREATE [ OR REPLACE ] [ TEMPORARY ] FUNCTION [ IF NOT EXISTS ]
     function_name AS class_name [ resource_locations ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>OR REPLACE</em></code></dt>
-  <dd>
+* **OR REPLACE**
+
     If specified, the resources for the function are reloaded. This is mainly useful
     to pick up any changes made to the implementation of the function. This
-    parameter is mutually exclusive to <code>IF NOT EXISTS</code> and can not
+    parameter is mutually exclusive to `IF NOT EXISTS` and can not
     be specified together.
-  </dd>
-  <dt><code><em>TEMPORARY</em></code></dt>
-  <dd>
-    Indicates the scope of function being created. When <code>TEMPORARY</code> is specified, the
+
+* **TEMPORARY**
+
+    Indicates the scope of function being created. When `TEMPORARY` is specified, the
     created function is valid and visible in the current session. No persistent
     entry is made in the catalog for these kind of functions.
-  </dd>
-  <dt><code><em>IF NOT EXISTS</em></code></dt>
-  <dd>
-    If specified, creates the function only when it does not exist. The creation
-    of function succeeds (no error is thrown) if the specified function already
-    exists in the system. This parameter is mutually exclusive to <code> OR REPLACE</code> 
-    and can not be specified together.
-  </dd>
-  <dt><code><em>function_name</em></code></dt>
-  <dd>
+
+* **IF NOT EXISTS**
+
     Specifies a name of function to be created. The function name may be
-    optionally qualified with a database name. <br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] function_name
-      </code>
-  </dd>
-  <dt><code><em>class_name</em></code></dt>
-  <dd>
+    optionally qualified with a database name.
+
+* **function_name**
+
+    Specifies a name of function to be created. The function name may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] function_name`
+
+* **class_name**
+
     Specifies the name of the class that provides the implementation for function to be created.
     The implementing class should extend one of the base classes as follows:
-    <ul>
-      <li>Should extend <code>UDF</code> or <code>UDAF</code> in <code>org.apache.hadoop.hive.ql.exec</code> package.</li>
-      <li>Should extend <code>AbstractGenericUDAFResolver</code>, <code>GenericUDF</code>, or
-          <code>GenericUDTF</code> in <code>org.apache.hadoop.hive.ql.udf.generic</code> package.</li>
-      <li>Should extend <code>UserDefinedAggregateFunction</code> in <code>org.apache.spark.sql.expressions</code> package.</li>
-    </ul>
-  </dd>
-  <dt><code><em>resource_locations</em></code></dt>
-  <dd>
+
+    * Should extend `UDF` or `UDAF` in `org.apache.hadoop.hive.ql.exec` package.
+    * Should extend `AbstractGenericUDAFResolver`, `GenericUDF`, or
+      `GenericUDTF` in `org.apache.hadoop.hive.ql.udf.generic` package.
+    * Should extend `UserDefinedAggregateFunction` in `org.apache.spark.sql.expressions` package.
+
+* **resource_locations**
+
     Specifies the list of resources that contain the implementation of the function
-    along with its dependencies. <br><br>
-    <b>Syntax:</b>
-      <code>
-        USING { { (JAR | FILE ) resource_uri } , ... }
-      </code>
-  </dd>
-</dl>
+    along with its dependencies.
+
+    **Syntax:** `USING { { (JAR | FILE ) resource_uri } , ... }`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- 1. Create a simple UDF `SimpleUdf` that increments the supplied integral value by 10.
 --    import org.apache.hadoop.hive.ql.exec.UDF;
 --    public class SimpleUdf extends UDF {
@@ -166,10 +155,10 @@ SELECT simple_udf(c1) AS function_return_value FROM t1;
 |                   21|
 |                   22|
 +---------------------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SHOW FUNCTIONS](sql-ref-syntax-aux-show-functions.html)
- * [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
- * [DROP FUNCTION](sql-ref-syntax-ddl-drop-function.html)
+* [SHOW FUNCTIONS](sql-ref-syntax-aux-show-functions.html)
+* [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
+* [DROP FUNCTION](sql-ref-syntax-ddl-drop-function.html)
diff --git a/docs/sql-ref-syntax-ddl-create-table-datasource.md b/docs/sql-ref-syntax-ddl-create-table-datasource.md
index 54827fd63568d..b592116c2a9e4 100644
--- a/docs/sql-ref-syntax-ddl-create-table-datasource.md
+++ b/docs/sql-ref-syntax-ddl-create-table-datasource.md
@@ -25,7 +25,7 @@ The `CREATE TABLE` statement defines a new table using a Data Source.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 CREATE TABLE [ IF NOT EXISTS ] table_identifier
     [ ( col_name1 col_type1 [ COMMENT col_comment1 ], ... ) ]
     [ USING data_source ]
@@ -38,62 +38,52 @@ CREATE TABLE [ IF NOT EXISTS ] table_identifier
     [ COMMENT table_comment ]
     [ TBLPROPERTIES ( key1=val1, key2=val2, ... ) ]
     [ AS select_statement ]
-{% endhighlight %}
+```
 
 Note that, the clauses between the USING clause and the AS SELECT clause can come in
 as any order. For example, you can write COMMENT table_comment after TBLPROPERTIES.
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>USING data_source</em></code></dt>
-  <dd>Data Source is the input format used to create the table. Data source can be CSV, TXT, ORC, JDBC, PARQUET, etc.</dd>
-</dl> 
-
-<dl>
-  <dt><code><em>PARTITIONED BY</em></code></dt>
-  <dd>Partitions are created on the table, based on the columns specified.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>CLUSTERED BY</em></code></dt>
-  <dd>
-	Partitions created on the table will be bucketed into fixed buckets based on the column specified for bucketing.<br><br>
-   	<b>NOTE:</b>Bucketing is an optimization technique that uses buckets (and bucketing columns) to determine data partitioning and avoid data shuffle.<br>
-	<dt><code><em>SORTED BY</em></code></dt>
-	<dd>Determines the order in which the data is stored in buckets. Default is Ascending order.</dd>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>LOCATION</em></code></dt>
-  <dd>Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>COMMENT</em></code></dt>
-  <dd>A string literal to describe the table.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>TBLPROPERTIES</em></code></dt>
-  <dd>A list of key-value pairs that is used to tag the table definition.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>AS select_statement</em></code></dt>
-  <dd>The table is populated using the data from the select statement.</dd>
-</dl>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **USING data_source**
+
+    Data Source is the input format used to create the table. Data source can be CSV, TXT, ORC, JDBC, PARQUET, etc.
+
+* **PARTITIONED BY**
+
+    Partitions are created on the table, based on the columns specified.
+
+* **CLUSTERED BY**
+
+    Partitions created on the table will be bucketed into fixed buckets based on the column specified for bucketing.
+
+    **NOTE:** Bucketing is an optimization technique that uses buckets (and bucketing columns) to determine data partitioning and avoid data shuffle.
+
+* **SORTED BY**
+
+    Determines the order in which the data is stored in buckets. Default is Ascending order.
+
+* **LOCATION**
+
+    Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc.
+
+* **COMMENT**
+
+    A string literal to describe the table.
+
+* **TBLPROPERTIES**
+
+    A list of key-value pairs that is used to tag the table definition.
+
+* **AS select_statement**
+
+    The table is populated using the data from the select statement.
 
 ### Data Source Interaction
 
@@ -110,7 +100,7 @@ input query, to make sure the table gets created contains exactly the same data
 
 ### Examples
 
-{% highlight sql %}
+```sql
 
 --Use data source
 CREATE TABLE student (id INT, name STRING, age INT) USING CSV;
@@ -137,9 +127,9 @@ CREATE TABLE student (id INT, name STRING, age INT)
     USING CSV
     PARTITIONED BY (age)
     CLUSTERED BY (Id) INTO 4 buckets;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE TABLE USING HIVE FORMAT](sql-ref-syntax-ddl-create-table-hiveformat.html)
- * [CREATE TABLE LIKE](sql-ref-syntax-ddl-create-table-like.html)
+* [CREATE TABLE USING HIVE FORMAT](sql-ref-syntax-ddl-create-table-hiveformat.html)
+* [CREATE TABLE LIKE](sql-ref-syntax-ddl-create-table-like.html)
diff --git a/docs/sql-ref-syntax-ddl-create-table-hiveformat.md b/docs/sql-ref-syntax-ddl-create-table-hiveformat.md
index 06f353ad2f103..576d9190f2716 100644
--- a/docs/sql-ref-syntax-ddl-create-table-hiveformat.md
+++ b/docs/sql-ref-syntax-ddl-create-table-hiveformat.md
@@ -25,7 +25,7 @@ The `CREATE TABLE` statement defines a new table using Hive format.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 CREATE [ EXTERNAL ] TABLE [ IF NOT EXISTS ] table_identifier
     [ ( col_name1[:] col_type1 [ COMMENT col_comment1 ], ... ) ]
     [ COMMENT table_comment ]
@@ -36,67 +36,54 @@ CREATE [ EXTERNAL ] TABLE [ IF NOT EXISTS ] table_identifier
     [ LOCATION path ]
     [ TBLPROPERTIES ( key1=val1, key2=val2, ... ) ]
     [ AS select_statement ]
-{% endhighlight %}
+```
 
 Note that, the clauses between the columns definition clause and the AS SELECT clause can come in
 as any order. For example, you can write COMMENT table_comment after TBLPROPERTIES.
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>EXTERNAL</em></code></dt>
-  <dd>Table is defined using the path provided as LOCATION, does not use default location for this table.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>PARTITIONED BY</em></code></dt>
-  <dd>Partitions are created on the table, based on the columns specified.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>ROW FORMAT</em></code></dt>
-  <dd>SERDE is used to specify a custom SerDe or the DELIMITED clause in order to use the native SerDe.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>STORED AS</em></code></dt>
-    <dd>File format for table storage, could be TEXTFILE, ORC, PARQUET,etc.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>LOCATION</em></code></dt>
-  <dd>Path to the directory where table data is stored, Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>COMMENT</em></code></dt>
-  <dd>A string literal to describe the table.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>TBLPROPERTIES</em></code></dt>
-  <dd>A list of key-value pairs that is used to tag the table definition.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>AS select_statement</em></code></dt>
-  <dd>The table is populated using the data from the select statement.</dd>
-</dl>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **EXTERNAL**
+
+    Table is defined using the path provided as LOCATION, does not use default location for this table.
+
+* **PARTITIONED BY**
+
+    Partitions are created on the table, based on the columns specified.
+
+* **ROW FORMAT**
+
+    SERDE is used to specify a custom SerDe or the DELIMITED clause in order to use the native SerDe.
+
+* **STORED AS**
+
+    File format for table storage, could be TEXTFILE, ORC, PARQUET,etc.
+
+* **LOCATION**
+
+    Path to the directory where table data is stored, Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc.
+
+* **COMMENT**
+
+    A string literal to describe the table.
+
+* **TBLPROPERTIES**
+
+    A list of key-value pairs that is used to tag the table definition.
+
+* **AS select_statement**
+
+    The table is populated using the data from the select statement.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 --Use hive format
 CREATE TABLE student (id INT, name STRING, age INT) STORED AS ORC;
 
@@ -130,9 +117,9 @@ CREATE TABLE student (id INT, name STRING)
 CREATE TABLE student (id INT,name STRING)
     ROW FORMAT DELIMITED FIELDS TERMINATED BY ','
     STORED AS TEXTFILE;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE TABLE USING DATASOURCE](sql-ref-syntax-ddl-create-table-datasource.html)
- * [CREATE TABLE LIKE](sql-ref-syntax-ddl-create-table-like.html)
+* [CREATE TABLE USING DATASOURCE](sql-ref-syntax-ddl-create-table-datasource.html)
+* [CREATE TABLE LIKE](sql-ref-syntax-ddl-create-table-like.html)
diff --git a/docs/sql-ref-syntax-ddl-create-table-like.md b/docs/sql-ref-syntax-ddl-create-table-like.md
index fe1dc4b1ef258..a374c554bd179 100644
--- a/docs/sql-ref-syntax-ddl-create-table-like.md
+++ b/docs/sql-ref-syntax-ddl-create-table-like.md
@@ -25,57 +25,46 @@ The `CREATE TABLE` statement defines a new table using the definition/metadata o
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 CREATE TABLE [IF NOT EXISTS] table_identifier LIKE source_table_identifier
     USING data_source
     [ ROW FORMAT row_format ]
     [ STORED AS file_format ]
     [ TBLPROPERTIES ( key1=val1, key2=val2, ... ) ]
     [ LOCATION path ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>  [ TBLPROPERTIES ( key1=val1, key2=val2, ... ) ]
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>USING data_source</em></code></dt>
-  <dd>Data Source is the input format used to create the table. Data source can be CSV, TXT, ORC, JDBC, PARQUET, etc.</dd>
-</dl> 
-
-<dl>
-  <dt><code><em>ROW FORMAT</em></code></dt>
-  <dd>SERDE is used to specify a custom SerDe or the DELIMITED clause in order to use the native SerDe.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>STORED AS</em></code></dt>
-  <dd>File format for table storage, could be TEXTFILE, ORC, PARQUET,etc.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>TBLPROPERTIES</em></code></dt>
-  <dd>Table properties that have to be set are specified, such as `created.by.user`, `owner`, etc.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>LOCATION</em></code></dt>
-  <dd>Path to the directory where table data is stored,Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc. Location to create an external table.</dd>
-</dl>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **USING data_source**
+
+    Data Source is the input format used to create the table. Data source can be CSV, TXT, ORC, JDBC, PARQUET, etc.
+
+* **ROW FORMAT**
+
+    SERDE is used to specify a custom SerDe or the DELIMITED clause in order to use the native SerDe.
+
+* **STORED AS**
+
+    File format for table storage, could be TEXTFILE, ORC, PARQUET,etc.
+
+* **TBLPROPERTIES**
+
+    Table properties that have to be set are specified, such as `created.by.user`, `owner`, etc.
+
+* **LOCATION**
+
+    Path to the directory where table data is stored,Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc. Location to create an external table.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Create table using an existing table
 CREATE TABLE Student_Dupli like Student;
 
@@ -90,10 +79,10 @@ CREATE TABLE Student_Dupli like Student
     ROW FORMAT DELIMITED FIELDS TERMINATED BY ','
     STORED AS TEXTFILE
     TBLPROPERTIES ('owner'='xxxx');
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE TABLE USING DATASOURCE](sql-ref-syntax-ddl-create-table-datasource.html)
- * [CREATE TABLE USING HIVE FORMAT](sql-ref-syntax-ddl-create-table-hiveformat.html)
+* [CREATE TABLE USING DATASOURCE](sql-ref-syntax-ddl-create-table-datasource.html)
+* [CREATE TABLE USING HIVE FORMAT](sql-ref-syntax-ddl-create-table-hiveformat.html)
 
diff --git a/docs/sql-ref-syntax-ddl-create-table.md b/docs/sql-ref-syntax-ddl-create-table.md
index b0388adbc9a38..85dc2020e6585 100644
--- a/docs/sql-ref-syntax-ddl-create-table.md
+++ b/docs/sql-ref-syntax-ddl-create-table.md
@@ -25,11 +25,11 @@ license: |
 
 The CREATE statements:
 
- * [CREATE TABLE USING DATA_SOURCE](sql-ref-syntax-ddl-create-table-datasource.html)
- * [CREATE TABLE USING HIVE FORMAT](sql-ref-syntax-ddl-create-table-hiveformat.html)
- * [CREATE TABLE LIKE](sql-ref-syntax-ddl-create-table-like.html)
+* [CREATE TABLE USING DATA_SOURCE](sql-ref-syntax-ddl-create-table-datasource.html)
+* [CREATE TABLE USING HIVE FORMAT](sql-ref-syntax-ddl-create-table-hiveformat.html)
+* [CREATE TABLE LIKE](sql-ref-syntax-ddl-create-table-like.html)
 
 ### Related Statements
 
- * [ALTER TABLE](sql-ref-syntax-ddl-alter-table.html)
- * [DROP TABLE](sql-ref-syntax-ddl-drop-table.html)
+* [ALTER TABLE](sql-ref-syntax-ddl-alter-table.html)
+* [DROP TABLE](sql-ref-syntax-ddl-drop-table.html)
diff --git a/docs/sql-ref-syntax-ddl-create-view.md b/docs/sql-ref-syntax-ddl-create-view.md
index ba8c1df1223a3..032bcbcf19ad3 100644
--- a/docs/sql-ref-syntax-ddl-create-view.md
+++ b/docs/sql-ref-syntax-ddl-create-view.md
@@ -27,55 +27,47 @@ a virtual table that has no physical data therefore other operations like
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 CREATE [ OR REPLACE ] [ [ GLOBAL ] TEMPORARY ] VIEW [ IF NOT EXISTS ] view_identifier
     create_view_clauses AS query
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>OR REPLACE</em></code></dt>
-  <dd>If a view of same name already exists, it will be replaced.</dd>
-</dl>
-<dl>
-  <dt><code><em>[ GLOBAL ] TEMPORARY</em></code></dt>
-  <dd>TEMPORARY views are session-scoped and will be dropped when session ends 
-      because it skips persisting the definition in the underlying metastore, if any.
-      GLOBAL TEMPORARY views are tied to a system preserved temporary database <code>global_temp</code>.</dd>
-</dl>
-<dl>
-  <dt><code><em>IF NOT EXISTS</em></code></dt>
-  <dd>Creates a view if it does not exists.</dd>
-</dl>
-<dl>
-  <dt><code><em>view_identifier</em></code></dt>
-  <dd>
-    Specifies a view name, which may be optionally qualified with a database name.<br><br>
-    <b> Syntax:</b>
-      <code>
-        [ database_name. ] view_name
-      </code>
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>create_view_clauses</em></code></dt>
-  <dd>These clauses are optional and order insensitive. It can be of following formats.
-    <ul>
-      <li><code>[ ( column_name [ COMMENT column_comment ], ... ) ]</code> to specify column-level comments.</li>
-      <li><code>[ COMMENT view_comment ]</code> to specify view-level comments.</li>
-      <li><code>[ TBLPROPERTIES ( property_name = property_value [ , ... ] ) ]</code> to add metadata key-value pairs.</li>
-    </ul>  
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>query</em></code></dt>
-  <dd>A <a href="sql-ref-syntax-qry-select.html">SELECT</a> statement that constructs the view from base tables or other views.</dd>
-</dl>
+* **OR REPLACE**
+
+    If a view of same name already exists, it will be replaced.
+
+* **[ GLOBAL ] TEMPORARY**
+
+    TEMPORARY views are session-scoped and will be dropped when session ends
+    because it skips persisting the definition in the underlying metastore, if any.
+    GLOBAL TEMPORARY views are tied to a system preserved temporary database `global_temp`.
+
+* **IF NOT EXISTS**
+
+    Creates a view if it does not exists.
+
+* **view_identifier**
+
+    Specifies a view name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] view_name`
+
+* **create_view_clauses**
+
+    These clauses are optional and order insensitive. It can be of following formats.
+
+    * `[ ( column_name [ COMMENT column_comment ], ... ) ]` to specify column-level comments.
+    * `[ COMMENT view_comment ]` to specify view-level comments.
+    * `[ TBLPROPERTIES ( property_name = property_value [ , ... ] ) ]` to add metadata key-value pairs.
+
+* **query**
+  A [SELECT](sql-ref-syntax-qry-select.html) statement that constructs the view from base tables or other views.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Create or replace view for `experienced_employee` with comments.
 CREATE OR REPLACE VIEW experienced_employee
     (ID COMMENT 'Unique identification number', Name) 
@@ -88,10 +80,10 @@ CREATE GLOBAL TEMPORARY VIEW IF NOT EXISTS subscribed_movies
     AS SELECT mo.member_id, mb.full_name, mo.movie_title
         FROM movies AS mo INNER JOIN members AS mb 
         ON mo.member_id = mb.id;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [ALTER VIEW](sql-ref-syntax-ddl-alter-view.html)
- * [DROP VIEW](sql-ref-syntax-ddl-drop-view.html)
- * [SHOW VIEWS](sql-ref-syntax-aux-show-views.html)
+* [ALTER VIEW](sql-ref-syntax-ddl-alter-view.html)
+* [DROP VIEW](sql-ref-syntax-ddl-drop-view.html)
+* [SHOW VIEWS](sql-ref-syntax-aux-show-views.html)
diff --git a/docs/sql-ref-syntax-ddl-drop-database.md b/docs/sql-ref-syntax-ddl-drop-database.md
index 7467e7a4ad6e7..4a3bc0c68b6d4 100644
--- a/docs/sql-ref-syntax-ddl-drop-database.md
+++ b/docs/sql-ref-syntax-ddl-drop-database.md
@@ -26,35 +26,31 @@ exception will be thrown if the database does not exist in the system.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 DROP { DATABASE | SCHEMA } [ IF EXISTS ] dbname [ RESTRICT | CASCADE ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>DATABASE | SCHEMA</em></code></dt>
-  <dd><code>DATABASE</code> and <code>SCHEMA</code> mean the same thing, either of them can be used.</dd>
-</dl>
+* **DATABASE `|` SCHEMA**
 
-<dl>
-  <dt><code><em>IF EXISTS</em></code></dt>
-  <dd>If specified, no exception is thrown when the database does not exist.</dd>
-</dl>
+    `DATABASE` and `SCHEMA` mean the same thing, either of them can be used.
 
-<dl>
-  <dt><code><em>RESTRICT</em></code></dt>
-  <dd>If specified, will restrict dropping a non-empty database and is enabled by default.</dd>
-</dl>
+* **IF EXISTS**
 
-<dl>
-  <dt><code><em>CASCADE</em></code></dt>
-  <dd>If specified, will drop all the associated tables and functions.</dd>
-</dl>
+    If specified, no exception is thrown when the database does not exist.
+
+* **RESTRICT**
+
+    If specified, will restrict dropping a non-empty database and is enabled by default.
+
+* **CASCADE**
+
+    If specified, will drop all the associated tables and functions.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Create `inventory_db` Database
 CREATE DATABASE inventory_db COMMENT 'This database is used to maintain Inventory';
 
@@ -63,10 +59,10 @@ DROP DATABASE inventory_db CASCADE;
 
 -- Drop the database using IF EXISTS
 DROP DATABASE IF EXISTS inventory_db CASCADE;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
- * [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
- * [SHOW DATABASES](sql-ref-syntax-aux-show-databases.html)
+* [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
+* [DESCRIBE DATABASE](sql-ref-syntax-aux-describe-database.html)
+* [SHOW DATABASES](sql-ref-syntax-aux-show-databases.html)
diff --git a/docs/sql-ref-syntax-ddl-drop-function.md b/docs/sql-ref-syntax-ddl-drop-function.md
index 66a405c24e413..b1b2ff9b1bb21 100644
--- a/docs/sql-ref-syntax-ddl-drop-function.md
+++ b/docs/sql-ref-syntax-ddl-drop-function.md
@@ -26,39 +26,32 @@ be thrown if the function does not exist.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 DROP [ TEMPORARY ] FUNCTION [ IF EXISTS ] function_name
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>function_name</em></code></dt>
-  <dd>
+* **function_name**
+
     Specifies the name of an existing function. The function name may be
-    optionally qualified with a database name. <br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] function_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>TEMPORARY</em></code></dt>
-  <dd>Should be used to delete the <code>TEMPORARY</code> function.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>IF EXISTS</em></code></dt>
-  <dd>If specified, no exception is thrown when the function does not exist.</dd>
-</dl>
+    optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] function_name`
+
+* **TEMPORARY**
+
+    Should be used to delete the `TEMPORARY` function.
+
+* **IF EXISTS**
+
+    If specified, no exception is thrown when the function does not exist.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Create a permanent function `test_avg`
-CREATE FUNCTION test_avg as 'org.apache.hadoop.hive.ql.udf.generic.GenericUDAFAverage';
+CREATE FUNCTION test_avg AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDAFAverage';
 
 -- List user functions
 SHOW USER FUNCTIONS;
@@ -100,10 +93,10 @@ SHOW USER FUNCTIONS;
   
 -- Drop Temporary function
 DROP TEMPORARY FUNCTION IF EXISTS test_avg;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE FUNCTION](sql-ref-syntax-ddl-create-function.html)
- * [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
- * [SHOW FUNCTION](sql-ref-syntax-aux-show-functions.html)
+* [CREATE FUNCTION](sql-ref-syntax-ddl-create-function.html)
+* [DESCRIBE FUNCTION](sql-ref-syntax-aux-describe-function.html)
+* [SHOW FUNCTION](sql-ref-syntax-aux-show-functions.html)
diff --git a/docs/sql-ref-syntax-ddl-drop-table.md b/docs/sql-ref-syntax-ddl-drop-table.md
index c943b922ae812..f2ff89993f2c3 100644
--- a/docs/sql-ref-syntax-ddl-drop-table.md
+++ b/docs/sql-ref-syntax-ddl-drop-table.md
@@ -28,30 +28,25 @@ In case of an external table, only the associated metadata information is remove
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 DROP TABLE [ IF EXISTS ] table_identifier
-{% endhighlight %}
+```
 
 ### Parameter
 
-<dl>
-  <dt><code><em>IF EXISTS</em></code></dt>
-  <dd>
-     If specified, no exception is thrown when the table does not exists.
-  </dd>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies the table name to be dropped. The table name may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
+* **IF EXISTS**
+
+    If specified, no exception is thrown when the table does not exists.
+
+* **table_identifier**
+
+    Specifies the table name to be dropped. The table name may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Assumes a table named `employeetable` exists.
 DROP TABLE employeetable;
 
@@ -67,10 +62,10 @@ DROP TABLE employeetable;
 -- Assumes a table named `employeetable` does not exists,Try with IF EXISTS
 -- this time it will not throw exception
 DROP TABLE IF EXISTS employeetable;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
- * [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
- * [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
+* [CREATE TABLE](sql-ref-syntax-ddl-create-table.html)
+* [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
+* [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
diff --git a/docs/sql-ref-syntax-ddl-drop-view.md b/docs/sql-ref-syntax-ddl-drop-view.md
index ad018b5e6fd5c..0f4a7ca6c9463 100644
--- a/docs/sql-ref-syntax-ddl-drop-view.md
+++ b/docs/sql-ref-syntax-ddl-drop-view.md
@@ -25,30 +25,25 @@ license: |
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 DROP VIEW [ IF EXISTS ] view_identifier
-{% endhighlight %}
+```
 
 ### Parameter
 
-<dl>
-  <dt><code><em>IF EXISTS</em></code></dt>
-  <dd>
-     If specified, no exception is thrown when the view does not exists.
-  </dd>
-  <dt><code><em>view_identifier</em></code></dt>
-  <dd>
-    Specifies the view name to be dropped. The view name may be optionally qualified with a database name.<br><br>
-    <b> Syntax:</b>
-      <code>
-        [ database_name. ] view_name
-      </code>
-  </dd>
-</dl>
+* **IF EXISTS**
+
+    If specified, no exception is thrown when the view does not exists.
+
+* **view_identifier**
+
+    Specifies the view name to be dropped. The view name may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] view_name`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Assumes a view named `employeeView` exists.
 DROP VIEW employeeView;
 
@@ -64,12 +59,12 @@ DROP VIEW employeeView;
 -- Assumes a view named `employeeView` does not exists,Try with IF EXISTS
 -- this time it will not throw exception
 DROP VIEW IF EXISTS employeeView;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE VIEW](sql-ref-syntax-ddl-create-view.html)
- * [ALTER VIEW](sql-ref-syntax-ddl-alter-view.html)
- * [SHOW VIEWS](sql-ref-syntax-aux-show-views.html)
- * [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
- * [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
+* [CREATE VIEW](sql-ref-syntax-ddl-create-view.html)
+* [ALTER VIEW](sql-ref-syntax-ddl-alter-view.html)
+* [SHOW VIEWS](sql-ref-syntax-aux-show-views.html)
+* [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
+* [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
diff --git a/docs/sql-ref-syntax-ddl-repair-table.md b/docs/sql-ref-syntax-ddl-repair-table.md
index c48b731512ad3..c2ef0a7b7fbe9 100644
--- a/docs/sql-ref-syntax-ddl-repair-table.md
+++ b/docs/sql-ref-syntax-ddl-repair-table.md
@@ -25,26 +25,21 @@ license: |
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 MSCK REPAIR TABLE table_identifier
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies the name of the table to be repaired. The table name may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
+* **table_identifier**
+
+    Specifies the name of the table to be repaired. The table name may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- create a partitioned table from existing data /tmp/namesAndAges.parquet
 CREATE TABLE t1 (name STRING, age INT) USING parquet PARTITIONED BY (age)
     LOCATION "/tmp/namesAndAges.parquet";
@@ -66,8 +61,8 @@ SELECT * FROM t1;
 +-------+---+
 |   Andy| 30|
 +-------+---+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [ALTER TABLE](sql-ref-syntax-ddl-alter-table.html)
+* [ALTER TABLE](sql-ref-syntax-ddl-alter-table.html)
diff --git a/docs/sql-ref-syntax-ddl-truncate-table.md b/docs/sql-ref-syntax-ddl-truncate-table.md
index 820f439f97a4b..6139814a3259a 100644
--- a/docs/sql-ref-syntax-ddl-truncate-table.md
+++ b/docs/sql-ref-syntax-ddl-truncate-table.md
@@ -27,37 +27,28 @@ in `partition_spec`. If no `partition_spec` is specified it will remove all part
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 TRUNCATE TABLE table_identifier [ partition_spec ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
     An optional parameter that specifies a comma separated list of key and value pairs
-    for partitions.<br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name  = partition_col_val [ , ... ] )
-      </code>
-  </dd>
-</dl>
+    for partitions.
+
+    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Create table Student with partition
 CREATE TABLE Student (name STRING, rollno INT) PARTITIONED BY (age INT);
 
@@ -89,9 +80,9 @@ SELECT * FROM Student;
 |name|rollno|age|
 +----+------+---+
 +----+------+---+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [DROP TABLE](sql-ref-syntax-ddl-drop-table.html)
- * [ALTER TABLE](sql-ref-syntax-ddl-alter-table.html)
+* [DROP TABLE](sql-ref-syntax-ddl-drop-table.html)
+* [ALTER TABLE](sql-ref-syntax-ddl-alter-table.html)
diff --git a/docs/sql-ref-syntax-dml-insert-into.md b/docs/sql-ref-syntax-dml-insert-into.md
index 924831f7feedd..ed5da2b2d28df 100644
--- a/docs/sql-ref-syntax-dml-insert-into.md
+++ b/docs/sql-ref-syntax-dml-insert-into.md
@@ -25,57 +25,43 @@ The `INSERT INTO` statement inserts new rows into a table. The inserted rows can
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 INSERT INTO [ TABLE ] table_identifier [ partition_spec ]
     { VALUES ( { value | NULL } [ , ... ] ) [ , ( ... ) ] | query }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
     An optional parameter that specifies a comma separated list of key and value pairs
-    for partitions.<br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name  = partition_col_val [ , ... ] )
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>VALUES ( { value | NULL } [ , ... ] ) [ , ( ... ) ]</em></code></dt>
-  <dd>Specifies the values to be inserted. Either an explicitly specified value or a NULL can be inserted. A comma must be used to separate each value in the clause. More than one set of values can be specified to insert multiple rows.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>query</em></code></dt>
-  <dd>A query that produces the rows to be inserted. It can be in one of following formats:
-    <ul>
-      <li>a <code>SELECT</code> statement</li>
-      <li>a <code>TABLE</code> statement</li>
-      <li>a <code>FROM</code> statement</li>
-    </ul>
-   </dd>
-</dl>
+    for partitions.
+
+    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
+
+* **VALUES ( { value `|` NULL } [ , ... ] ) [ , ( ... ) ]**
+
+    Specifies the values to be inserted. Either an explicitly specified value or a NULL can be inserted.
+    A comma must be used to separate each value in the clause. More than one set of values can be specified to insert multiple rows.
+
+* **query**
+
+    A query that produces the rows to be inserted. It can be in one of following formats:
+    * a `SELECT` statement
+    * a `TABLE` statement
+    * a `FROM` statement
 
 ### Examples
 
 #### Single Row Insert Using a VALUES Clause
 
-{% highlight sql %}
+```sql
 CREATE TABLE students (name VARCHAR(64), address VARCHAR(64), student_id INT)
     USING PARQUET PARTITIONED BY (student_id);
 
@@ -88,11 +74,11 @@ SELECT * FROM students;
 +---------+---------------------+----------+
 |Amy Smith|123 Park Ave,San Jose|    111111|
 +---------+---------------------+----------+
-{% endhighlight %}
+```
 
 #### Multi-Row Insert Using a VALUES Clause
 
-{% highlight sql %}
+```sql
 INSERT INTO students VALUES
     ('Bob Brown', '456 Taylor St, Cupertino', 222222),
     ('Cathy Johnson', '789 Race Ave, Palo Alto', 333333);
@@ -107,11 +93,11 @@ SELECT * FROM students;
 +-------------+------------------------+----------+
 |Cathy Johnson| 789 Race Ave, Palo Alto|    333333|
 +--------------+-----------------------+----------+
-{% endhighlight %}
+```
 
 #### Insert Using a SELECT Statement
 
-{% highlight sql %}
+```sql
 -- Assuming the persons table has already been created and populated.
 SELECT * FROM persons;
 +-------------+-------------------------+---------+
@@ -137,11 +123,11 @@ SELECT * FROM students;
 +-------------+-------------------------+----------+
 |Dora Williams|134 Forest Ave, Melo Park|    444444|
 +-------------+-------------------------+----------+
-{% endhighlight %}
+```
 
 #### Insert Using a TABLE Statement
 
-{% highlight sql %}
+```sql
 -- Assuming the visiting_students table has already been created and populated.
 SELECT * FROM visiting_students;
 +-------------+---------------------+----------+
@@ -170,11 +156,11 @@ SELECT * FROM students;
 +-------------+-------------------------+----------+
 |Gordon Martin|     779 Lake Ave, Oxford|    888888|
 +-------------+-------------------------+----------+
-{% endhighlight %}
+```
 
 #### Insert Using a FROM Statement
 
-{% highlight sql %}
+```sql
 -- Assuming the applicants table has already been created and populated.
 SELECT * FROM applicants;
 +-----------+--------------------------+----------+---------+
@@ -210,10 +196,10 @@ SELECT * FROM students;
 +-------------+-------------------------+----------+
 |   Jason Wang|    908 Bird St, Saratoga|    121212|
 +-------------+-------------------------+----------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [INSERT OVERWRITE statement](sql-ref-syntax-dml-insert-overwrite-table.html)
- * [INSERT OVERWRITE DIRECTORY statement](sql-ref-syntax-dml-insert-overwrite-directory.html)
- * [INSERT OVERWRITE DIRECTORY with Hive format statement](sql-ref-syntax-dml-insert-overwrite-directory-hive.html)
+* [INSERT OVERWRITE statement](sql-ref-syntax-dml-insert-overwrite-table.html)
+* [INSERT OVERWRITE DIRECTORY statement](sql-ref-syntax-dml-insert-overwrite-directory.html)
+* [INSERT OVERWRITE DIRECTORY with Hive format statement](sql-ref-syntax-dml-insert-overwrite-directory-hive.html)
diff --git a/docs/sql-ref-syntax-dml-insert-overwrite-directory-hive.md b/docs/sql-ref-syntax-dml-insert-overwrite-directory-hive.md
index 3cd2107668fbe..8ed6a3cd1be09 100644
--- a/docs/sql-ref-syntax-dml-insert-overwrite-directory-hive.md
+++ b/docs/sql-ref-syntax-dml-insert-overwrite-directory-hive.md
@@ -26,56 +26,41 @@ Hive support must be enabled to use this command. The inserted rows can be speci
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 INSERT OVERWRITE [ LOCAL ] DIRECTORY directory_path
     [ ROW FORMAT row_format ] [ STORED AS file_format ]
     { VALUES ( { value | NULL } [ , ... ] ) [ , ( ... ) ] | query }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>directory_path</em></code></dt>
-  <dd>
-  Specifies the destination directory. The <code>LOCAL</code> keyword is used to specify that the directory is on the local file system.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>row_format</em></code></dt>
-  <dd>
-  Specifies the row format for this insert. Valid options are <code>SERDE</code> clause and <code>DELIMITED</code> clause. <code>SERDE</code> clause can be used to specify a custom <code>SerDe</code> for this insert. Alternatively, <code>DELIMITED</code> clause can be used to specify the native <code>SerDe</code> and state the delimiter, escape character, null character, and so on.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>file_format</em></code></dt>
-  <dd>
-  Specifies the file format for this insert. Valid options are <code>TEXTFILE</code>, <code>SEQUENCEFILE</code>, <code>RCFILE</code>, <code>ORC</code>, <code>PARQUET</code>, and <code>AVRO</code>. You can also specify your own input and output format using <code>INPUTFORMAT</code> and <code>OUTPUTFORMAT</code>. <code>ROW FORMAT SERDE</code> can only be used with <code>TEXTFILE</code>, <code>SEQUENCEFILE</code>, or <code>RCFILE</code>, while <code>ROW FORMAT DELIMITED</code> can only be used with <code>TEXTFILE</code>.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>VALUES ( { value | NULL } [ , ... ] ) [ , ( ... ) ]</em></code></dt>
-  <dd>
-  Specifies the values to be inserted. Either an explicitly specified value or a NULL can be inserted. A comma must be used to separate each value in the clause. More than one set of values can be specified to insert multiple rows.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>query</em></code></dt>
-  <dd>A query that produces the rows to be inserted. It can be in one of following formats:
-    <ul>
-      <li>a <code>SELECT</code> statement</li>
-      <li>a <code>TABLE</code> statement</li>
-      <li>a <code>FROM</code> statement</li>
-    </ul>
-   </dd>
-</dl>
+* **directory_path**
+
+    Specifies the destination directory. The `LOCAL` keyword is used to specify that the directory is on the local file system.
+
+* **row_format**
+
+    Specifies the row format for this insert. Valid options are `SERDE` clause and `DELIMITED` clause. `SERDE` clause can be used to specify a custom `SerDe` for this insert. Alternatively, `DELIMITED` clause can be used to specify the native `SerDe` and state the delimiter, escape character, null character, and so on.
+
+* **file_format**
+
+    Specifies the file format for this insert. Valid options are `TEXTFILE`, `SEQUENCEFILE`, `RCFILE`, `ORC`, `PARQUET`, and `AVRO`. You can also specify your own input and output format using `INPUTFORMAT` and `OUTPUTFORMAT`. `ROW FORMAT SERDE` can only be used with `TEXTFILE`, `SEQUENCEFILE`, or `RCFILE`, while `ROW FORMAT DELIMITED` can only be used with `TEXTFILE`.
+
+* **VALUES ( { value `|` NULL } [ , ... ] ) [ , ( ... ) ]**
+
+    Specifies the values to be inserted. Either an explicitly specified value or a NULL can be inserted.
+    A comma must be used to separate each value in the clause. More than one set of values can be specified to insert multiple rows.
+
+* **query**
+
+    A query that produces the rows to be inserted. It can be in one of following formats:
+    * a `SELECT` statement
+    * a `TABLE` statement
+    * a `FROM` statement
 
 ### Examples
 
-{% highlight sql %}
+```sql
 INSERT OVERWRITE LOCAL DIRECTORY '/tmp/destination'
     STORED AS orc
     SELECT * FROM test_table;
@@ -83,10 +68,10 @@ INSERT OVERWRITE LOCAL DIRECTORY '/tmp/destination'
 INSERT OVERWRITE LOCAL DIRECTORY '/tmp/destination'
     ROW FORMAT DELIMITED FIELDS TERMINATED BY ','
     SELECT * FROM test_table;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [INSERT INTO statement](sql-ref-syntax-dml-insert-into.html)
- * [INSERT OVERWRITE statement](sql-ref-syntax-dml-insert-overwrite-table.html)
- * [INSERT OVERWRITE DIRECTORY statement](sql-ref-syntax-dml-insert-overwrite-directory.html)
+* [INSERT INTO statement](sql-ref-syntax-dml-insert-into.html)
+* [INSERT OVERWRITE statement](sql-ref-syntax-dml-insert-overwrite-table.html)
+* [INSERT OVERWRITE DIRECTORY statement](sql-ref-syntax-dml-insert-overwrite-directory.html)
diff --git a/docs/sql-ref-syntax-dml-insert-overwrite-directory.md b/docs/sql-ref-syntax-dml-insert-overwrite-directory.md
index 6ce7f50588e32..fd7437d37c909 100644
--- a/docs/sql-ref-syntax-dml-insert-overwrite-directory.md
+++ b/docs/sql-ref-syntax-dml-insert-overwrite-directory.md
@@ -25,54 +25,42 @@ The `INSERT OVERWRITE DIRECTORY` statement overwrites the existing data in the d
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 INSERT OVERWRITE [ LOCAL ] DIRECTORY [ directory_path ]
     USING file_format [ OPTIONS ( key = val [ , ... ] ) ]
     { VALUES ( { value | NULL } [ , ... ] ) [ , ( ... ) ] | query }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>directory_path</em></code></dt>
-  <dd>
-  Specifies the destination directory. It can also be specified in <code>OPTIONS</code> using <code>path</code>. The <code>LOCAL</code> keyword is used to specify that the directory is on the local file system.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>file_format</em></code></dt>
-  <dd>
-  Specifies the file format to use for the insert. Valid options are <code>TEXT</code>, <code>CSV</code>, <code>JSON</code>, <code>JDBC</code>, <code>PARQUET</code>, <code>ORC</code>, <code>HIVE</code>, <code>LIBSVM</code>, or a fully qualified class name of a custom implementation of <code>org.apache.spark.sql.execution.datasources.FileFormat</code>.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>OPTIONS ( key = val [ , ... ] )</em></code></dt>
-  <dd>Specifies one or more options for the writing of the file format.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>VALUES ( { value | NULL } [ , ... ] ) [ , ( ... ) ]</em></code></dt>
-  <dd>
-  Specifies the values to be inserted. Either an explicitly specified value or a NULL can be inserted. A comma must be used to separate each value in the clause. More than one set of values can be specified to insert multiple rows.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>query</em></code></dt>
-  <dd>A query that produces the rows to be inserted. It can be in one of following formats:
-    <ul>
-      <li>a <code>SELECT</code> statement</li>
-      <li>a <code>TABLE</code> statement</li>
-      <li>a <code>FROM</code> statement</li>
-    </ul>
-   </dd>
-</dl>
+* **directory_path**
+
+    Specifies the destination directory. It can also be specified in `OPTIONS` using `path`.
+    The `LOCAL` keyword is used to specify that the directory is on the local file system.
+
+* **file_format**
+
+    Specifies the file format to use for the insert. Valid options are `TEXT`, `CSV`, `JSON`, `JDBC`, `PARQUET`, `ORC`, `HIVE`, `LIBSVM`, or a fully qualified class name of a custom implementation of `org.apache.spark.sql.execution.datasources.FileFormat`.
+
+* **OPTIONS ( key = val [ , ... ] )**
+
+    Specifies one or more options for the writing of the file format.
+
+* **VALUES ( { value `|` NULL } [ , ... ] ) [ , ( ... ) ]**
+
+    Specifies the values to be inserted. Either an explicitly specified value or a NULL can be inserted.
+    A comma must be used to separate each value in the clause. More than one set of values can be specified to insert multiple rows.
+
+* **query**
+
+    A query that produces the rows to be inserted. It can be in one of following formats:
+    * a `SELECT` statement
+    * a `TABLE` statement
+    * a `FROM` statement
 
 ### Examples
 
-{% highlight sql %}
+```sql
 INSERT OVERWRITE DIRECTORY '/tmp/destination'
     USING parquet
     OPTIONS (col1 1, col2 2, col3 'test')
@@ -82,10 +70,10 @@ INSERT OVERWRITE DIRECTORY
     USING parquet
     OPTIONS ('path' '/tmp/destination', col1 1, col2 2, col3 'test')
     SELECT * FROM test_table;
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [INSERT INTO statement](sql-ref-syntax-dml-insert-into.html)
- * [INSERT OVERWRITE statement](sql-ref-syntax-dml-insert-overwrite-table.html)
- * [INSERT OVERWRITE DIRECTORY with Hive format statement](sql-ref-syntax-dml-insert-overwrite-directory-hive.html)
+* [INSERT INTO statement](sql-ref-syntax-dml-insert-into.html)
+* [INSERT OVERWRITE statement](sql-ref-syntax-dml-insert-overwrite-table.html)
+* [INSERT OVERWRITE DIRECTORY with Hive format statement](sql-ref-syntax-dml-insert-overwrite-directory-hive.html)
diff --git a/docs/sql-ref-syntax-dml-insert-overwrite-table.md b/docs/sql-ref-syntax-dml-insert-overwrite-table.md
index 5c760f00ed0c4..ecfd060dfd5ee 100644
--- a/docs/sql-ref-syntax-dml-insert-overwrite-table.md
+++ b/docs/sql-ref-syntax-dml-insert-overwrite-table.md
@@ -25,57 +25,43 @@ The `INSERT OVERWRITE` statement overwrites the existing data in the table using
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 INSERT OVERWRITE [ TABLE ] table_identifier [ partition_spec [ IF NOT EXISTS ] ]
     { VALUES ( { value | NULL } [ , ... ] ) [ , ( ... ) ] | query }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
     An optional parameter that specifies a comma separated list of key and value pairs
-    for partitions.<br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name [ = partition_col_val ] [ , ... ] )
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>VALUES ( { value | NULL } [ , ... ] ) [ , ( ... ) ]</em></code></dt>
-  <dd>Specifies the values to be inserted. Either an explicitly specified value or a NULL can be inserted. A comma must be used to separate each value in the clause. More than one set of values can be specified to insert multiple rows.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>query</em></code></dt>
-  <dd>A query that produces the rows to be inserted. It can be in one of following formats:
-    <ul>
-      <li>a <code>SELECT</code> statement</li>
-      <li>a <code>TABLE</code> statement</li>
-      <li>a <code>FROM</code> statement</li>
-    </ul>
-   </dd>
-</dl>
+    for partitions.
+
+    **Syntax:** `PARTITION ( partition_col_name [ = partition_col_val ] [ , ... ] )`
+
+* **VALUES ( { value `|` NULL } [ , ... ] ) [ , ( ... ) ]**
+
+    Specifies the values to be inserted. Either an explicitly specified value or a NULL can be inserted.
+    A comma must be used to separate each value in the clause. More than one set of values can be specified to insert multiple rows.
+
+* **query**
+
+    A query that produces the rows to be inserted. It can be in one of following formats:
+    * a `SELECT` statement
+    * a `TABLE` statement
+    * a `FROM` statement
 
 ### Examples
 
 #### Insert Using a VALUES Clause
 
-{% highlight sql %}
+```sql
 -- Assuming the students table has already been created and populated.
 SELECT * FROM students;
 +-------------+-------------------------+----------+
@@ -102,12 +88,11 @@ SELECT * FROM students;
 |Ashua Hill|456 Erica Ct, Cupertino|    111111|
 |Brian Reed|723 Kern Ave, Palo Alto|    222222|
 +----------+-----------------------+----------+
-
-{% endhighlight %}
+```
 
 #### Insert Using a SELECT Statement
 
-{% highlight sql %}
+```sql
 -- Assuming the persons table has already been created and populated.
 SELECT * FROM persons;
 +-------------+-------------------------+---------+
@@ -129,11 +114,11 @@ SELECT * FROM students;
 +-------------+-------------------------+----------+
 |Dora Williams|134 Forest Ave, Melo Park|    222222|
 +-------------+-------------------------+----------+
-{% endhighlight %}
+```
 
 #### Insert Using a TABLE Statement
 
-{% highlight sql %}
+```sql
 -- Assuming the visiting_students table has already been created and populated.
 SELECT * FROM visiting_students;
 +-------------+---------------------+----------+
@@ -154,11 +139,11 @@ SELECT * FROM students;
 +-------------+---------------------+----------+
 |Gordon Martin| 779 Lake Ave, Oxford|    888888|
 +-------------+---------------------+----------+
-{% endhighlight %}
+```
 
 #### Insert Using a FROM Statement
 
-{% highlight sql %}
+```sql
 -- Assuming the applicants table has already been created and populated.
 SELECT * FROM applicants;
 +-----------+--------------------------+----------+---------+
@@ -182,10 +167,10 @@ SELECT * FROM students;
 +-----------+-------------------------+----------+
 | Jason Wang|    908 Bird St, Saratoga|    121212|
 +-----------+-------------------------+----------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [INSERT INTO statement](sql-ref-syntax-dml-insert-into.html)
- * [INSERT OVERWRITE DIRECTORY statement](sql-ref-syntax-dml-insert-overwrite-directory.html)
- * [INSERT OVERWRITE DIRECTORY with Hive format statement](sql-ref-syntax-dml-insert-overwrite-directory-hive.html)
+* [INSERT INTO statement](sql-ref-syntax-dml-insert-into.html)
+* [INSERT OVERWRITE DIRECTORY statement](sql-ref-syntax-dml-insert-overwrite-directory.html)
+* [INSERT OVERWRITE DIRECTORY with Hive format statement](sql-ref-syntax-dml-insert-overwrite-directory-hive.html)
diff --git a/docs/sql-ref-syntax-dml-insert.md b/docs/sql-ref-syntax-dml-insert.md
index 2345add2460c8..62f6dee876450 100644
--- a/docs/sql-ref-syntax-dml-insert.md
+++ b/docs/sql-ref-syntax-dml-insert.md
@@ -21,7 +21,7 @@ license: |
 
 The INSERT statements:
 
- * [INSERT INTO statement](sql-ref-syntax-dml-insert-into.html)
- * [INSERT OVERWRITE statement](sql-ref-syntax-dml-insert-overwrite-table.html)
- * [INSERT OVERWRITE DIRECTORY statement](sql-ref-syntax-dml-insert-overwrite-directory.html)
- * [INSERT OVERWRITE DIRECTORY with Hive format statement](sql-ref-syntax-dml-insert-overwrite-directory-hive.html)
+* [INSERT INTO statement](sql-ref-syntax-dml-insert-into.html)
+* [INSERT OVERWRITE statement](sql-ref-syntax-dml-insert-overwrite-table.html)
+* [INSERT OVERWRITE DIRECTORY statement](sql-ref-syntax-dml-insert-overwrite-directory.html)
+* [INSERT OVERWRITE DIRECTORY with Hive format statement](sql-ref-syntax-dml-insert-overwrite-directory-hive.html)
diff --git a/docs/sql-ref-syntax-dml-load.md b/docs/sql-ref-syntax-dml-load.md
index 01ece31bd17fa..9381b4267fb24 100644
--- a/docs/sql-ref-syntax-dml-load.md
+++ b/docs/sql-ref-syntax-dml-load.md
@@ -25,53 +25,40 @@ license: |
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 LOAD DATA [ LOCAL ] INPATH path [ OVERWRITE ] INTO TABLE table_identifier [ partition_spec ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>path</em></code></dt>
-  <dd>Path of the file system. It can be either an absolute or a relative path.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>table_identifier</em></code></dt>
-  <dd>
-    Specifies a table name, which may be optionally qualified with a database name.<br><br>
-    <b>Syntax:</b>
-      <code>
-        [ database_name. ] table_name
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>partition_spec</em></code></dt>
-  <dd>
+* **path**
+
+    Path of the file system. It can be either an absolute or a relative path.
+
+* **table_identifier**
+
+    Specifies a table name, which may be optionally qualified with a database name.
+
+    **Syntax:** `[ database_name. ] table_name`
+
+* **partition_spec**
+
     An optional parameter that specifies a comma separated list of key and value pairs
-    for partitions.<br><br>
-    <b>Syntax:</b>
-      <code>
-        PARTITION ( partition_col_name = partition_col_val [ , ... ] )
-      </code>
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>LOCAL</em></code></dt>
-  <dd>If specified, it causes the <code>INPATH</code> to be resolved against the local file system, instead of the default file system, which is typically a distributed storage.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>OVERWRITE</em></code></dt>
-  <dd>By default, new data is appended to the table. If <code>OVERWRITE</code> is used, the table is instead overwritten with new data.</dd>
-</dl>
+    for partitions.
+
+    **Syntax:** `PARTITION ( partition_col_name = partition_col_val [ , ... ] )`
+
+* **LOCAL**
+
+    If specified, it causes the `INPATH` to be resolved against the local file system, instead of the default file system, which is typically a distributed storage.
+
+* **OVERWRITE**
+
+    By default, new data is appended to the table. If `OVERWRITE` is used, the table is instead overwritten with new data.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Example without partition specification.
 -- Assuming the students table has already been created and populated.
 SELECT * FROM students;
@@ -123,4 +110,4 @@ SELECT * FROM test_load_partition;
 +---+---+---+
 |  1|  2|  3|
 +---+---+---+
-{% endhighlight %}
+```
diff --git a/docs/sql-ref-syntax-dml.md b/docs/sql-ref-syntax-dml.md
index 9f75990555f64..fc408e1d38d26 100644
--- a/docs/sql-ref-syntax-dml.md
+++ b/docs/sql-ref-syntax-dml.md
@@ -21,5 +21,5 @@ license: |
 
 Data Manipulation Statements are used to add, change, or delete data. Spark SQL supports the following Data Manipulation Statements:
 
- * [INSERT](sql-ref-syntax-dml-insert.html)
- * [LOAD](sql-ref-syntax-dml-load.html)
+* [INSERT](sql-ref-syntax-dml-insert.html)
+* [LOAD](sql-ref-syntax-dml-load.html)
diff --git a/docs/sql-ref-syntax-qry-explain.md b/docs/sql-ref-syntax-qry-explain.md
index 298a2edaea1f2..7b84264a28cca 100644
--- a/docs/sql-ref-syntax-qry-explain.md
+++ b/docs/sql-ref-syntax-qry-explain.md
@@ -26,46 +26,38 @@ By default, this clause provides information about a physical plan only.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 EXPLAIN [ EXTENDED | CODEGEN | COST | FORMATTED ] statement
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>EXTENDED</em></code></dt>
-  <dd>Generates parsed logical plan, analyzed logical plan, optimized logical plan and physical plan.
-   Parsed Logical plan is a unresolved plan that extracted from the query.
-   Analyzed logical plans transforms which translates unresolvedAttribute and unresolvedRelation into fully typed objects.
-   The optimized logical plan transforms through a set of optimization rules, resulting in the physical plan.
-  </dd>
-</dl> 
-
-<dl>
-  <dt><code><em>CODEGEN</em></code></dt>
-  <dd>Generates code for the statement, if any and a physical plan.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>COST</em></code></dt>
-  <dd>If plan node statistics are available, generates a logical plan and the statistics.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>FORMATTED</em></code></dt>
-  <dd>Generates two sections: a physical plan outline and node details.</dd>
-</dl>
-
-<dl>
-  <dt><code><em>statement</em></code></dt>
-  <dd>
+* **EXTENDED**
+
+    Generates parsed logical plan, analyzed logical plan, optimized logical plan and physical plan.
+    Parsed Logical plan is a unresolved plan that extracted from the query.
+    Analyzed logical plans transforms which translates unresolvedAttribute and unresolvedRelation into fully typed objects.
+    The optimized logical plan transforms through a set of optimization rules, resulting in the physical plan.
+
+* **CODEGEN**
+
+    Generates code for the statement, if any and a physical plan.
+
+* **COST**
+
+    If plan node statistics are available, generates a logical plan and the statistics.
+
+* **FORMATTED**
+
+    Generates two sections: a physical plan outline and node details.
+
+* **statement**
+
     Specifies a SQL statement to be explained.
-  </dd>
- </dl>
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Default Output
 EXPLAIN select k, sum(v) from values (1, 2), (1, 3) t(k, v) group by k;
 +----------------------------------------------------+
@@ -132,4 +124,4 @@ EXPLAIN FORMATTED select k, sum(v) from values (1, 2), (1, 3) t(k, v) group by k
  Input: [k#19, sum#24L]
 |
 +----------------------------------------------------+
-{% endhighlight %}
+```
diff --git a/docs/sql-ref-syntax-qry-sampling.md b/docs/sql-ref-syntax-qry-sampling.md
index 82f6588e6c504..28e21e802fe25 100644
--- a/docs/sql-ref-syntax-qry-sampling.md
+++ b/docs/sql-ref-syntax-qry-sampling.md
@@ -30,15 +30,15 @@ Note: `TABLESAMPLE` returns the approximate number of rows or fraction requested
 
 ### Syntax
 
-{% highlight sql %}
-TABLESAMPLE ((integer_expression | decimal_expression) PERCENT)
-    | TABLESAMPLE (integer_expression ROWS)
-    | TABLESAMPLE (BUCKET integer_expression OUT OF integer_expression)
-{% endhighlight %}
+```sql
+TABLESAMPLE ({ integer_expression | decimal_expression } PERCENT)
+    | TABLESAMPLE ( integer_expression ROWS )
+    | TABLESAMPLE ( BUCKET integer_expression OUT OF integer_expression )
+```
 
 ### Examples
 
-{% highlight sql %}
+```sql
 SELECT * FROM test;
 +--+----+
 |id|name|
@@ -87,8 +87,8 @@ SELECT * FROM test TABLESAMPLE (BUCKET 4 OUT OF 10);
 | 9|Eric|
 | 6|Mark|
 +--+----+
-{% endhighlight %}
+```
 
-### Related Statement
+### Related Statements
 
-  * [SELECT](sql-ref-syntax-qry-select.html)
\ No newline at end of file
+* [SELECT](sql-ref-syntax-qry-select.html)
\ No newline at end of file
diff --git a/docs/sql-ref-syntax-qry-select-clusterby.md b/docs/sql-ref-syntax-qry-select-clusterby.md
index ac1e1ccb00ac9..e3bd2ed926ecc 100644
--- a/docs/sql-ref-syntax-qry-select-clusterby.md
+++ b/docs/sql-ref-syntax-qry-select-clusterby.md
@@ -21,7 +21,7 @@ license: |
 
 ### Description
 
-The <code>CLUSTER BY</code> clause is used to first repartition the data based
+The `CLUSTER BY` clause is used to first repartition the data based
 on the input expressions and then sort the data within each partition. This is
 semantically equivalent to performing a
 [DISTRIBUTE BY](sql-ref-syntax-qry-select-distribute-by.html) followed by a
@@ -30,22 +30,19 @@ resultant rows are sorted within each partition and does not guarantee a total o
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 CLUSTER BY { expression [ , ... ] }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>expression</em></code></dt>
-  <dd>
+* **expression**
+
     Specifies combination of one or more values, operators and SQL functions that results in a value.
-  </dd>
-</dl>
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE person (name STRING, age INT);
 INSERT INTO person VALUES
     ('Zen Hui', 25),
@@ -90,15 +87,15 @@ SELECT age, name FROM person CLUSTER BY age;
 | 16|Shone S|
 | 16| Jack N|
 +---+-------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SELECT Main](sql-ref-syntax-qry-select.html)
- * [WHERE Clause](sql-ref-syntax-qry-select-where.html)
- * [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
- * [HAVING Clause](sql-ref-syntax-qry-select-having.html)
- * [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
- * [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
- * [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
- * [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
+* [SELECT Main](sql-ref-syntax-qry-select.html)
+* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
+* [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
+* [HAVING Clause](sql-ref-syntax-qry-select-having.html)
+* [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
+* [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
+* [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
+* [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
diff --git a/docs/sql-ref-syntax-qry-select-cte.md b/docs/sql-ref-syntax-qry-select-cte.md
index 2408c884c64b5..351de64a2d026 100644
--- a/docs/sql-ref-syntax-qry-select-cte.md
+++ b/docs/sql-ref-syntax-qry-select-cte.md
@@ -25,33 +25,28 @@ A common table expression (CTE) defines a temporary result set that a user can r
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 WITH common_table_expression [ , ... ]
-{% endhighlight %}
+```
 
 While `common_table_expression` is defined as
-{% highlight sql %}
-expression_name [ ( column_name [ , ... ] ) ] [ AS ] ( [ common_table_expression ] query )
-{% endhighlight %}
+```sql
+expression_name [ ( column_name [ , ... ] ) ] [ AS ] ( query )
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>expression_name</em></code></dt>
-  <dd>
+* **expression_name**
+
     Specifies a name for the common table expression.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>query</em></code></dt>
-  <dd>
-    A <a href="sql-ref-syntax-qry-select.html">SELECT</a> statement.
-  </dd>
-</dl>
+
+* **query**
+
+    A [SELECT statement](sql-ref-syntax-qry-select.html).
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- CTE with multiple column aliases
 WITH t(x, y) AS (SELECT 1, 2)
 SELECT * FROM t WHERE x = 1 AND y = 2;
@@ -62,7 +57,7 @@ SELECT * FROM t WHERE x = 1 AND y = 2;
 +---+---+
 
 -- CTE in CTE definition
-WITH t as (
+WITH t AS (
     WITH t2 AS (SELECT 1)
     SELECT * FROM t2
 )
@@ -122,8 +117,8 @@ SELECT * FROM t2;
 +---+
 |  2|
 +---+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SELECT](sql-ref-syntax-qry-select.html)
+* [SELECT](sql-ref-syntax-qry-select.html)
diff --git a/docs/sql-ref-syntax-qry-select-distribute-by.md b/docs/sql-ref-syntax-qry-select-distribute-by.md
index 9e2db27ae7161..1fdfb91dad286 100644
--- a/docs/sql-ref-syntax-qry-select-distribute-by.md
+++ b/docs/sql-ref-syntax-qry-select-distribute-by.md
@@ -21,28 +21,25 @@ license: |
 
 ### Description
 
-The <code>DISTRIBUTE BY</code> clause is used to repartition the data based
+The `DISTRIBUTE BY` clause is used to repartition the data based
 on the input expressions. Unlike the [CLUSTER BY](sql-ref-syntax-qry-select-clusterby.html)
 clause, this does not sort the data within each partition.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 DISTRIBUTE BY { expression [ , ... ] }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>expression</em></code></dt>
-  <dd>
+* **expression**
+
     Specifies combination of one or more values, operators and SQL functions that results in a value.
-  </dd>
-</dl>
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE person (name STRING, age INT);
 INSERT INTO person VALUES
     ('Zen Hui', 25),
@@ -85,15 +82,15 @@ SELECT age, name FROM person DISTRIBUTE BY age;
 | 16|Shone S|
 | 16| Jack N|
 +---+-------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SELECT Main](sql-ref-syntax-qry-select.html)
- * [WHERE Clause](sql-ref-syntax-qry-select-where.html)
- * [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
- * [HAVING Clause](sql-ref-syntax-qry-select-having.html)
- * [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
- * [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
- * [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
- * [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
+* [SELECT Main](sql-ref-syntax-qry-select.html)
+* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
+* [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
+* [HAVING Clause](sql-ref-syntax-qry-select-having.html)
+* [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
+* [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
+* [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
+* [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
diff --git a/docs/sql-ref-syntax-qry-select-groupby.md b/docs/sql-ref-syntax-qry-select-groupby.md
index 22fe782f9eaa7..bd9377ef78df6 100644
--- a/docs/sql-ref-syntax-qry-select-groupby.md
+++ b/docs/sql-ref-syntax-qry-select-groupby.md
@@ -21,84 +21,79 @@ license: |
 
 ### Description
 
-The <code>GROUP BY</code> clause is used to group the rows based on a set of specified grouping expressions and compute aggregations on
+The `GROUP BY` clause is used to group the rows based on a set of specified grouping expressions and compute aggregations on
 the group of rows based on one or more specified aggregate functions. Spark also supports advanced aggregations to do multiple
 aggregations for the same input record set via `GROUPING SETS`, `CUBE`, `ROLLUP` clauses.
 When a FILTER clause is attached to an aggregate function, only the matching rows are passed to that function.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 GROUP BY group_expression [ , group_expression [ , ... ] ]
     [ { WITH ROLLUP | WITH CUBE | GROUPING SETS (grouping_set [ , ...]) } ]
 
 GROUP BY GROUPING SETS (grouping_set [ , ...])
-{% endhighlight %}
+```
 
 While aggregate functions are defined as
-{% highlight sql %}
+```sql
 aggregate_name ( [ DISTINCT ] expression [ , ... ] ) [ FILTER ( WHERE boolean_expression ) ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>GROUPING SETS</em></code></dt>
-  <dd>
+* **GROUPING SETS**
+
     Groups the rows for each subset of the expressions specified in the grouping sets. For example,
-    <code>GROUP BY GROUPING SETS (warehouse, product)</code> is semantically equivalent
-    to union of results of <code>GROUP BY warehouse</code> and <code>GROUP BY product</code>. This clause
-    is a shorthand for a <code>UNION ALL</code> where each leg of the <code>UNION ALL</code>
-    operator performs aggregation of subset of the columns specified in the <code>GROUPING SETS</code> clause.
-  </dd>
-  <dt><code><em>grouping_set</em></code></dt>
-  <dd>
-    A grouping set is specified by zero or more comma-separated expressions in parentheses.<br><br>
-    <b>Syntax:</b>
-      <code>
-        ([expression [, ...]])
-      </code>
-  </dd>
-  <dt><code><em>grouping_expression</em></code></dt>
-  <dd>
+    `GROUP BY GROUPING SETS (warehouse, product)` is semantically equivalent
+    to union of results of `GROUP BY warehouse` and `GROUP BY product`. This clause
+    is a shorthand for a `UNION ALL` where each leg of the `UNION ALL`
+    operator performs aggregation of subset of the columns specified in the `GROUPING SETS` clause.
+
+* **grouping_set**
+
+    A grouping set is specified by zero or more comma-separated expressions in parentheses.
+
+    **Syntax:** `( [ expression [ , ... ] ] )`
+
+* **grouping_expression**
+
     Specifies the critieria based on which the rows are grouped together. The grouping of rows is performed based on
     result values of the grouping expressions. A grouping expression may be a column alias, a column position
     or an expression.
-  </dd>
-  <dt><code><em>ROLLUP</em></code></dt>
-  <dd>
+
+* **ROLLUP**
+
     Specifies multiple levels of aggregations in a single statement. This clause is used to compute aggregations
-    based on multiple grouping sets. <code>ROLLUP</code> is a shorthand for <code>GROUPING SETS</code>. For example,
-    <code>GROUP BY warehouse, product WITH ROLLUP</code> is equivalent to <code>GROUP BY GROUPING SETS
-    ((warehouse, product), (warehouse), ())</code>.
-    The N elements of a <code>ROLLUP</code> specification results in N+1 <code>GROUPING SETS</code>.
-  </dd>
-  <dt><code><em>CUBE</em></code></dt>
-  <dd>
-    <code>CUBE</code> clause is used to perform aggregations based on combination of grouping columns specified in the
-    <code>GROUP BY</code> clause. <code>CUBE</code> is a shorthand for <code>GROUPING SETS</code>. For example,
-    <code>GROUP BY warehouse, product WITH CUBE</code> is equivalent to <code>GROUP BY GROUPING SETS
-    ((warehouse, product), (warehouse), (product), ())</code>.
-    The N elements of a <code>CUBE</code> specification results in 2^N <code>GROUPING SETS</code>.
-  </dd>
-  <dt><code><em>aggregate_name</em></code></dt>
-  <dd>
+    based on multiple grouping sets. `ROLLUP` is a shorthand for `GROUPING SETS`. For example,
+    `GROUP BY warehouse, product WITH ROLLUP` is equivalent to `GROUP BY GROUPING SETS
+    ((warehouse, product), (warehouse), ())`.
+    The N elements of a `ROLLUP` specification results in N+1 `GROUPING SETS`.
+
+* **CUBE**
+
+    `CUBE` clause is used to perform aggregations based on combination of grouping columns specified in the
+    `GROUP BY` clause. `CUBE` is a shorthand for `GROUPING SETS`. For example,
+    `GROUP BY warehouse, product WITH CUBE` is equivalent to `GROUP BY GROUPING SETS
+    ((warehouse, product), (warehouse), (product), ())`.
+    The N elements of a `CUBE` specification results in 2^N `GROUPING SETS`.
+
+* **aggregate_name**
+
     Specifies an aggregate function name (MIN, MAX, COUNT, SUM, AVG, etc.).
-  </dd>
-  <dt><code><em>DISTINCT</em></code></dt>
-  <dd>
+
+* **DISTINCT**
+
     Removes duplicates in input rows before they are passed to aggregate functions.
-  </dd>
-  <dt><code><em>FILTER</em></code></dt>
-  <dd>
-    Filters the input rows for which the <code>boolean_expression</code> in the <code>WHERE</code> clause evaluates
+
+* **FILTER**
+
+    Filters the input rows for which the `boolean_expression` in the `WHERE` clause evaluates
     to true are passed to the aggregate function; other rows are discarded.
-  </dd>
-</dl>
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE dealer (id INT, city STRING, car_model STRING, quantity INT);
 INSERT INTO dealer VALUES
     (100, 'Fremont', 'Honda Civic', 10),
@@ -174,106 +169,106 @@ SELECT id, sum(quantity) FILTER (
 SELECT city, car_model, sum(quantity) AS sum FROM dealer
     GROUP BY GROUPING SETS ((city, car_model), (city), (car_model), ())
     ORDER BY city;
-+--------+------------+---+
-|    city|   car_model|sum|
-+--------+------------+---+
-|    null|        null| 78|
-|    null| HondaAccord| 33|
-|    null|    HondaCRV| 10|
-|    null|  HondaCivic| 35|
-|  Dublin|        null| 33|
-|  Dublin| HondaAccord| 10|
-|  Dublin|    HondaCRV|  3|
-|  Dublin|  HondaCivic| 20|
-| Fremont|        null| 32|
-| Fremont| HondaAccord| 15|
-| Fremont|    HondaCRV|  7|
-| Fremont|  HondaCivic| 10|
-| SanJose|        null| 13|
-| SanJose| HondaAccord|  8|
-| SanJose|  HondaCivic|  5|
-+--------+------------+---+
++---------+------------+---+
+|     city|   car_model|sum|
++---------+------------+---+
+|     null|        null| 78|
+|     null| HondaAccord| 33|
+|     null|    HondaCRV| 10|
+|     null|  HondaCivic| 35|
+|   Dublin|        null| 33|
+|   Dublin| HondaAccord| 10|
+|   Dublin|    HondaCRV|  3|
+|   Dublin|  HondaCivic| 20|
+|  Fremont|        null| 32|
+|  Fremont| HondaAccord| 15|
+|  Fremont|    HondaCRV|  7|
+|  Fremont|  HondaCivic| 10|
+| San Jose|        null| 13|
+| San Jose| HondaAccord|  8|
+| San Jose|  HondaCivic|  5|
++---------+------------+---+
 
 -- Alternate syntax for `GROUPING SETS` in which both `GROUP BY` and `GROUPING SETS`
 -- specifications are present.
 SELECT city, car_model, sum(quantity) AS sum FROM dealer
     GROUP BY city, car_model GROUPING SETS ((city, car_model), (city), (car_model), ())
     ORDER BY city, car_model;
-+--------+------------+---+
-|    city|   car_model|sum|
-+--------+------------+---+
-|    null|        null| 78|
-|    null| HondaAccord| 33|
-|    null|    HondaCRV| 10|
-|    null|  HondaCivic| 35|
-|  Dublin|        null| 33|
-|  Dublin| HondaAccord| 10|
-|  Dublin|    HondaCRV|  3|
-|  Dublin|  HondaCivic| 20|
-| Fremont|        null| 32|
-| Fremont| HondaAccord| 15|
-| Fremont|    HondaCRV|  7|
-| Fremont|  HondaCivic| 10|
-| SanJose|        null| 13|
-| SanJose| HondaAccord|  8|
-| SanJose|  HondaCivic|  5|
-+--------+------------+---+
++---------+------------+---+
+|     city|   car_model|sum|
++---------+------------+---+
+|     null|        null| 78|
+|     null| HondaAccord| 33|
+|     null|    HondaCRV| 10|
+|     null|  HondaCivic| 35|
+|   Dublin|        null| 33|
+|   Dublin| HondaAccord| 10|
+|   Dublin|    HondaCRV|  3|
+|   Dublin|  HondaCivic| 20|
+|  Fremont|        null| 32|
+|  Fremont| HondaAccord| 15|
+|  Fremont|    HondaCRV|  7|
+|  Fremont|  HondaCivic| 10|
+| San Jose|        null| 13|
+| San Jose| HondaAccord|  8|
+| San Jose|  HondaCivic|  5|
++---------+------------+---+
 
 -- Group by processing with `ROLLUP` clause.
 -- Equivalent GROUP BY GROUPING SETS ((city, car_model), (city), ())
 SELECT city, car_model, sum(quantity) AS sum FROM dealer
     GROUP BY city, car_model WITH ROLLUP
     ORDER BY city, car_model;
-+--------+------------+---+
-|    city|   car_model|sum|
-+--------+------------+---+
-|    null|        null| 78|
-|  Dublin|        null| 33|
-|  Dublin| HondaAccord| 10|
-|  Dublin|    HondaCRV|  3|
-|  Dublin|  HondaCivic| 20|
-| Fremont|        null| 32|
-| Fremont| HondaAccord| 15|
-| Fremont|    HondaCRV|  7|
-| Fremont|  HondaCivic| 10|
-| SanJose|        null| 13|
-| SanJose| HondaAccord|  8|
-| SanJose|  HondaCivic|  5|
-+--------+------------+---+
++---------+------------+---+
+|     city|   car_model|sum|
++---------+------------+---+
+|     null|        null| 78|
+|   Dublin|        null| 33|
+|   Dublin| HondaAccord| 10|
+|   Dublin|    HondaCRV|  3|
+|   Dublin|  HondaCivic| 20|
+|  Fremont|        null| 32|
+|  Fremont| HondaAccord| 15|
+|  Fremont|    HondaCRV|  7|
+|  Fremont|  HondaCivic| 10|
+| San Jose|        null| 13|
+| San Jose| HondaAccord|  8|
+| San Jose|  HondaCivic|  5|
++---------+------------+---+
 
 -- Group by processing with `CUBE` clause.
 -- Equivalent GROUP BY GROUPING SETS ((city, car_model), (city), (car_model), ())
 SELECT city, car_model, sum(quantity) AS sum FROM dealer
     GROUP BY city, car_model WITH CUBE
     ORDER BY city, car_model;
-+--------+------------+---+
-|    city|   car_model|sum|
-+--------+------------+---+
-|    null|        null| 78|
-|    null| HondaAccord| 33|
-|    null|    HondaCRV| 10|
-|    null|  HondaCivic| 35|
-|  Dublin|        null| 33|
-|  Dublin| HondaAccord| 10|
-|  Dublin|    HondaCRV|  3|
-|  Dublin|  HondaCivic| 20|
-| Fremont|        null| 32|
-| Fremont| HondaAccord| 15|
-| Fremont|    HondaCRV|  7|
-| Fremont|  HondaCivic| 10|
-| SanJose|        null| 13|
-| SanJose| HondaAccord|  8|
-| SanJose|  HondaCivic|  5|
-+--------+------------+---+
-{% endhighlight %}
++---------+------------+---+
+|     city|   car_model|sum|
++---------+------------+---+
+|     null|        null| 78|
+|     null| HondaAccord| 33|
+|     null|    HondaCRV| 10|
+|     null|  HondaCivic| 35|
+|   Dublin|        null| 33|
+|   Dublin| HondaAccord| 10|
+|   Dublin|    HondaCRV|  3|
+|   Dublin|  HondaCivic| 20|
+|  Fremont|        null| 32|
+|  Fremont| HondaAccord| 15|
+|  Fremont|    HondaCRV|  7|
+|  Fremont|  HondaCivic| 10|
+| San Jose|        null| 13|
+| San Jose| HondaAccord|  8|
+| San Jose|  HondaCivic|  5|
++---------+------------+---+
+```
 
 ### Related Statements
 
- * [SELECT Main](sql-ref-syntax-qry-select.html)
- * [WHERE Clause](sql-ref-syntax-qry-select-where.html)
- * [HAVING Clause](sql-ref-syntax-qry-select-having.html)
- * [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
- * [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
- * [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
- * [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
- * [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
+* [SELECT Main](sql-ref-syntax-qry-select.html)
+* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
+* [HAVING Clause](sql-ref-syntax-qry-select-having.html)
+* [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
+* [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
+* [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
+* [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
+* [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
diff --git a/docs/sql-ref-syntax-qry-select-having.md b/docs/sql-ref-syntax-qry-select-having.md
index c8c4f2c38104c..935782c551e1f 100644
--- a/docs/sql-ref-syntax-qry-select-having.md
+++ b/docs/sql-ref-syntax-qry-select-having.md
@@ -21,39 +21,35 @@ license: |
 
 ### Description
 
-The <code>HAVING</code> clause is used to filter the results produced by
-<code>GROUP BY</code> based on the specified condition. It is often used
+The `HAVING` clause is used to filter the results produced by
+`GROUP BY` based on the specified condition. It is often used
 in conjunction with a [GROUP BY](sql-ref-syntax-qry-select-groupby.html)
 clause.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 HAVING boolean_expression
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>boolean_expression</em></code></dt>
-  <dd>
-    Specifies any expression that evaluates to a result type <code>boolean</code>. Two or
+* **boolean_expression**
+
+    Specifies any expression that evaluates to a result type `boolean`. Two or
     more expressions may be combined together using the logical
-    operators ( <code>AND</code>, <code>OR</code> ).<br><br>
-
-    <b>Note</b><br>
-    The expressions specified in the <code>HAVING</code> clause can only refer to:
-     <ol>
-      <li>Constants</li>
-      <li>Expressions that appear in GROUP BY</li>
-      <li>Aggregate functions</li>
-    </ol>
-  </dd>
-</dl>
+    operators ( `AND`, `OR` ).
+
+    **Note**
+
+    The expressions specified in the `HAVING` clause can only refer to:
+    1. Constants
+    2. Expressions that appear in GROUP BY
+    3. Aggregate functions
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE dealer (id INT, city STRING, car_model STRING, quantity INT);
 INSERT INTO dealer VALUES
     (100, 'Fremont', 'Honda Civic', 10),
@@ -117,15 +113,15 @@ SELECT sum(quantity) AS sum FROM dealer HAVING sum(quantity) > 10;
 +---+
 | 78|
 +---+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SELECT Main](sql-ref-syntax-qry-select.html)
- * [WHERE Clause](sql-ref-syntax-qry-select-where.html)
- * [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
- * [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
- * [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
- * [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
- * [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
- * [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
+* [SELECT Main](sql-ref-syntax-qry-select.html)
+* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
+* [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
+* [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
+* [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
+* [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
+* [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
+* [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
diff --git a/docs/sql-ref-syntax-qry-select-hints.md b/docs/sql-ref-syntax-qry-select-hints.md
index 16f4f95f90ea1..4bb48b08d5e3b 100644
--- a/docs/sql-ref-syntax-qry-select-hints.md
+++ b/docs/sql-ref-syntax-qry-select-hints.md
@@ -23,39 +23,33 @@ license: |
 
 Join Hints allow users to suggest the join strategy that Spark should use. Prior to Spark 3.0, only the `BROADCAST` Join Hint was supported. `MERGE`, `SHUFFLE_HASH` and `SHUFFLE_REPLICATE_NL` Joint Hints support was added in 3.0. When different join strategy hints are specified on both sides of a join, Spark prioritizes hints in the following order: `BROADCAST` over `MERGE` over `SHUFFLE_HASH` over `SHUFFLE_REPLICATE_NL`. When both sides are specified with the `BROADCAST` hint or the `SHUFFLE_HASH` hint, Spark will pick the build side based on the join type and the sizes of the relations. Since a given strategy may not support all join types, Spark is not guaranteed to use the join strategy suggested by the hint.
 
+### Syntax
+
+```sql
+/*+ join_hint [ , ... ] */
+```
+
 ### Join Hints Types
 
-<dl>
-  <dt><code><em>BROADCAST</em></code></dt>
-  <dd>
-    Suggests that Spark use broadcast join. The join side with the hint will be broadcast regardless of <code>autoBroadcastJoinThreshold</code>. If both sides of the join have the broadcast hints, the one with the smaller size (based on stats) will be broadcast. The aliases for <code>BROADCAST</code> are <code>BROADCASTJOIN</code> and <code>MAPJOIN</code>.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>MERGE</em></code></dt>
-  <dd>
-     Suggests that Spark use shuffle sort merge join. The aliases for <code>MERGE</code> are <code>SHUFFLE_MERGE</code> and <code>MERGEJOIN</code>.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>SHUFFLE_HASH</em></code></dt>
-  <dd>
-     Suggests that Spark use shuffle hash join. If both sides have the shuffle hash hints, Spark chooses the smaller side (based on stats) as the build side.
-  </dd>
-</dl>
-
-<dl>
-  <dt><code><em>SHUFFLE_REPLICATE_NL</em></code></dt>
-  <dd>
+* **BROADCAST**
+
+    Suggests that Spark use broadcast join. The join side with the hint will be broadcast regardless of `autoBroadcastJoinThreshold`. If both sides of the join have the broadcast hints, the one with the smaller size (based on stats) will be broadcast. The aliases for `BROADCAST` are `BROADCASTJOIN` and `MAPJOIN`.
+
+* **MERGE**
+
+    Suggests that Spark use shuffle sort merge join. The aliases for `MERGE` are `SHUFFLE_MERGE` and `MERGEJOIN`.
+
+* **SHUFFLE_HASH**
+
+    Suggests that Spark use shuffle hash join. If both sides have the shuffle hash hints, Spark chooses the smaller side (based on stats) as the build side.
+
+* **SHUFFLE_REPLICATE_NL**
+
     Suggests that Spark use shuffle-and-replicate nested loop join.
-  </dd>
-</dl>
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Join Hints for broadcast join
 SELECT /*+ BROADCAST(t1) */ * FROM t1 INNER JOIN t2 ON t1.key = t2.key;
 SELECT /*+ BROADCASTJOIN (t1) */ * FROM t1 left JOIN t2 ON t1.key = t2.key;
@@ -78,10 +72,10 @@ SELECT /*+ SHUFFLE_REPLICATE_NL(t1) */ * FROM t1 INNER JOIN t2 ON t1.key = t2.ke
 -- Spark will issue Warning in the following example
 -- org.apache.spark.sql.catalyst.analysis.HintErrorLogger: Hint (strategy=merge)
 -- is overridden by another hint and will not take effect.
-SELECT /*+ BROADCAST(t1) */ /*+ MERGE(t1, t2) */ * FROM t1 INNER JOIN t2 ON t1.key = t2.key;
-{% endhighlight %}
+SELECT /*+ BROADCAST(t1), MERGE(t1, t2) */ * FROM t1 INNER JOIN t2 ON t1.key = t2.key;
+```
 
 ### Related Statements
 
- * [JOIN](sql-ref-syntax-qry-select-join.html)
- * [SELECT](sql-ref-syntax-qry-select.html)
+* [JOIN](sql-ref-syntax-qry-select-join.html)
+* [SELECT](sql-ref-syntax-qry-select.html)
diff --git a/docs/sql-ref-syntax-qry-select-inline-table.md b/docs/sql-ref-syntax-qry-select-inline-table.md
index 9c33cbc679f06..38ecc3da5e14e 100644
--- a/docs/sql-ref-syntax-qry-select-inline-table.md
+++ b/docs/sql-ref-syntax-qry-select-inline-table.md
@@ -25,32 +25,24 @@ An inline table is a temporary table created using a VALUES clause.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 VALUES ( expression [ , ... ] ) [ table_alias ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>expression</em></code></dt>
-  <dd>
+* **expression**
+
     Specifies a combination of one or more values, operators and SQL functions that results in a value.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>table_alias</em></code></dt>
-  <dd>
+
+* **table_alias**
+
     Specifies a temporary name with an optional column name list. <br><br>
-    <b>Syntax:</b>
-      <code>
-        [ AS ] table_name [ ( column_name [ , ... ] ) ]
-      </code>
-  </dd>
-</dl>
+    **Syntax:** `[ AS ] table_name [ ( column_name [ , ... ] ) ]`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- single row, without a table alias
 SELECT * FROM VALUES ("one", 1);
 +----+----+
@@ -77,8 +69,8 @@ SELECT * FROM VALUES ("one", array(0, 1)), ("two", array(2, 3)) AS data(a, b);
 |one|[0, 1]|
 |two|[2, 3]|
 +---+------+
-{% endhighlight %}
+```
 
-### Related Statement
+### Related Statements
 
- * [SELECT](sql-ref-syntax-qry-select.html)
+* [SELECT](sql-ref-syntax-qry-select.html)
diff --git a/docs/sql-ref-syntax-qry-select-join.md b/docs/sql-ref-syntax-qry-select-join.md
index 0b1bb1eb8fd61..28b21f5e3f0ff 100644
--- a/docs/sql-ref-syntax-qry-select-join.md
+++ b/docs/sql-ref-syntax-qry-select-join.md
@@ -25,118 +25,95 @@ A SQL join is used to combine rows from two relations based on join criteria. Th
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 relation { [ join_type ] JOIN relation [ join_criteria ] | NATURAL join_type JOIN relation }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>relation</em></code></dt>
-  <dd>
+* **relation**
+
     Specifies the relation to be joined.
-  </dd>
-  <dt><code><em>join_type</em></code></dt>
-  <dd>
-    Specifies the join type.<br><br>
-    <b>Syntax:</b><br>
-      <code>
-        [ INNER ]
-        | CROSS
-        | LEFT [ OUTER ]
-        | [ LEFT ] SEMI
-        | RIGHT [ OUTER ]
-        | FULL [ OUTER ]
-        | [ LEFT ] ANTI
-      </code>
-  </dd>
-  <dt><code><em>join_criteria</em></code></dt>
-  <dd>
-    Specifies how the rows from one relation will be combined with the rows of another relation.<br><br>
-    <b>Syntax:</b>
-      <code>
-        ON boolean_expression | USING ( column_name [ , column_name ... ] )
-      </code> <br><br>
-      <code>boolean_expression</code><br>
-      Specifies an expression with a return type of boolean.
-  </dd>
-</dl>
+
+* **join_type**
+
+    Specifies the join type.
+
+    **Syntax:**
+
+    `[ INNER ] | CROSS | LEFT [ OUTER ] | [ LEFT ] SEMI | RIGHT [ OUTER ] | FULL [ OUTER ] | [ LEFT ] ANTI`
+
+* **join_criteria**
+
+    Specifies how the rows from one relation will be combined with the rows of another relation.
+
+    **Syntax:** `ON boolean_expression | USING ( column_name [ , ... ] )`
+
+    `boolean_expression`
+
+    Specifies an expression with a return type of boolean.
 
 ### Join Types
 
-#### <b>Inner Join</b>
-
-<dd>
-The inner join is the default join in Spark SQL. It selects rows that have matching values in both relations.<br><br>
-  <b>Syntax:</b><br>
-    <code>
-    relation [ INNER ] JOIN relation [ join_criteria ]
-    </code>
-</dd>
-
-#### <b>Left Join </b>
-
-<dd>
-A left join returns all values from the left relation and the matched values from the right relation, or appends NULL if there is no match. It is also referred to as a left outer join.<br><br>
-  <b>Syntax:</b><br>
-    <code>
-    relation LEFT [ OUTER ] JOIN relation [ join_criteria ]
-    </code>
-</dd>
-
-#### <b>Right Join </b>
-
-<dd>
-A right join returns all values from the right relation and the matched values from the left relation, or appends NULL if there is no match. It is also referred to as a right outer join.<br><br>
-  <b>Syntax:</b><br>
-    <code>
-    relation RIGHT [ OUTER ] JOIN relation [ join_criteria ]
-    </code>
-</dd>
-
-#### <b>Full Join </b>
-
-<dd>
-A full join returns all values from both relations, appending NULL values on the side that does not have a match. It is also referred to as a full outer join.<br><br>
-  <b>Syntax:</b><br>
-    <code>
-    relation FULL [ OUTER ] JOIN relation [ join_criteria ]
-    </code>
-</dd>
-
-#### <b>Cross Join </b>
-
-<dd>
-A cross join returns the Cartesian product of two relations.<br><br>
-  <b>Syntax:</b><br>
-    <code>
-    relation CROSS JOIN relation [ join_criteria ]
-    </code>
-</dd>
-
-#### <b>Semi Join </b>
-
-<dd>
-A semi join returns values from the left side of the relation that has a match with the right. It is also referred to as a left semi join.<br><br>
-  <b>Syntax:</b><br>
-    <code>
-    relation [ LEFT ] SEMI JOIN relation [ join_criteria ]
-    </code>
-</dd>
-
-#### <b>Anti Join </b>
-
-<dd>
-An anti join returns values from the left relation that has no match with the right. It is also referred to as a left anti join.<br><br>
-  <b>Syntax:</b><br>
-    <code>
-    relation [ LEFT ] ANTI JOIN relation [ join_criteria ]
-    </code>
-</dd>
+#### **Inner Join**
+
+The inner join is the default join in Spark SQL. It selects rows that have matching values in both relations.
+
+**Syntax:**
+
+`relation [ INNER ] JOIN relation [ join_criteria ]`
+
+#### **Left Join**
+
+A left join returns all values from the left relation and the matched values from the right relation, or appends NULL if there is no match. It is also referred to as a left outer join.
+
+**Syntax:**
+
+`relation LEFT [ OUTER ] JOIN relation [ join_criteria ]`
+
+#### **Right Join**
+
+A right join returns all values from the right relation and the matched values from the left relation, or appends NULL if there is no match. It is also referred to as a right outer join.
+
+**Syntax:**
+
+`relation RIGHT [ OUTER ] JOIN relation [ join_criteria ]`
+
+#### **Full Join**
+
+A full join returns all values from both relations, appending NULL values on the side that does not have a match. It is also referred to as a full outer join.
+
+**Syntax:**
+
+`relation FULL [ OUTER ] JOIN relation [ join_criteria ]`
+
+#### **Cross Join**
+
+A cross join returns the Cartesian product of two relations.
+
+**Syntax:**
+
+`relation CROSS JOIN relation [ join_criteria ]`
+
+#### **Semi Join**
+
+A semi join returns values from the left side of the relation that has a match with the right. It is also referred to as a left semi join.
+
+**Syntax:**
+
+`relation [ LEFT ] SEMI JOIN relation [ join_criteria ]`
+
+#### **Anti Join**
+
+An anti join returns values from the left relation that has no match with the right. It is also referred to as a left anti join.
+
+**Syntax:**
+
+`relation [ LEFT ] ANTI JOIN relation [ join_criteria ]`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Use employee and department tables to demonstrate different type of joins.
 SELECT * FROM employee;
 +---+-----+------+
@@ -253,9 +230,9 @@ SELECT * FROM employee ANTI JOIN department ON employee.deptno = department.dept
 |104| Evan|     4|
 |106|  Amy|     6|
 +---+-----+------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
-  * [SELECT](sql-ref-syntax-qry-select.html)
-  * [Join Hints](sql-ref-syntax-qry-select-hints.html)
+* [SELECT](sql-ref-syntax-qry-select.html)
+* [Join Hints](sql-ref-syntax-qry-select-hints.html)
diff --git a/docs/sql-ref-syntax-qry-select-like.md b/docs/sql-ref-syntax-qry-select-like.md
index 408673c532ddd..feb5eb7b3c80d 100644
--- a/docs/sql-ref-syntax-qry-select-like.md
+++ b/docs/sql-ref-syntax-qry-select-like.md
@@ -25,38 +25,30 @@ A LIKE predicate is used to search for a specific pattern.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 [ NOT ] { LIKE search_pattern [ ESCAPE esc_char ] | RLIKE regex_pattern }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>search_pattern</em></code></dt>
-  <dd>
-    Specifies a string pattern to be searched by the <code>LIKE</code> clause. It can contain special pattern-matching characters:
-    <ul>
-      <li><code>%</code></li> matches zero or more characters.
-      <li><code>_</code></li> matches exactly one character.
-    </ul>
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>esc_char</em></code></dt>
-  <dd>
-    Specifies the escape character. The default escape character is <code>\</code>.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>regex_pattern</em></code></dt>
-  <dd>
-    Specifies a regular expression search pattern to be searched by the <code>RLIKE</code> clause.
-  </dd>
-</dl>
+* **search_pattern**
+
+    Specifies a string pattern to be searched by the `LIKE` clause. It can contain special pattern-matching characters:
+
+    * `%` matches zero or more characters.
+    * `_` matches exactly one character.
+
+* **esc_char**
+
+    Specifies the escape character. The default escape character is `\`.
+
+* **regex_pattern**
+
+    Specifies a regular expression search pattern to be searched by the `RLIKE` clause.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE person (id INT, name STRING, age INT);
 INSERT INTO person VALUES
     (100, 'John', 30),
@@ -90,12 +82,11 @@ SELECT * FROM person WHERE name NOT LIKE 'M_ry';
 |400|   Dan| 50|
 +---+------+---+
 
-SELECT * FROM person WHERE name RLIKE '[MD]';
+SELECT * FROM person WHERE name RLIKE 'M+';
 +---+----+----+
 | id|name| age|
 +---+----+----+
 |300|Mike|  80|
-|400| Dan|  50|
 |200|Mary|null|
 +---+----+----+
 
@@ -112,9 +103,9 @@ SELECT * FROM person WHERE name LIKE '%$_%' ESCAPE '$';
 +---+------+---+
 |500|Evan_W| 16|
 +---+------+---+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SELECT](sql-ref-syntax-qry-select.html)
- * [WHERE Clause](sql-ref-syntax-qry-select-where.html)
+* [SELECT](sql-ref-syntax-qry-select.html)
+* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
diff --git a/docs/sql-ref-syntax-qry-select-limit.md b/docs/sql-ref-syntax-qry-select-limit.md
index eaeaed068102f..ec3532214084b 100644
--- a/docs/sql-ref-syntax-qry-select-limit.md
+++ b/docs/sql-ref-syntax-qry-select-limit.md
@@ -21,34 +21,31 @@ license: |
 
 ### Description
 
-The <code>LIMIT</code> clause is used to constrain the number of rows returned by
+The `LIMIT` clause is used to constrain the number of rows returned by
 the [SELECT](sql-ref-syntax-qry-select.html) statement. In general, this clause
 is used in conjunction with [ORDER BY](sql-ref-syntax-qry-select-orderby.html) to
 ensure that the results are deterministic.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 LIMIT { ALL | integer_expression }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>ALL</em></code></dt>
-  <dd>
+* **ALL**
+
     If specified, the query returns all the rows. In other words, no limit is applied if this
     option is specified.
-  </dd>
-  <dt><code><em>integer_expression</em></code></dt>
-  <dd>
+
+* **integer_expression**
+
     Specifies a foldable expression that returns an integer.
-  </dd>
-</dl>
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE person (name STRING, age INT);
 INSERT INTO person VALUES
     ('Zen Hui', 25),
@@ -95,15 +92,15 @@ SELECT name, age FROM person ORDER BY name LIMIT length('SPARK');
 -- A non-foldable expression as an input to LIMIT is not allowed.
 SELECT name, age FROM person ORDER BY name LIMIT length(name);
   org.apache.spark.sql.AnalysisException: The limit expression must evaluate to a constant value ...
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SELECT Main](sql-ref-syntax-qry-select.html)
- * [WHERE Clause](sql-ref-syntax-qry-select-where.html)
- * [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
- * [HAVING Clause](sql-ref-syntax-qry-select-having.html)
- * [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
- * [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
- * [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
- * [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
+* [SELECT Main](sql-ref-syntax-qry-select.html)
+* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
+* [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
+* [HAVING Clause](sql-ref-syntax-qry-select-having.html)
+* [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
+* [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
+* [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
+* [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
diff --git a/docs/sql-ref-syntax-qry-select-orderby.md b/docs/sql-ref-syntax-qry-select-orderby.md
index d927177398f7f..85bbe514cdc95 100644
--- a/docs/sql-ref-syntax-qry-select-orderby.md
+++ b/docs/sql-ref-syntax-qry-select-orderby.md
@@ -21,56 +21,48 @@ license: |
 
 ### Description
 
-The <code>ORDER BY</code> clause is used to return the result rows in a sorted manner
+The `ORDER BY` clause is used to return the result rows in a sorted manner
 in the user specified order. Unlike the [SORT BY](sql-ref-syntax-qry-select-sortby.html)
 clause, this clause guarantees a total order in the output.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 ORDER BY { expression [ sort_direction | nulls_sort_oder ] [ , ... ] }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>ORDER BY</em></code></dt>
-  <dd>
-    Specifies a comma-separated list of expressions along with optional parameters <code>sort_direction</code>
-    and <code>nulls_sort_order</code> which are used to sort the rows.
-  </dd>
-  <dt><code><em>sort_direction</em></code></dt>
-  <dd>
+* **ORDER BY**
+
+    Specifies a comma-separated list of expressions along with optional parameters `sort_direction`
+    and `nulls_sort_order` which are used to sort the rows.
+
+* **sort_direction**
+
     Optionally specifies whether to sort the rows in ascending or descending
-    order. The valid values for the sort direction are <code>ASC</code> for ascending
-    and <code>DESC</code> for descending. If sort direction is not explicitly specified, then by default
-    rows are sorted ascending. <br><br>
-    <b>Syntax:</b>
-    <code>
-       [ ASC | DESC ]
-    </code>
-  </dd>
-  <dt><code><em>nulls_sort_order</em></code></dt>
-  <dd>
+    order. The valid values for the sort direction are `ASC` for ascending
+    and `DESC` for descending. If sort direction is not explicitly specified, then by default
+    rows are sorted ascending.
+
+    **Syntax:** [ ASC `|` DESC ]
+
+* **nulls_sort_order**
+
     Optionally specifies whether NULL values are returned before/after non-NULL values. If
-    <code>null_sort_order</code> is not specified, then NULLs sort first if sort order is
-    <code>ASC</code> and NULLS sort last if sort order is <code>DESC</code>.<br><br>
-    <ol>
-      <li> If <code>NULLS FIRST</code> is specified, then NULL values are returned first
-           regardless of the sort order.</li>
-      <li>If <code>NULLS LAST</code> is specified, then NULL values are returned last regardless of
-           the sort order. </li>
-    </ol><br>
-    <b>Syntax:</b>
-    <code>
-       [ NULLS { FIRST | LAST } ]
-    </code>
-  </dd>
-</dl>
+    `null_sort_order` is not specified, then NULLs sort first if sort order is
+    `ASC` and NULLS sort last if sort order is `DESC`.
+
+    1. If `NULLS FIRST` is specified, then NULL values are returned first
+       regardless of the sort order.
+    2. If `NULLS LAST` is specified, then NULL values are returned last regardless of
+       the sort order.
+
+    **Syntax:** `[ NULLS { FIRST | LAST } ]`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE person (id INT, name STRING, age INT);
 INSERT INTO person VALUES
     (100, 'John', 30),
@@ -139,15 +131,15 @@ SELECT * FROM person ORDER BY name ASC, age DESC;
 |200| Mary|null|
 |300| Mike|  80|
 +---+-----+----+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SELECT Main](sql-ref-syntax-qry-select.html)
- * [WHERE Clause](sql-ref-syntax-qry-select-where.html)
- * [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
- * [HAVING Clause](sql-ref-syntax-qry-select-having.html)
- * [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
- * [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
- * [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
- * [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
+* [SELECT Main](sql-ref-syntax-qry-select.html)
+* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
+* [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
+* [HAVING Clause](sql-ref-syntax-qry-select-having.html)
+* [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
+* [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
+* [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
+* [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
diff --git a/docs/sql-ref-syntax-qry-select-setops.md b/docs/sql-ref-syntax-qry-select-setops.md
index 98c20941d16bf..8cd12c37fa603 100644
--- a/docs/sql-ref-syntax-qry-select-setops.md
+++ b/docs/sql-ref-syntax-qry-select-setops.md
@@ -35,13 +35,13 @@ Note that input relations must have the same number of columns and compatible da
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 [ ( ] relation [ ) ] EXCEPT | MINUS [ ALL | DISTINCT ] [ ( ] relation [ ) ]
-{% endhighlight %}
+```
 
 #### Examples
 
-{% highlight sql %}
+```sql
 -- Use number1 and number2 tables to demonstrate set operators in this page.
 SELECT * FROM number1;
 +---+
@@ -98,7 +98,7 @@ SELECT c FROM number1 MINUS ALL (SELECT c FROM number2);
 |  3|
 |  4|
 +---+
-{% endhighlight %}
+```
 
 ### INTERSECT
 
@@ -106,13 +106,13 @@ SELECT c FROM number1 MINUS ALL (SELECT c FROM number2);
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 [ ( ] relation [ ) ] INTERSECT [ ALL | DISTINCT ] [ ( ] relation [ ) ]
-{% endhighlight %}
+```
 
 #### Examples
 
-{% highlight sql %}
+```sql
 (SELECT c FROM number1) INTERSECT (SELECT c FROM number2);
 +---+
 |  c|
@@ -137,7 +137,7 @@ SELECT c FROM number1 MINUS ALL (SELECT c FROM number2);
 |  2|
 |  2|
 +---+
-{% endhighlight %}
+```
 
 ### UNION
 
@@ -145,13 +145,13 @@ SELECT c FROM number1 MINUS ALL (SELECT c FROM number2);
 
 #### Syntax
 
-{% highlight sql %}
+```sql
 [ ( ] relation [ ) ] UNION [ ALL | DISTINCT ] [ ( ] relation [ ) ]
-{% endhighlight %}
+```
 
 ### Examples
 
-{% highlight sql %}
+```sql
 (SELECT c FROM number1) UNION (SELECT c FROM number2);
 +---+
 |  c|
@@ -189,8 +189,8 @@ SELECT c FROM number1 UNION ALL (SELECT c FROM number2);
 |  2|
 |  2|
 +---+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SELECT Statement](sql-ref-syntax-qry-select.html)
+* [SELECT Statement](sql-ref-syntax-qry-select.html)
diff --git a/docs/sql-ref-syntax-qry-select-sortby.md b/docs/sql-ref-syntax-qry-select-sortby.md
index 1dfa10429709e..554bdb569d005 100644
--- a/docs/sql-ref-syntax-qry-select-sortby.md
+++ b/docs/sql-ref-syntax-qry-select-sortby.md
@@ -21,58 +21,50 @@ license: |
 
 ### Description
 
-The <code>SORT BY</code> clause is used to return the result rows sorted
+The `SORT BY` clause is used to return the result rows sorted
 within each partition in the user specified order. When there is more than one partition
-<code>SORT BY</code> may return result that is partially ordered. This is different
+`SORT BY` may return result that is partially ordered. This is different
 than [ORDER BY](sql-ref-syntax-qry-select-orderby.html) clause which guarantees a
 total order of the output.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 SORT BY { expression [ sort_direction | nulls_sort_order ] [ , ... ] }
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>SORT BY</em></code></dt>
-  <dd>
-    Specifies a comma-separated list of expressions along with optional parameters <code>sort_direction</code>
-    and <code>nulls_sort_order</code> which are used to sort the rows within each partition.
-  </dd>
-  <dt><code><em>sort_direction</em></code></dt>
-  <dd>
+* **SORT BY**
+
+    Specifies a comma-separated list of expressions along with optional parameters `sort_direction`
+    and `nulls_sort_order` which are used to sort the rows within each partition.
+
+* **sort_direction**
+
     Optionally specifies whether to sort the rows in ascending or descending
-    order. The valid values for the sort direction are <code>ASC</code> for ascending
-    and <code>DESC</code> for descending. If sort direction is not explicitly specified, then by default
-    rows are sorted ascending. <br><br>
-    <b>Syntax:</b>
-    <code>
-       [ ASC | DESC ]
-    </code>
-  </dd>
-  <dt><code><em>nulls_sort_order</em></code></dt>
-  <dd>
+    order. The valid values for the sort direction are `ASC` for ascending
+    and `DESC` for descending. If sort direction is not explicitly specified, then by default
+    rows are sorted ascending.
+
+    **Syntax:** `[ ASC | DESC ]`
+
+* **nulls_sort_order**
+
     Optionally specifies whether NULL values are returned before/after non-NULL values. If
-    <code>null_sort_order</code> is not specified, then NULLs sort first if sort order is
-    <code>ASC</code> and NULLS sort last if sort order is <code>DESC</code>.<br><br>
-    <ol>
-      <li> If <code>NULLS FIRST</code> is specified, then NULL values are returned first
-           regardless of the sort order.</li>
-      <li>If <code>NULLS LAST</code> is specified, then NULL values are returned last regardless of
-           the sort order. </li>
-    </ol><br>
-    <b>Syntax:</b>
-    <code>
-       [ NULLS { FIRST | LAST } ]
-    </code>
-  </dd>
-</dl>
+    `null_sort_order` is not specified, then NULLs sort first if sort order is
+    `ASC` and NULLS sort last if sort order is `DESC`.
+
+    1. If `NULLS FIRST` is specified, then NULL values are returned first
+       regardless of the sort order.
+    2. If `NULLS LAST` is specified, then NULL values are returned last regardless of
+       the sort order.
+
+    **Syntax:** `[ NULLS { FIRST | LAST } ]`
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE person (zip_code INT, name STRING, age INT);
 INSERT INTO person VALUES
     (94588, 'Zen Hui', 50),
@@ -172,15 +164,15 @@ SELECT /*+ REPARTITION(zip_code) */ name, age, zip_code FROM person
 | David K|  42|   94511|
 |Lalit B.|null|   94511|
 +--------+----+--------+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SELECT Main](sql-ref-syntax-qry-select.html)
- * [WHERE Clause](sql-ref-syntax-qry-select-where.html)
- * [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
- * [HAVING Clause](sql-ref-syntax-qry-select-having.html)
- * [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
- * [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
- * [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
- * [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
+* [SELECT Main](sql-ref-syntax-qry-select.html)
+* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
+* [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
+* [HAVING Clause](sql-ref-syntax-qry-select-having.html)
+* [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
+* [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
+* [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
+* [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
diff --git a/docs/sql-ref-syntax-qry-select-tvf.md b/docs/sql-ref-syntax-qry-select-tvf.md
index ac8fecaae6413..89ad01aff2167 100644
--- a/docs/sql-ref-syntax-qry-select-tvf.md
+++ b/docs/sql-ref-syntax-qry-select-tvf.md
@@ -25,28 +25,21 @@ A table-valued function (TVF) is a function that returns a relation or a set of
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 function_name ( expression [ , ... ] ) [ table_alias ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>expression</em></code></dt>
-  <dd>
+* **expression**
+
     Specifies a combination of one or more values, operators and SQL functions that results in a value.
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>table_alias</em></code></dt>
-  <dd>
-    Specifies a temporary name with an optional column name list. <br><br>
-    <b>Syntax:</b>
-      <code>
-        [ AS ] table_name [ ( column_name [ , ... ] ) ]
-      </code>
-  </dd>
-</dl>
+
+* **table_alias**
+
+    Specifies a temporary name with an optional column name list.
+
+    **Syntax:** `[ AS ] table_name [ ( column_name [ , ... ] ) ]`
 
 ### Supported Table-valued Functions
 
@@ -78,7 +71,7 @@ function_name ( expression [ , ... ] ) [ table_alias ]
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- range call with end
 SELECT * FROM range(6 + cos(3));
 +---+
@@ -124,8 +117,8 @@ SELECT * FROM range(5, 8) AS test;
 |  6|
 |  7|
 +---+
-{% endhighlight %}
+```
 
-### Related Statement
+### Related Statements
 
- * [SELECT](sql-ref-syntax-qry-select.html)
+* [SELECT](sql-ref-syntax-qry-select.html)
diff --git a/docs/sql-ref-syntax-qry-select-usedb.md b/docs/sql-ref-syntax-qry-select-usedb.md
index bb95a8e4ddf30..4119a4927bc9f 100644
--- a/docs/sql-ref-syntax-qry-select-usedb.md
+++ b/docs/sql-ref-syntax-qry-select-usedb.md
@@ -28,32 +28,29 @@ The default database name is 'default'.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 USE database_name
-{% endhighlight %}
+```
 
 ### Parameter
 
-<dl>
-  <dt><code><em>database_name</em></code></dt>
-  <dd>
-     Name of the database will be used. If the database does not exist, an exception will be thrown.
-  </dd>
-</dl>
+* **database_name**
+
+    Name of the database will be used. If the database does not exist, an exception will be thrown.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 -- Use the 'userdb' which exists.
 USE userdb;
 
 -- Use the 'userdb1' which doesn't exist
 USE userdb1;
   Error: org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException: Database 'userdb1' not found;(state=,code=0)
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
- * [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
- * [CREATE TABLE ](sql-ref-syntax-ddl-create-table.html)
+* [CREATE DATABASE](sql-ref-syntax-ddl-create-database.html)
+* [DROP DATABASE](sql-ref-syntax-ddl-drop-database.html)
+* [CREATE TABLE ](sql-ref-syntax-ddl-create-table.html)
diff --git a/docs/sql-ref-syntax-qry-select-where.md b/docs/sql-ref-syntax-qry-select-where.md
index 360313fcfff1c..ca3f5ec7866c6 100644
--- a/docs/sql-ref-syntax-qry-select-where.md
+++ b/docs/sql-ref-syntax-qry-select-where.md
@@ -21,29 +21,26 @@ license: |
 
 ### Description
 
-The <code>WHERE</code> clause is used to limit the results of the <code>FROM</code>
+The `WHERE` clause is used to limit the results of the `FROM`
 clause of a query or a subquery based on the specified condition.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 WHERE boolean_expression
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>boolean_expression</em></code></dt>
-  <dd>
-    Specifies any expression that evaluates to a result type <code>boolean</code>. Two or
+* **boolean_expression**
+
+    Specifies any expression that evaluates to a result type `boolean`. Two or
     more expressions may be combined together using the logical
-    operators ( <code>AND</code>, <code>OR</code> ).
-  </dd>
-</dl>
+    operators ( `AND`, `OR` ).
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE person (id INT, name STRING, age INT);
 INSERT INTO person VALUES
     (100, 'John', 30),
@@ -116,15 +113,15 @@ SELECT * FROM person AS parent
 +---+----+----+
 |200|Mary|null|
 +---+----+----+
-{% endhighlight %}
+```
 
 ### Related Statements
 
- * [SELECT Main](sql-ref-syntax-qry-select.html)
- * [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
- * [HAVING Clause](sql-ref-syntax-qry-select-having.html)
- * [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
- * [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
- * [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
- * [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
- * [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
+* [SELECT Main](sql-ref-syntax-qry-select.html)
+* [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
+* [HAVING Clause](sql-ref-syntax-qry-select-having.html)
+* [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
+* [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
+* [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
+* [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
+* [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
diff --git a/docs/sql-ref-syntax-qry-select.md b/docs/sql-ref-syntax-qry-select.md
index bc2cc0269124e..1aeecdb982c4c 100644
--- a/docs/sql-ref-syntax-qry-select.md
+++ b/docs/sql-ref-syntax-qry-select.md
@@ -28,7 +28,7 @@ of a query along with examples.
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 [ WITH with_query [ , ... ] ]
 select_statement [ { UNION | INTERSECT | EXCEPT } [ ALL | DISTINCT ] select_statement, ... ]
     [ ORDER BY { expression [ ASC | DESC ] [ NULLS { FIRST | LAST } ] [ , ...] } ]
@@ -37,126 +37,125 @@ select_statement [ { UNION | INTERSECT | EXCEPT } [ ALL | DISTINCT ] select_stat
     [ DISTRIBUTE BY { expression [, ...] } ]
     [ WINDOW { named_window [ , WINDOW named_window, ... ] } ]
     [ LIMIT { ALL | expression } ]
-{% endhighlight %}
+```
 
 While `select_statement` is defined as
-{% highlight sql %}
+```sql
 SELECT [ hints , ... ] [ ALL | DISTINCT ] { named_expression [ , ... ] }
     FROM { from_item [ , ...] }
     [ WHERE boolean_expression ]
     [ GROUP BY expression [ , ...] ]
     [ HAVING boolean_expression ]
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>with_query</em></code></dt>
-  <dd>
-    Specifies the <a href="sql-ref-syntax-qry-select-cte.html">common table expressions (CTEs)</a> before the main query block.
+* **with_query**
+
+    Specifies the [common table expressions (CTEs)](sql-ref-syntax-qry-select-cte.html) before the main query block.
     These table expressions are allowed to be referenced later in the FROM clause. This is useful to abstract
     out repeated subquery blocks in the FROM clause and improves readability of the query.
-  </dd>
-  <dt><code><em>hints</em></code></dt>
-  <dd>
+
+* **hints**
+
     Hints can be specified to help spark optimizer make better planning decisions. Currently spark supports hints
     that influence selection of join strategies and repartitioning of the data.
-  </dd>
-  <dt><code><em>ALL</em></code></dt>
-  <dd>
+
+* **ALL**
+
     Select all matching rows from the relation and is enabled by default.
-  </dd>
-  <dt><code><em>DISTINCT</em></code></dt>
-  <dd>
+
+* **DISTINCT**
+
     Select all matching rows from the relation after removing duplicates in results.
-  </dd>
-  <dt><code><em>named_expression</em></code></dt>
-  <dd>
-    An expression with an assigned name. In general, it denotes a column expression.<br><br>
-    <b>Syntax:</b>
-      <code>
-        expression [AS] [alias]
-      </code>
-  </dd>
-  <dt><code><em>from_item</em></code></dt>
-  <dd>
-    Specifies a source of input for the query. It can be one of the following:
-    <ol>
-      <li>Table relation</li>
-      <li><a href="sql-ref-syntax-qry-select-join.html">Join relation</a></li>
-      <li><a href="sql-ref-syntax-qry-select-tvf.html">Table-value function</a></li>
-      <li><a href="sql-ref-syntax-qry-select-inline-table.html">Inline table</a></li>
-      <li>Subquery</li>
-    </ol>
-  </dd>
-  <dt><code><em>WHERE</em></code></dt>
-  <dd>
-    Filters the result of the FROM clause based on the supplied predicates.
-  </dd>
-  <dt><code><em>GROUP BY</em></code></dt>
-  <dd>
-    Specifies the expressions that are used to group the rows. This is used in conjunction with aggregate functions
-    (MIN, MAX, COUNT, SUM, AVG, etc.) to group rows based on the grouping expressions and aggregate values in each group.
-    When a FILTER clause is attached to an aggregate function, only the matching rows are passed to that function.
-  </dd>
-  <dt><code><em>HAVING</em></code></dt>
-  <dd>
-    Specifies the predicates by which the rows produced by GROUP BY are filtered. The HAVING clause is used to
-    filter rows after the grouping is performed. If HAVING is specified without GROUP BY, it indicates a GROUP BY
-    without grouping expressions (global aggregate).
-  </dd>
-  <dt><code><em>ORDER BY</em></code></dt>
-  <dd>
-    Specifies an ordering of the rows of the complete result set of the query. The output rows are ordered
-    across the partitions. This parameter is mutually exclusive with <code>SORT BY</code>,
-    <code>CLUSTER BY</code> and <code>DISTRIBUTE BY</code> and can not be specified together.
-  </dd>
-  <dt><code><em>SORT BY</em></code></dt>
-  <dd>
-    Specifies an ordering by which the rows are ordered within each partition. This parameter is mutually
-    exclusive with <code>ORDER BY</code> and <code>CLUSTER BY</code> and can not be specified together.
-  </dd>
-  <dt><code><em>CLUSTER BY</em></code></dt>
-  <dd>
-    Specifies a set of expressions that is used to repartition and sort the rows. Using this clause has
-    the same effect of using <code>DISTRIBUTE BY</code> and <code>SORT BY</code> together.
-  </dd>
-  <dt><code><em>DISTRIBUTE BY</em></code></dt>
-  <dd>
-    Specifies a set of expressions by which the result rows are repartitioned. This parameter is mutually
-    exclusive with <code>ORDER BY</code> and <code>CLUSTER BY</code> and can not be specified together.
-  </dd>
-  <dt><code><em>LIMIT</em></code></dt>
-  <dd>
-    Specifies the maximum number of rows that can be returned by a statement or subquery. This clause
-    is mostly used in the conjunction with <code>ORDER BY</code> to produce a deterministic result.
-  </dd>
-  <dt><code><em>boolean_expression</em></code></dt>
-  <dd>
-    Specifies an expression with a return type of boolean.
-  </dd>
-  <dt><code><em>expression</em></code></dt>
-  <dd>
-    Specifies a combination of one or more values, operators, and SQL functions that evaluates to a value.
-  </dd>
-  <dt><code><em>named_window</em></code></dt>
-  <dd>
-    Specifies aliases for one or more source window specifications. The source window specifications can
-    be referenced in the widow definitions in the query.
-  </dd>
-</dl>
+
+* **named_expression**
+
+    An expression with an assigned name. In general, it denotes a column expression.
+
+    **Syntax:** `expression [AS] [alias]`
+
+ * **from_item**
+
+     Specifies a source of input for the query. It can be one of the following:
+     * Table relation
+     * [Join relation](sql-ref-syntax-qry-select-join.html)
+     * [Table-value function](sql-ref-syntax-qry-select-tvf.html)
+     * [Inline table](sql-ref-syntax-qry-select-inline-table.html)
+     * Subquery
+
+
+ * **WHERE**
+
+     Filters the result of the FROM clause based on the supplied predicates.
+
+ * **GROUP BY**
+
+     Specifies the expressions that are used to group the rows. This is used in conjunction with aggregate functions
+     (MIN, MAX, COUNT, SUM, AVG, etc.) to group rows based on the grouping expressions and aggregate values in each group.
+     When a FILTER clause is attached to an aggregate function, only the matching rows are passed to that function.
+
+ * **HAVING**
+
+     Specifies the predicates by which the rows produced by GROUP BY are filtered. The HAVING clause is used to
+     filter rows after the grouping is performed. If HAVING is specified without GROUP BY, it indicates a GROUP BY
+     without grouping expressions (global aggregate).
+
+ * **ORDER BY**
+
+     Specifies an ordering of the rows of the complete result set of the query. The output rows are ordered
+     across the partitions. This parameter is mutually exclusive with `SORT BY`,
+     `CLUSTER BY` and `DISTRIBUTE BY` and can not be specified together.
+
+ * **SORT BY**
+
+     Specifies an ordering by which the rows are ordered within each partition. This parameter is mutually
+     exclusive with `ORDER BY` and `CLUSTER BY` and can not be specified together.
+
+ * **CLUSTER BY**
+
+     Specifies a set of expressions that is used to repartition and sort the rows. Using this clause has
+     the same effect of using `DISTRIBUTE BY` and `SORT BY` together.
+
+ * **DISTRIBUTE BY**
+
+     Specifies a set of expressions by which the result rows are repartitioned. This parameter is mutually
+     exclusive with `ORDER BY` and `CLUSTER BY` and can not be specified together.
+
+ * **LIMIT**
+
+     Specifies the maximum number of rows that can be returned by a statement or subquery. This clause
+     is mostly used in the conjunction with `ORDER BY` to produce a deterministic result.
+
+ * **boolean_expression**
+
+     Specifies an expression with a return type of boolean.
+
+ * **expression**
+
+     Specifies a combination of one or more values, operators, and SQL functions that evaluates to a value.
+
+ * **named_window**
+
+      Specifies aliases for one or more source window specifications. The source window specifications can
+      be referenced in the widow definitions in the query.
 
 ### Related Statements
 
- * [WHERE Clause](sql-ref-syntax-qry-select-where.html)
- * [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
- * [HAVING Clause](sql-ref-syntax-qry-select-having.html)
- * [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
- * [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
- * [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
- * [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
- * [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
- * [TABLESAMPLE](sql-ref-syntax-qry-sampling.html)
- * [JOIN](sql-ref-syntax-qry-select-join.html)
- * [SET Operators](sql-ref-syntax-qry-select-setops.html)
- * [Common Table Expression](sql-ref-syntax-qry-select-cte.html)
+* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
+* [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
+* [HAVING Clause](sql-ref-syntax-qry-select-having.html)
+* [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
+* [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
+* [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
+* [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
+* [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
+* [Common Table Expression](sql-ref-syntax-qry-select-cte.html)
+* [Inline Table](sql-ref-syntax-qry-select-inline-table.html)
+* [JOIN](sql-ref-syntax-qry-select-join.html)
+* [Join Hints](sql-ref-syntax-qry-select-hints.html)
+* [LIKE Predicate](sql-ref-syntax-qry-select-like.html)
+* [Set Operators](sql-ref-syntax-qry-select-setops.html)
+* [TABLESAMPLE](sql-ref-syntax-qry-sampling.html)
+* [Table-valued Function](sql-ref-syntax-qry-select-tvf.html)
+* [Window Function](sql-ref-syntax-qry-window.html)
diff --git a/docs/sql-ref-syntax-qry-window.md b/docs/sql-ref-syntax-qry-window.md
index e3762925760e2..9c03b65fec3eb 100644
--- a/docs/sql-ref-syntax-qry-window.md
+++ b/docs/sql-ref-syntax-qry-window.md
@@ -25,67 +25,52 @@ Window functions operate on a group of rows, referred to as a window, and calcul
 
 ### Syntax
 
-{% highlight sql %}
+```sql
 window_function OVER
 ( [  { PARTITION | DISTRIBUTE } BY partition_col_name = partition_col_val ( [ , ... ] ) ]
   { ORDER | SORT } BY expression [ ASC | DESC ] [ NULLS { FIRST | LAST } ] [ , ... ]
   [ window_frame ] )
-{% endhighlight %}
+```
 
 ### Parameters
 
-<dl>
-  <dt><code><em>window_function</em></code></dt>
-  <dd>
-    <ul>
-      <li>Ranking Functions</li>
-      <br>
-      <b>Syntax:</b>
-        <code>
-          RANK | DENSE_RANK | PERCENT_RANK | NTILE | ROW_NUMBER
-        </code>
-    </ul>
-    <ul>
-      <li>Analytic Functions</li>
-      <br>
-      <b>Syntax:</b>
-        <code>
-          CUME_DIST | LAG | LEAD
-        </code>
-    </ul>
-    <ul>
-      <li>Aggregate Functions</li>
-      <br>
-      <b>Syntax:</b>
-        <code>
-          MAX | MIN | COUNT | SUM | AVG | ...
-        </code>
-        <br>
-        Please refer to the <a href="api/sql/">Built-in Functions</a> document for a complete list of Spark aggregate functions.
-    </ul>
-  </dd>
-</dl>
-<dl>
-  <dt><code><em>window_frame</em></code></dt>
-  <dd>
+* **window_function**
+
+    * Ranking Functions
+
+      **Syntax:** `RANK | DENSE_RANK | PERCENT_RANK | NTILE | ROW_NUMBER`
+
+    * Analytic Functions
+
+      **Syntax:** `CUME_DIST | LAG | LEAD`
+
+    * Aggregate Functions
+
+      **Syntax:** `MAX | MIN | COUNT | SUM | AVG | ...`
+
+      Please refer to the [Built-in Aggregation Functions](sql-ref-functions-builtin.html#aggregate-functions) document for a complete list of Spark aggregate functions.
+
+* **window_frame**
+
     Specifies which row to start the window on and where to end it.<br>
-    <b>Syntax:</b><br>
-      <code>{ RANGE | ROWS } { frame_start | BETWEEN frame_start AND frame_end }</code><br>
-      If frame_end is omitted it defaults to CURRENT ROW.<br><br>
-      <ul>
-      <code>frame_start</code> and <code>frame_end</code> have the following syntax<br>
-      <b>Syntax:</b><br>
-        <code>
-          UNBOUNDED PRECEDING | offset PRECEDING | CURRENT ROW | offset FOLLOWING | UNBOUNDED FOLLOWING
-        </code><br>
-        <code>offset:</code>specifies the <code>offset</code> from the position of the current row.
-      </ul>
-  </dd>
-</dl>
+
+    **Syntax:**
+
+    `{ RANGE | ROWS } { frame_start | BETWEEN frame_start AND frame_end }`
+
+    If frame_end is omitted it defaults to CURRENT ROW.
+
+    `frame_start` and `frame_end` have the following syntax
+
+     **Syntax:**
+
+     `UNBOUNDED PRECEDING | offset PRECEDING | CURRENT ROW | offset FOLLOWING | UNBOUNDED FOLLOWING`
+
+     `offset:` specifies the <code>offset</code> from the position of the current row.
 
 ### Examples
 
-{% highlight sql %}
+```sql
 CREATE TABLE employees (name STRING, dept STRING, salary INT, age INT);
 
 INSERT INTO employees VALUES ("Lisa", "Sales", 10000, 35);
@@ -199,8 +184,8 @@ SELECT name, salary,
 | Jane|  Marketing| 29000|29000|35000|
 | Jeff|  Marketing| 35000|29000|    0|
 +-----+-----------+------+-----+-----+
-{% endhighlight %}
+```
 
 ### Related Statements
 
-  * [SELECT](sql-ref-syntax-qry-select.html)
+* [SELECT](sql-ref-syntax-qry-select.html)
diff --git a/docs/sql-ref-syntax-qry.md b/docs/sql-ref-syntax-qry.md
index 325c9b69f12f9..1171fead55e30 100644
--- a/docs/sql-ref-syntax-qry.md
+++ b/docs/sql-ref-syntax-qry.md
@@ -27,20 +27,21 @@ to SELECT are also included in this section. Spark also provides the
 ability to generate logical and physical plan for a given query using
 [EXPLAIN](sql-ref-syntax-qry-explain.html) statement.
 
- * [WHERE Clause](sql-ref-syntax-qry-select-where.html)
- * [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
- * [HAVING Clause](sql-ref-syntax-qry-select-having.html)
- * [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
- * [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
- * [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
- * [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
- * [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
- * [JOIN](sql-ref-syntax-qry-select-join.html)
- * [Join Hints](sql-ref-syntax-qry-select-hints.html)
- * [Set Operators](sql-ref-syntax-qry-select-setops.html)
- * [TABLESAMPLE](sql-ref-syntax-qry-sampling.html)
- * [Table-valued Function](sql-ref-syntax-qry-select-tvf.html)
- * [Inline Table](sql-ref-syntax-qry-select-inline-table.html)
- * [Common Table Expression](sql-ref-syntax-qry-select-cte.html)
- * [Window Function](sql-ref-syntax-qry-window.html)
- * [EXPLAIN Statement](sql-ref-syntax-qry-explain.html)
+* [WHERE Clause](sql-ref-syntax-qry-select-where.html)
+* [GROUP BY Clause](sql-ref-syntax-qry-select-groupby.html)
+* [HAVING Clause](sql-ref-syntax-qry-select-having.html)
+* [ORDER BY Clause](sql-ref-syntax-qry-select-orderby.html)
+* [SORT BY Clause](sql-ref-syntax-qry-select-sortby.html)
+* [CLUSTER BY Clause](sql-ref-syntax-qry-select-clusterby.html)
+* [DISTRIBUTE BY Clause](sql-ref-syntax-qry-select-distribute-by.html)
+* [LIMIT Clause](sql-ref-syntax-qry-select-limit.html)
+* [Common Table Expression](sql-ref-syntax-qry-select-cte.html)
+* [Inline Table](sql-ref-syntax-qry-select-inline-table.html)
+* [JOIN](sql-ref-syntax-qry-select-join.html)
+* [Join Hints](sql-ref-syntax-qry-select-hints.html)
+* [LIKE Predicate](sql-ref-syntax-qry-select-like.html)
+* [Set Operators](sql-ref-syntax-qry-select-setops.html)
+* [TABLESAMPLE](sql-ref-syntax-qry-sampling.html)
+* [Table-valued Function](sql-ref-syntax-qry-select-tvf.html)
+* [Window Function](sql-ref-syntax-qry-window.html)
+* [EXPLAIN Statement](sql-ref-syntax-qry-explain.html)

From fad1bd029c6023db3287c90363b6fbd46b17d113 Mon Sep 17 00:00:00 2001
From: Huaxin Gao <huaxing@us.ibm.com>
Date: Mon, 4 May 2020 09:13:37 -0700
Subject: [PATCH 02/19] fix

---
 docs/sql-ref-syntax-aux-analyze-table.md           | 2 +-
 docs/sql-ref-syntax-aux-show-functions.md          | 2 +-
 docs/sql-ref-syntax-aux-show.md                    | 4 ++--
 docs/sql-ref-syntax-ddl-alter-table.md             | 4 ----
 docs/sql-ref-syntax-ddl-create-function.md         | 6 ++++--
 docs/sql-ref-syntax-ddl-create-table-datasource.md | 2 +-
 6 files changed, 9 insertions(+), 11 deletions(-)

diff --git a/docs/sql-ref-syntax-aux-analyze-table.md b/docs/sql-ref-syntax-aux-analyze-table.md
index a8e11303432ba..8f43d7388d7db 100644
--- a/docs/sql-ref-syntax-aux-analyze-table.md
+++ b/docs/sql-ref-syntax-aux-analyze-table.md
@@ -47,7 +47,7 @@ ANALYZE TABLE table_identifier [ partition_spec ]
 
 * **[ NOSCAN `|` FOR COLUMNS col [ , ... ] `|` FOR ALL COLUMNS ]**
 
-     * If no analyze option is specified, `ANALYZE TABLE` collects the table's number of rows and size in bytes. </li>
+     * If no analyze option is specified, `ANALYZE TABLE` collects the table's number of rows and size in bytes.
      * **NOSCAN**
 
        Collects only the table's size in bytes ( which does not require scanning the entire table ).
diff --git a/docs/sql-ref-syntax-aux-show-functions.md b/docs/sql-ref-syntax-aux-show-functions.md
index 2cfca0f34bf77..942d6a5409ca4 100644
--- a/docs/sql-ref-syntax-aux-show-functions.md
+++ b/docs/sql-ref-syntax-aux-show-functions.md
@@ -49,7 +49,7 @@ SHOW [ function_kind ] FUNCTIONS [ [ LIKE ] { function_name | regex_pattern } ]
     a database then the function is resolved from the user specified database, otherwise
     it is resolved from the current database.
 
-    **Syntax:** `[database_name.]function_name`
+    **Syntax:** `[ database_name. ] function_name`
 
 * **regex_pattern**
 
diff --git a/docs/sql-ref-syntax-aux-show.md b/docs/sql-ref-syntax-aux-show.md
index 424fe71370897..9f64ea2d50ae1 100644
--- a/docs/sql-ref-syntax-aux-show.md
+++ b/docs/sql-ref-syntax-aux-show.md
@@ -20,11 +20,11 @@ license: |
 ---
 
  * [SHOW COLUMNS](sql-ref-syntax-aux-show-columns.html)
+ * [SHOW CREATE TABLE](sql-ref-syntax-aux-show-create-table.html)
  * [SHOW DATABASES](sql-ref-syntax-aux-show-databases.html)
  * [SHOW FUNCTIONS](sql-ref-syntax-aux-show-functions.html)
+ * [SHOW PARTITIONS](sql-ref-syntax-aux-show-partitions.html)
  * [SHOW TABLE EXTENDED](sql-ref-syntax-aux-show-table.html)
  * [SHOW TABLES](sql-ref-syntax-aux-show-tables.html)
  * [SHOW TBLPROPERTIES](sql-ref-syntax-aux-show-tblproperties.html)
- * [SHOW PARTITIONS](sql-ref-syntax-aux-show-partitions.html)
- * [SHOW CREATE TABLE](sql-ref-syntax-aux-show-create-table.html)
  * [SHOW VIEWS](sql-ref-syntax-aux-show-views.html)
diff --git a/docs/sql-ref-syntax-ddl-alter-table.md b/docs/sql-ref-syntax-ddl-alter-table.md
index dc3f52344c43a..7a109d91d16bf 100644
--- a/docs/sql-ref-syntax-ddl-alter-table.md
+++ b/docs/sql-ref-syntax-ddl-alter-table.md
@@ -71,8 +71,6 @@ ALTER TABLE table_identifier ADD COLUMNS ( col_spec [ , ... ] )
 
     Specifies the columns to be added.
 
-    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
-
 ### ALTER OR CHANGE COLUMN
 
 `ALTER TABLE ALTER COLUMN` or `ALTER TABLE CHANGE COLUMN` statement changes column's comment.
@@ -95,8 +93,6 @@ ALTER TABLE table_identifier { ALTER | CHANGE } [ COLUMN ] col_spec alterColumnA
 
     Specifies the columns to be added.
 
-    **Syntax:** `PARTITION ( partition_col_name  = partition_col_val [ , ... ] )`
-
 * **alterColumnAction**
 
     Change the comment string.
diff --git a/docs/sql-ref-syntax-ddl-create-function.md b/docs/sql-ref-syntax-ddl-create-function.md
index e66df5352b1b5..aa6c1fad7b56b 100644
--- a/docs/sql-ref-syntax-ddl-create-function.md
+++ b/docs/sql-ref-syntax-ddl-create-function.md
@@ -55,8 +55,10 @@ CREATE [ OR REPLACE ] [ TEMPORARY ] FUNCTION [ IF NOT EXISTS ]
 
 * **IF NOT EXISTS**
 
-    Specifies a name of function to be created. The function name may be
-    optionally qualified with a database name.
+    If specified, creates the function only when it does not exist. The creation
+    of function succeeds (no error is thrown) if the specified function already
+    exists in the system. This parameter is mutually exclusive to `OR REPLACE`
+    and can not be specified together.
 
 * **function_name**
 
diff --git a/docs/sql-ref-syntax-ddl-create-table-datasource.md b/docs/sql-ref-syntax-ddl-create-table-datasource.md
index b592116c2a9e4..bb7215ab06876 100644
--- a/docs/sql-ref-syntax-ddl-create-table-datasource.md
+++ b/docs/sql-ref-syntax-ddl-create-table-datasource.md
@@ -65,7 +65,7 @@ as any order. For example, you can write COMMENT table_comment after TBLPROPERTI
 
     **NOTE:** Bucketing is an optimization technique that uses buckets (and bucketing columns) to determine data partitioning and avoid data shuffle.
 
-* **SORTED BY**
+    **SORTED BY**
 
     Determines the order in which the data is stored in buckets. Default is Ascending order.
 

From d3033f126b0bee326b4d2f1f0d3bb426272572eb Mon Sep 17 00:00:00 2001
From: Huaxin Gao <huaxing@us.ibm.com>
Date: Mon, 4 May 2020 10:34:02 -0700
Subject: [PATCH 03/19] fix

---
 docs/sql-ref-syntax-ddl-create-table-datasource.md |  2 +-
 docs/sql-ref-syntax-ddl-create-table-hiveformat.md |  2 +-
 docs/sql-ref-syntax-ddl-create-table-like.md       |  2 +-
 docs/sql-ref-syntax-qry-window.md                  | 10 +++++-----
 4 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/docs/sql-ref-syntax-ddl-create-table-datasource.md b/docs/sql-ref-syntax-ddl-create-table-datasource.md
index bb7215ab06876..b592116c2a9e4 100644
--- a/docs/sql-ref-syntax-ddl-create-table-datasource.md
+++ b/docs/sql-ref-syntax-ddl-create-table-datasource.md
@@ -65,7 +65,7 @@ as any order. For example, you can write COMMENT table_comment after TBLPROPERTI
 
     **NOTE:** Bucketing is an optimization technique that uses buckets (and bucketing columns) to determine data partitioning and avoid data shuffle.
 
-    **SORTED BY**
+* **SORTED BY**
 
     Determines the order in which the data is stored in buckets. Default is Ascending order.
 
diff --git a/docs/sql-ref-syntax-ddl-create-table-hiveformat.md b/docs/sql-ref-syntax-ddl-create-table-hiveformat.md
index 576d9190f2716..7f7033fcaebaf 100644
--- a/docs/sql-ref-syntax-ddl-create-table-hiveformat.md
+++ b/docs/sql-ref-syntax-ddl-create-table-hiveformat.md
@@ -67,7 +67,7 @@ as any order. For example, you can write COMMENT table_comment after TBLPROPERTI
 
 * **LOCATION**
 
-    Path to the directory where table data is stored, Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc.
+    Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc.
 
 * **COMMENT**
 
diff --git a/docs/sql-ref-syntax-ddl-create-table-like.md b/docs/sql-ref-syntax-ddl-create-table-like.md
index a374c554bd179..23d8e4f9712a6 100644
--- a/docs/sql-ref-syntax-ddl-create-table-like.md
+++ b/docs/sql-ref-syntax-ddl-create-table-like.md
@@ -60,7 +60,7 @@ CREATE TABLE [IF NOT EXISTS] table_identifier LIKE source_table_identifier
 
 * **LOCATION**
 
-    Path to the directory where table data is stored,Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc. Location to create an external table.
+    Path to the directory where table data is stored, which could be a path on distributed storage like HDFS, etc. Location to create an external table.
 
 ### Examples
 
diff --git a/docs/sql-ref-syntax-qry-window.md b/docs/sql-ref-syntax-qry-window.md
index 9c03b65fec3eb..823ffa2677624 100644
--- a/docs/sql-ref-syntax-qry-window.md
+++ b/docs/sql-ref-syntax-qry-window.md
@@ -58,15 +58,15 @@ window_function OVER
 
     `{ RANGE | ROWS } { frame_start | BETWEEN frame_start AND frame_end }`
 
-    If frame_end is omitted it defaults to CURRENT ROW.
+    * `frame_start` and `frame_end` have the following syntax:
 
-    `frame_start` and `frame_end` have the following syntax
+      **Syntax:**
 
-     **Syntax:**
+      `UNBOUNDED PRECEDING | offset PRECEDING | CURRENT ROW | offset FOLLOWING | UNBOUNDED FOLLOWING`
 
-     `UNBOUNDED PRECEDING | offset PRECEDING | CURRENT ROW | offset FOLLOWING | UNBOUNDED FOLLOWING`
+      `offset:` specifies the `offset` from the position of the current row.
 
-     `offset:` specifies the <code>offset</code> from the position of the current row.
+    **Note:** If `frame_end` is omitted it defaults to `CURRENT ROW`.
 
 ### Examples
 

From ca9f9ebaa38b6309de79d2101711929b20032e02 Mon Sep 17 00:00:00 2001
From: Max Gekk <max.gekk@gmail.com>
Date: Sat, 2 May 2020 17:54:36 +0900
Subject: [PATCH 04/19] [MINOR][SQL][TESTS] Disable UI in SQL benchmarks by
 default

### What changes were proposed in this pull request?
Set `spark.ui.enabled` to `false` in `SqlBasedBenchmark.getSparkSession`. This disables UI in all SQL benchmarks by default.

### Why are the changes needed?
UI overhead lowers numbers in the `Relative` column and impacts on `Stdev` in benchmark results.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
Checked by running `DateTimeRebaseBenchmark`.

Closes #28432 from MaxGekk/ui-off-in-benchmarks.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
---
 .../spark/sql/execution/benchmark/DataSourceReadBenchmark.scala | 2 --
 .../spark/sql/execution/benchmark/FilterPushdownBenchmark.scala | 2 --
 .../spark/sql/execution/benchmark/SqlBasedBenchmark.scala       | 2 ++
 3 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DataSourceReadBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DataSourceReadBenchmark.scala
index d29c5e3f88010..0fc43c7052d06 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DataSourceReadBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DataSourceReadBenchmark.scala
@@ -23,7 +23,6 @@ import scala.util.Random
 
 import org.apache.spark.SparkConf
 import org.apache.spark.benchmark.Benchmark
-import org.apache.spark.internal.config.UI._
 import org.apache.spark.sql.{DataFrame, DataFrameWriter, Row, SparkSession}
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.execution.datasources.parquet.{SpecificParquetRecordReaderBase, VectorizedParquetRecordReader}
@@ -52,7 +51,6 @@ object DataSourceReadBenchmark extends SqlBasedBenchmark {
       .set("spark.master", "local[1]")
       .setIfMissing("spark.driver.memory", "3g")
       .setIfMissing("spark.executor.memory", "3g")
-      .setIfMissing(UI_ENABLED, false)
 
     val sparkSession = SparkSession.builder.config(conf).getOrCreate()
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala
index 444ffa4f99697..b3f65d40ad95b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala
@@ -23,7 +23,6 @@ import scala.util.Random
 
 import org.apache.spark.SparkConf
 import org.apache.spark.benchmark.Benchmark
-import org.apache.spark.internal.config.UI._
 import org.apache.spark.sql.{DataFrame, SparkSession}
 import org.apache.spark.sql.functions.monotonically_increasing_id
 import org.apache.spark.sql.internal.SQLConf
@@ -49,7 +48,6 @@ object FilterPushdownBenchmark extends SqlBasedBenchmark {
       .set("spark.master", "local[1]")
       .setIfMissing("spark.driver.memory", "3g")
       .setIfMissing("spark.executor.memory", "3g")
-      .setIfMissing(UI_ENABLED, false)
       .setIfMissing("orc.compression", "snappy")
       .setIfMissing("spark.sql.parquet.compression.codec", "snappy")
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/SqlBasedBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/SqlBasedBenchmark.scala
index ee7a03e5e0542..28387dcef125b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/SqlBasedBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/SqlBasedBenchmark.scala
@@ -18,6 +18,7 @@
 package org.apache.spark.sql.execution.benchmark
 
 import org.apache.spark.benchmark.{Benchmark, BenchmarkBase}
+import org.apache.spark.internal.config.UI.UI_ENABLED
 import org.apache.spark.sql.{Dataset, SparkSession}
 import org.apache.spark.sql.SaveMode.Overwrite
 import org.apache.spark.sql.catalyst.plans.SQLHelper
@@ -37,6 +38,7 @@ trait SqlBasedBenchmark extends BenchmarkBase with SQLHelper {
       .appName(this.getClass.getCanonicalName)
       .config(SQLConf.SHUFFLE_PARTITIONS.key, 1)
       .config(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key, 1)
+      .config(UI_ENABLED.key, false)
       .getOrCreate()
   }
 

From 0c8146a062e14042a8f865282636d157c0e4e029 Mon Sep 17 00:00:00 2001
From: Michael Chirico <michael.chirico@grabtaxi.com>
Date: Sun, 3 May 2020 12:40:20 +0900
Subject: [PATCH 05/19] [SPARK-31571][R] Overhaul stop/message/warning calls to
 be more canonical

### What changes were proposed in this pull request?

Internal usages like `{stop,warning,message}({paste,paste0,sprintf}` and `{stop,warning,message}(some_literal_string_as_variable` have been removed and replaced as appropriate.

### Why are the changes needed?

CRAN policy recommends against using such constructions to build error messages, in particular because it makes the process of creating portable error messages for the package more onerous.

### Does this PR introduce any user-facing change?

There may be some small grammatical changes visible in error messaging.

### How was this patch tested?

Not done

Closes #28365 from MichaelChirico/r-stop-paste.

Authored-by: Michael Chirico <michael.chirico@grabtaxi.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
---
 R/pkg/R/DataFrame.R                   | 40 ++++++++---------
 R/pkg/R/RDD.R                         |  2 +-
 R/pkg/R/SQLContext.R                  | 17 ++++----
 R/pkg/R/client.R                      |  7 ++-
 R/pkg/R/context.R                     |  8 ++--
 R/pkg/R/deserialize.R                 |  2 +-
 R/pkg/R/group.R                       |  4 +-
 R/pkg/R/install.R                     | 62 +++++++++++----------------
 R/pkg/R/mllib_classification.R        |  4 +-
 R/pkg/R/mllib_stat.R                  |  3 +-
 R/pkg/R/pairRDD.R                     |  2 +-
 R/pkg/R/schema.R                      |  2 +-
 R/pkg/R/serialize.R                   |  4 +-
 R/pkg/R/sparkR.R                      |  9 ++--
 R/pkg/R/utils.R                       | 53 +++++++++++------------
 R/pkg/tests/fulltests/test_sparkSQL.R |  2 +-
 16 files changed, 103 insertions(+), 118 deletions(-)

diff --git a/R/pkg/R/DataFrame.R b/R/pkg/R/DataFrame.R
index 09e831814b893..15b3ce2935427 100644
--- a/R/pkg/R/DataFrame.R
+++ b/R/pkg/R/DataFrame.R
@@ -431,7 +431,7 @@ setMethod("coltypes",
                 if (is.null(type)) {
                   specialtype <- specialtypeshandle(x)
                   if (is.null(specialtype)) {
-                    stop(paste("Unsupported data type: ", x))
+                    stop("Unsupported data type: ", x)
                   }
                   type <- PRIMITIVE_TYPES[[specialtype]]
                 }
@@ -829,8 +829,8 @@ setMethod("repartitionByRange",
                 jcol <- lapply(cols, function(c) { c@jc })
                 sdf <- callJMethod(x@sdf, "repartitionByRange", numToInt(numPartitions), jcol)
               } else {
-                stop(paste("numPartitions and col must be numeric and Column; however, got",
-                           class(numPartitions), "and", class(col)))
+                stop("numPartitions and col must be numeric and Column; however, got ",
+                     class(numPartitions), " and ", class(col))
               }
             } else if (!is.null(col))  {
               # only columns are specified
@@ -839,7 +839,7 @@ setMethod("repartitionByRange",
                 jcol <- lapply(cols, function(c) { c@jc })
                 sdf <- callJMethod(x@sdf, "repartitionByRange", jcol)
               } else {
-                stop(paste("col must be Column; however, got", class(col)))
+                stop("col must be Column; however, got ", class(col))
               }
             } else if (!is.null(numPartitions)) {
               # only numPartitions is specified
@@ -1068,10 +1068,10 @@ setMethod("sample",
           signature(x = "SparkDataFrame"),
           function(x, withReplacement = FALSE, fraction, seed) {
             if (!is.numeric(fraction)) {
-              stop(paste("fraction must be numeric; however, got", class(fraction)))
+              stop("fraction must be numeric; however, got ", class(fraction))
             }
             if (!is.logical(withReplacement)) {
-              stop(paste("withReplacement must be logical; however, got", class(withReplacement)))
+              stop("withReplacement must be logical; however, got ", class(withReplacement))
             }
 
             if (!missing(seed)) {
@@ -1211,11 +1211,10 @@ setMethod("collect",
                 checkSchemaInArrow(schema(x))
                 TRUE
               }, error = function(e) {
-                warning(paste0("The conversion from Spark DataFrame to R DataFrame was attempted ",
-                               "with Arrow optimization because ",
-                               "'spark.sql.execution.arrow.sparkr.enabled' is set to true; ",
-                               "however, failed, attempting non-optimization. Reason: ",
-                               e))
+                warning("The conversion from Spark DataFrame to R DataFrame was attempted ",
+                        "with Arrow optimization because ",
+                        "'spark.sql.execution.arrow.sparkr.enabled' is set to true; ",
+                        "however, failed, attempting non-optimization. Reason: ", e)
                 FALSE
               })
             }
@@ -1508,8 +1507,8 @@ dapplyInternal <- function(x, func, schema) {
     if (inherits(schema, "structType")) {
       checkSchemaInArrow(schema)
     } else if (is.null(schema)) {
-      stop(paste0("Arrow optimization does not support 'dapplyCollect' yet. Please disable ",
-                  "Arrow optimization or use 'collect' and 'dapply' APIs instead."))
+      stop("Arrow optimization does not support 'dapplyCollect' yet. Please disable ",
+           "Arrow optimization or use 'collect' and 'dapply' APIs instead.")
     } else {
       stop("'schema' should be DDL-formatted string or structType.")
     }
@@ -2012,8 +2011,8 @@ setMethod("[", signature(x = "SparkDataFrame"),
               x
             } else {
               if (class(i) != "Column") {
-                stop(paste0("Expressions other than filtering predicates are not supported ",
-                      "in the first parameter of extract operator [ or subset() method."))
+                stop("Expressions other than filtering predicates are not supported ",
+                      "in the first parameter of extract operator [ or subset() method.")
               }
               filter(x, i)
             }
@@ -2604,18 +2603,17 @@ setMethod("join",
               if (is.null(joinType)) {
                 sdf <- callJMethod(x@sdf, "join", y@sdf, joinExpr@jc)
               } else {
-                if (joinType %in% c("inner", "cross",
+                validJoinTypes <- c("inner", "cross",
                     "outer", "full", "fullouter", "full_outer",
                     "left", "leftouter", "left_outer",
                     "right", "rightouter", "right_outer",
-                    "semi", "left_semi", "leftsemi", "anti", "left_anti", "leftanti")) {
+                    "semi", "leftsemi", "left_semi", "anti", "leftanti", "left_anti")
+                if (joinType %in% validJoinTypes) {
                   joinType <- gsub("_", "", joinType, fixed = TRUE)
                   sdf <- callJMethod(x@sdf, "join", y@sdf, joinExpr@jc, joinType)
                 } else {
-                  stop(paste("joinType must be one of the following types:",
-                       "'inner', 'cross', 'outer', 'full', 'fullouter', 'full_outer',",
-                       "'left', 'leftouter', 'left_outer', 'right', 'rightouter', 'right_outer',",
-                       "'semi', 'leftsemi', 'left_semi', 'anti', 'leftanti' or 'left_anti'."))
+                  stop("joinType must be one of the following types: ",
+                       "'", paste(validJoinTypes, collapse = "', '"), "'")
                 }
               }
             }
diff --git a/R/pkg/R/RDD.R b/R/pkg/R/RDD.R
index 7ee725d90d550..7a1d157bb8a36 100644
--- a/R/pkg/R/RDD.R
+++ b/R/pkg/R/RDD.R
@@ -947,7 +947,7 @@ setMethod("takeSample", signature(x = "RDD", withReplacement = "logical",
             MAXINT <- .Machine$integer.max
 
             if (num < 0)
-              stop(paste("Negative number of elements requested"))
+              stop("Negative number of elements requested")
 
             if (initialCount > MAXINT - 1) {
               maxSelected <- MAXINT - 1
diff --git a/R/pkg/R/SQLContext.R b/R/pkg/R/SQLContext.R
index 1ef2641742704..c0ac68332ec41 100644
--- a/R/pkg/R/SQLContext.R
+++ b/R/pkg/R/SQLContext.R
@@ -34,7 +34,7 @@ getInternalType <- function(x) {
          Date = "date",
          POSIXlt = "timestamp",
          POSIXct = "timestamp",
-         stop(paste("Unsupported type for SparkDataFrame:", class(x))))
+         stop("Unsupported type for SparkDataFrame: ", class(x)))
 }
 
 #' return the SparkSession
@@ -112,9 +112,9 @@ sparkR.conf <- function(key, defaultValue) {
               error = function(e) {
                 estr <- as.character(e)
                 if (any(grepl("java.util.NoSuchElementException", estr, fixed = TRUE))) {
-                  stop(paste0("Config '", key, "' is not set"))
+                  stop("Config '", key, "' is not set")
                 } else {
-                  stop(paste0("Unknown error: ", estr))
+                  stop("Unknown error: ", estr)
                 }
               })
     } else {
@@ -208,7 +208,7 @@ getSchema <- function(schema, firstRow = NULL, rdd = NULL) {
     names <- lapply(names, function(n) {
       nn <- gsub(".", "_", n, fixed = TRUE)
       if (nn != n) {
-        warning(paste("Use", nn, "instead of", n, "as column name"))
+        warning("Use ", nn, " instead of ", n, " as column name")
       }
       nn
     })
@@ -290,10 +290,9 @@ createDataFrame <- function(data, schema = NULL, samplingRatio = 1.0,
         TRUE
       },
       error = function(e) {
-        warning(paste0("createDataFrame attempted Arrow optimization because ",
-                       "'spark.sql.execution.arrow.sparkr.enabled' is set to true; however, ",
-                       "failed, attempting non-optimization. Reason: ",
-                       e))
+        warning("createDataFrame attempted Arrow optimization because ",
+                "'spark.sql.execution.arrow.sparkr.enabled' is set to true; however, ",
+                "failed, attempting non-optimization. Reason: ", e)
         FALSE
       })
     }
@@ -326,7 +325,7 @@ createDataFrame <- function(data, schema = NULL, samplingRatio = 1.0,
   } else if (inherits(data, "RDD")) {
     rdd <- data
   } else {
-    stop(paste("unexpected type:", class(data)))
+    stop("unexpected type: ", class(data))
   }
 
   schema <- getSchema(schema, firstRow, rdd)
diff --git a/R/pkg/R/client.R b/R/pkg/R/client.R
index 872b21443eaad..797a5c7da1549 100644
--- a/R/pkg/R/client.R
+++ b/R/pkg/R/client.R
@@ -102,10 +102,9 @@ checkJavaVersion <- function() {
     javaVersionNum <- as.integer(versions[1])
   }
   if (javaVersionNum < minJavaVersion || javaVersionNum >= maxJavaVersion) {
-    stop(paste0("Java version, greater than or equal to ", minJavaVersion,
-                " and less than ", maxJavaVersion,
-                ", is required for this package; found version: ",
-                javaVersionStr))
+    stop("Java version, greater than or equal to ", minJavaVersion,
+         " and less than ", maxJavaVersion, ", is required for this ",
+         "package; found version: ", javaVersionStr)
   }
   return(javaVersionNum)
 }
diff --git a/R/pkg/R/context.R b/R/pkg/R/context.R
index d96a287f818a2..e3c9d9f8793d6 100644
--- a/R/pkg/R/context.R
+++ b/R/pkg/R/context.R
@@ -144,13 +144,13 @@ parallelize <- function(sc, coll, numSlices = 1) {
   if ((!is.list(coll) && !is.vector(coll)) || is.data.frame(coll)) {
   # nolint end
     if (is.data.frame(coll)) {
-      message(paste("context.R: A data frame is parallelized by columns."))
+      message("context.R: A data frame is parallelized by columns.")
     } else {
       if (is.matrix(coll)) {
-        message(paste("context.R: A matrix is parallelized by elements."))
+        message("context.R: A matrix is parallelized by elements.")
       } else {
-        message(paste("context.R: parallelize() currently only supports lists and vectors.",
-                      "Calling as.list() to coerce coll into a list."))
+        message("context.R: parallelize() currently only supports lists and vectors. ",
+                "Calling as.list() to coerce coll into a list.")
       }
     }
     coll <- as.list(coll)
diff --git a/R/pkg/R/deserialize.R b/R/pkg/R/deserialize.R
index ca4a6e342d772..3e7c456bd548d 100644
--- a/R/pkg/R/deserialize.R
+++ b/R/pkg/R/deserialize.R
@@ -57,7 +57,7 @@ readTypedObject <- function(con, type) {
     "s" = readStruct(con),
     "n" = NULL,
     "j" = getJobj(readString(con)),
-    stop(paste("Unsupported type for deserialization", type)))
+    stop("Unsupported type for deserialization ", type))
 }
 
 readStringData <- function(con, len) {
diff --git a/R/pkg/R/group.R b/R/pkg/R/group.R
index 2b7995e1e37f6..99d62240a3b2a 100644
--- a/R/pkg/R/group.R
+++ b/R/pkg/R/group.R
@@ -234,8 +234,8 @@ gapplyInternal <- function(x, func, schema) {
     if (inherits(schema, "structType")) {
       checkSchemaInArrow(schema)
     } else if (is.null(schema)) {
-      stop(paste0("Arrow optimization does not support 'gapplyCollect' yet. Please disable ",
-                  "Arrow optimization or use 'collect' and 'gapply' APIs instead."))
+      stop("Arrow optimization does not support 'gapplyCollect' yet. Please disable ",
+           "Arrow optimization or use 'collect' and 'gapply' APIs instead.")
     } else {
       stop("'schema' should be DDL-formatted string or structType.")
     }
diff --git a/R/pkg/R/install.R b/R/pkg/R/install.R
index 8c5355a8324f9..ea2c0b4c0f42f 100644
--- a/R/pkg/R/install.R
+++ b/R/pkg/R/install.R
@@ -89,8 +89,8 @@ install.spark <- function(hadoopVersion = "2.7", mirrorUrl = NULL,
   }
 
   if (overwrite) {
-    message(paste0("Overwrite = TRUE: download and overwrite the tar file",
-                   "and Spark package directory if they exist."))
+    message("Overwrite = TRUE: download and overwrite the tar file",
+            "and Spark package directory if they exist.")
   }
 
   releaseUrl <- Sys.getenv("SPARKR_RELEASE_DOWNLOAD_URL")
@@ -103,12 +103,11 @@ install.spark <- function(hadoopVersion = "2.7", mirrorUrl = NULL,
   # can use dir.exists(packageLocalDir) under R 3.2.0 or later
   if (!is.na(file.info(packageLocalDir)$isdir) && !overwrite) {
     if (releaseUrl != "") {
-      message(paste(packageName, "found, setting SPARK_HOME to", packageLocalDir))
+      message(packageName, " found, setting SPARK_HOME to ", packageLocalDir)
     } else {
-      fmt <- "%s for Hadoop %s found, setting SPARK_HOME to %s"
-      msg <- sprintf(fmt, version, ifelse(hadoopVersion == "without", "Free build", hadoopVersion),
-                     packageLocalDir)
-      message(msg)
+      message(version, " for Hadoop ",
+              if (hadoopVersion == "without") "Free build" else hadoopVersion,
+              " found, setting SPARK_HOME to ", packageLocalDir)
     }
     Sys.setenv(SPARK_HOME = packageLocalDir)
     return(invisible(packageLocalDir))
@@ -127,26 +126,23 @@ install.spark <- function(hadoopVersion = "2.7", mirrorUrl = NULL,
       success <- downloadUrl(releaseUrl, packageLocalPath)
       if (!success) {
         unlink(packageLocalPath)
-        stop(paste0("Fetch failed from ", releaseUrl))
+        stop("Fetch failed from ", releaseUrl)
       }
     } else {
       robustDownloadTar(mirrorUrl, version, hadoopVersion, packageName, packageLocalPath)
     }
   }
 
-  message(sprintf("Installing to %s", localDir))
+  message("Installing to ", localDir)
   # There are two ways untar can fail - untar could stop() on errors like incomplete block on file
   # or, tar command can return failure code
   success <- tryCatch(untar(tarfile = packageLocalPath, exdir = localDir) == 0,
                      error = function(e) {
-                       message(e)
-                       message()
+                       message(e, "\n")
                        FALSE
                      },
                      warning = function(w) {
-                       # Treat warning as error, add an empty line with message()
-                       message(w)
-                       message()
+                       message(w, "\n")
                        FALSE
                      })
   if (!tarExists || overwrite || !success) {
@@ -160,7 +156,7 @@ install.spark <- function(hadoopVersion = "2.7", mirrorUrl = NULL,
   if (!success) stop("Extract archive failed.")
   message("DONE.")
   Sys.setenv(SPARK_HOME = packageLocalDir)
-  message(paste("SPARK_HOME set to", packageLocalDir))
+  message("SPARK_HOME set to ", packageLocalDir)
   invisible(packageLocalDir)
 }
 
@@ -173,7 +169,7 @@ robustDownloadTar <- function(mirrorUrl, version, hadoopVersion, packageName, pa
     if (success) {
       return()
     } else {
-      message(paste0("Unable to download from mirrorUrl: ", mirrorUrl))
+      message("Unable to download from mirrorUrl: ", mirrorUrl)
     }
   } else {
     message("MirrorUrl not provided.")
@@ -201,11 +197,9 @@ robustDownloadTar <- function(mirrorUrl, version, hadoopVersion, packageName, pa
     # remove any partially downloaded file
     unlink(packageLocalPath)
     message("Unable to download from default mirror site: ", mirrorUrl)
-    msg <- sprintf(paste("Unable to download Spark %s for Hadoop %s.",
-                         "Please check network connection, Hadoop version,",
-                         "or provide other mirror sites."),
-                   version, ifelse(hadoopVersion == "without", "Free build", hadoopVersion))
-    stop(msg)
+    stop("Unable to download Spark ", version,
+         " for Hadoop ", if (hadoopVersion == "without") "Free build" else hadoopVersion,
+         ". Please check network connection, Hadoop version, or provide other mirror sites.")
   }
 }
 
@@ -222,7 +216,7 @@ getPreferredMirror <- function(version, packageName) {
     endPos <- matchInfo + attr(matchInfo, "match.length") - 2
     mirrorPreferred <- base::substr(linePreferred, startPos, endPos)
     mirrorPreferred <- paste0(mirrorPreferred, "spark")
-    message(sprintf("Preferred mirror site found: %s", mirrorPreferred))
+    message("Preferred mirror site found: ", mirrorPreferred)
   } else {
     mirrorPreferred <- NULL
   }
@@ -231,24 +225,20 @@ getPreferredMirror <- function(version, packageName) {
 
 directDownloadTar <- function(mirrorUrl, version, hadoopVersion, packageName, packageLocalPath) {
   packageRemotePath <- paste0(file.path(mirrorUrl, version, packageName), ".tgz")
-  fmt <- "Downloading %s for Hadoop %s from:\n- %s"
-  msg <- sprintf(fmt, version, ifelse(hadoopVersion == "without", "Free build", hadoopVersion),
-                 packageRemotePath)
-  message(msg)
+  message("Downloading ", version, " for Hadoop ",
+          if (hadoopVersion == "without") "Free build" else hadoopVersion,
+          " from:\n- ", packageRemotePath)
   downloadUrl(packageRemotePath, packageLocalPath)
 }
 
 downloadUrl <- function(remotePath, localPath) {
   isFail <- tryCatch(download.file(remotePath, localPath),
                      error = function(e) {
-                       message(e)
-                       message()
+                       message(e, "\n")
                        TRUE
                      },
                      warning = function(w) {
-                       # Treat warning as error, add an empty line with message()
-                       message(w)
-                       message()
+                       message(w, "\n")
                        TRUE
                      })
   !isFail
@@ -279,9 +269,9 @@ sparkCachePath <- function() {
       winAppPath <- Sys.getenv("USERPROFILE", unset = NA)
     }
     if (is.na(winAppPath)) {
-      stop(paste("%LOCALAPPDATA% and %USERPROFILE% not found.",
-                   "Please define the environment variable",
-                   "or restart and enter an installation path in localDir."))
+      stop("%LOCALAPPDATA% and %USERPROFILE% not found. ",
+           "Please define the environment variable ",
+           "or restart and enter an installation path in localDir.")
     } else {
       path <- file.path(winAppPath, "Apache", "Spark", "Cache")
     }
@@ -293,7 +283,7 @@ sparkCachePath <- function() {
         Sys.getenv("XDG_CACHE_HOME", file.path(Sys.getenv("HOME"), ".cache")), "spark")
     }
   } else {
-    stop(sprintf("Unknown OS: %s", .Platform$OS.type))
+    stop("Unknown OS: ", .Platform$OS.type)
   }
   normalizePath(path, mustWork = FALSE)
 }
@@ -322,7 +312,7 @@ installInstruction <- function(mode) {
            "If you need further help, ",
            "contact the administrators of the cluster.")
   } else {
-    stop(paste0("No instruction found for ", mode, " mode."))
+    stop("No instruction found for mode ", mode)
   }
 }
 
diff --git a/R/pkg/R/mllib_classification.R b/R/pkg/R/mllib_classification.R
index 5cc97ea723afc..ec83b6bd406a7 100644
--- a/R/pkg/R/mllib_classification.R
+++ b/R/pkg/R/mllib_classification.R
@@ -337,8 +337,8 @@ setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula")
 
               if (!is.null(lowerBoundsOnCoefficients) && (row != nrow(upperBoundsOnCoefficients)
                 || col != ncol(upperBoundsOnCoefficients))) {
-                stop(paste0("dimension of upperBoundsOnCoefficients ",
-                            "is not the same as lowerBoundsOnCoefficients"))
+                stop("dimension of upperBoundsOnCoefficients ",
+                     "is not the same as lowerBoundsOnCoefficients")
               }
 
               if (is.null(lowerBoundsOnCoefficients)) {
diff --git a/R/pkg/R/mllib_stat.R b/R/pkg/R/mllib_stat.R
index f8c3329359961..6db4d5d4831dd 100644
--- a/R/pkg/R/mllib_stat.R
+++ b/R/pkg/R/mllib_stat.R
@@ -69,8 +69,7 @@ setMethod("spark.kstest", signature(data = "SparkDataFrame"),
           function(data, testCol = "test", nullHypothesis = c("norm"), distParams = c(0, 1)) {
             tryCatch(match.arg(nullHypothesis),
                      error = function(e) {
-                       msg <- paste("Distribution", nullHypothesis, "is not supported.")
-                       stop(msg)
+                       stop("Distribution ", nullHypothesis, " is not supported.")
                      })
             if (nullHypothesis == "norm") {
               distParams <- as.numeric(distParams)
diff --git a/R/pkg/R/pairRDD.R b/R/pkg/R/pairRDD.R
index 9c2e57d3067db..b29381bb900fb 100644
--- a/R/pkg/R/pairRDD.R
+++ b/R/pkg/R/pairRDD.R
@@ -906,7 +906,7 @@ setMethod("sampleByKey",
 
             for (elem in fractions) {
               if (elem < 0.0) {
-                stop(paste("Negative fraction value ", fractions[which(fractions == elem)]))
+                stop("Negative fraction value ", fractions[which(fractions == elem)])
               }
             }
 
diff --git a/R/pkg/R/schema.R b/R/pkg/R/schema.R
index 89d5c2cd1a5e2..7044ede0cc58b 100644
--- a/R/pkg/R/schema.R
+++ b/R/pkg/R/schema.R
@@ -199,7 +199,7 @@ checkType <- function(type) {
             })
   }
 
-  stop(paste("Unsupported type for SparkDataframe:", type))
+  stop("Unsupported type for SparkDataframe: ", type)
 }
 
 #' @param type The data type of the field
diff --git a/R/pkg/R/serialize.R b/R/pkg/R/serialize.R
index cb3c1c59d12ed..7760d9be16f0b 100644
--- a/R/pkg/R/serialize.R
+++ b/R/pkg/R/serialize.R
@@ -84,7 +84,7 @@ writeObject <- function(con, object, writeType = TRUE) {
          Date = writeDate(con, object),
          POSIXlt = writeTime(con, object),
          POSIXct = writeTime(con, object),
-         stop(paste("Unsupported type for serialization", type)))
+         stop("Unsupported type for serialization ", type))
 }
 
 writeVoid <- function(con) {
@@ -158,7 +158,7 @@ writeType <- function(con, class) {
                  Date = "D",
                  POSIXlt = "t",
                  POSIXct = "t",
-                 stop(paste("Unsupported type for serialization", class)))
+                 stop("Unsupported type for serialization ", class))
   writeBin(charToRaw(type), con)
 }
 
diff --git a/R/pkg/R/sparkR.R b/R/pkg/R/sparkR.R
index 9ba36ad46740a..e4a11a5f78a71 100644
--- a/R/pkg/R/sparkR.R
+++ b/R/pkg/R/sparkR.R
@@ -154,8 +154,8 @@ sparkR.sparkContext <- function(
   connectionTimeout <- as.numeric(Sys.getenv("SPARKR_BACKEND_CONNECTION_TIMEOUT", "6000"))
   if (existingPort != "") {
     if (length(packages) != 0) {
-      warning(paste("sparkPackages has no effect when using spark-submit or sparkR shell",
-                    " please use the --packages commandline instead", sep = ","))
+      warning("sparkPackages has no effect when using spark-submit or sparkR shell, ",
+              "please use the --packages commandline instead")
     }
     backendPort <- existingPort
     authSecret <- Sys.getenv("SPARKR_BACKEND_AUTH_SECRET")
@@ -439,8 +439,9 @@ sparkR.session <- function(
   rPackageVersion <- paste0(packageVersion("SparkR"))
 
   if (jvmVersionStrip != rPackageVersion) {
-    warning(paste("Version mismatch between Spark JVM and SparkR package. JVM version was",
-                  jvmVersion, ", while R package version was", rPackageVersion))
+    warning("Version mismatch between Spark JVM and SparkR package. ",
+            "JVM version was ", jvmVersion,
+            ", while R package version was ", rPackageVersion)
   }
 
   sparkSession
diff --git a/R/pkg/R/utils.R b/R/pkg/R/utils.R
index c60e4db1496d0..65db9c21d9dbb 100644
--- a/R/pkg/R/utils.R
+++ b/R/pkg/R/utils.R
@@ -46,9 +46,9 @@ convertJListToRList <- function(jList, flatten, logicalUpperBound = NULL,
                 res <- list(unserialize(keyBytes),
                   unserialize(valBytes))
               } else {
-                stop(paste("utils.R: convertJListToRList only supports",
-                  "RDD[Array[Byte]] and",
-                  "JavaPairRDD[Array[Byte], Array[Byte]] for now"))
+                stop("utils.R: convertJListToRList only supports ",
+                  "RDD[Array[Byte]] and ",
+                  "JavaPairRDD[Array[Byte], Array[Byte]] for now")
               }
             } else {
               if (inherits(obj, "raw")) {
@@ -354,8 +354,8 @@ varargsToStrEnv <- function(...) {
       } else {
         value <- pairs[[name]]
         if (!(is.logical(value) || is.numeric(value) || is.character(value) || is.null(value))) {
-          stop(paste0("Unsupported type for ", name, " : ", class(value),
-               ". Supported types are logical, numeric, character and NULL."), call. = FALSE)
+          stop("Unsupported type for ", name, " : ", toString(class(value)), ". ",
+               "Supported types are logical, numeric, character and NULL.", call. = FALSE)
         }
         if (is.logical(value)) {
           env[[name]] <- tolower(as.character(value))
@@ -369,8 +369,7 @@ varargsToStrEnv <- function(...) {
   }
 
   if (length(ignoredNames) != 0) {
-    warning(paste0("Unnamed arguments ignored: ", paste(ignoredNames, collapse = ", "), "."),
-            call. = FALSE)
+    warning("Unnamed arguments ignored: ", toString(ignoredNames), ".", call. = FALSE)
   }
   env
 }
@@ -449,7 +448,7 @@ storageLevelToString <- function(levelObj) {
 # the user to type (for example) `5` instead of `5L` to avoid a confusing error message.
 numToInt <- function(num) {
   if (as.integer(num) != num) {
-    warning(paste("Coercing", as.list(sys.call())[[2]], "to integer."))
+    warning("Coercing ", as.list(sys.call())[[2L]], " to integer.")
   }
   as.integer(num)
 }
@@ -650,8 +649,8 @@ mergePartitions <- function(rdd, zip) {
         # For zip operation, check if corresponding partitions
         # of both RDDs have the same number of elements.
         if (zip && lengthOfKeys != lengthOfValues) {
-          stop(paste("Can only zip RDDs with same number of elements",
-                     "in each pair of corresponding partitions."))
+          stop("Can only zip RDDs with same number of elements ",
+               "in each pair of corresponding partitions.")
         }
 
         if (lengthOfKeys > 1) {
@@ -804,7 +803,7 @@ handledCallJMethod <- function(obj, method, ...) {
 
 captureJVMException <- function(e, method) {
   rawmsg <- as.character(e)
-  if (any(grep("^Error in .*?: ", rawmsg))) {
+  if (any(grepl("^Error in .*?: ", rawmsg))) {
     # If the exception message starts with "Error in ...", this is possibly
     # "Error in invokeJava(...)". Here, it replaces the characters to
     # `paste("Error in", method, ":")` in order to identify which function
@@ -818,58 +817,58 @@ captureJVMException <- function(e, method) {
   }
 
   # StreamingQueryException could wrap an IllegalArgumentException, so look for that first
-  if (any(grep("org.apache.spark.sql.streaming.StreamingQueryException: ",
-               stacktrace, fixed = TRUE))) {
+  if (any(grepl("org.apache.spark.sql.streaming.StreamingQueryException: ",
+                stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "org.apache.spark.sql.streaming.StreamingQueryException: ",
                     fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(paste0(rmsg, "streaming query error - ", first), call. = FALSE)
-  } else if (any(grep("java.lang.IllegalArgumentException: ", stacktrace, fixed = TRUE))) {
+    stop(rmsg, "streaming query error - ", first, call. = FALSE)
+  } else if (any(grepl("java.lang.IllegalArgumentException: ", stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "java.lang.IllegalArgumentException: ", fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(paste0(rmsg, "illegal argument - ", first), call. = FALSE)
-  } else if (any(grep("org.apache.spark.sql.AnalysisException: ", stacktrace, fixed = TRUE))) {
+    stop(rmsg, "illegal argument - ", first, call. = FALSE)
+  } else if (any(grepl("org.apache.spark.sql.AnalysisException: ", stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "org.apache.spark.sql.AnalysisException: ", fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(paste0(rmsg, "analysis error - ", first), call. = FALSE)
+    stop(rmsg, "analysis error - ", first, call. = FALSE)
   } else
-    if (any(grep("org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException: ",
-                 stacktrace, fixed = TRUE))) {
+    if (any(grepl("org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException: ",
+                  stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException: ",
                     fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(paste0(rmsg, "no such database - ", first), call. = FALSE)
+    stop(rmsg, "no such database - ", first, call. = FALSE)
   } else
-    if (any(grep("org.apache.spark.sql.catalyst.analysis.NoSuchTableException: ",
-                 stacktrace, fixed = TRUE))) {
+    if (any(grepl("org.apache.spark.sql.catalyst.analysis.NoSuchTableException: ",
+                  stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "org.apache.spark.sql.catalyst.analysis.NoSuchTableException: ",
                     fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(paste0(rmsg, "no such table - ", first), call. = FALSE)
-  } else if (any(grep("org.apache.spark.sql.catalyst.parser.ParseException: ",
-                      stacktrace, fixed = TRUE))) {
+    stop(rmsg, "no such table - ", first, call. = FALSE)
+  } else if (any(grepl("org.apache.spark.sql.catalyst.parser.ParseException: ",
+                       stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "org.apache.spark.sql.catalyst.parser.ParseException: ",
                     fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(paste0(rmsg, "parse error - ", first), call. = FALSE)
+    stop(rmsg, "parse error - ", first, call. = FALSE)
   } else {
     stop(stacktrace, call. = FALSE)
   }
diff --git a/R/pkg/tests/fulltests/test_sparkSQL.R b/R/pkg/tests/fulltests/test_sparkSQL.R
index b7172b2ae0774..611d9057c0f13 100644
--- a/R/pkg/tests/fulltests/test_sparkSQL.R
+++ b/R/pkg/tests/fulltests/test_sparkSQL.R
@@ -2558,7 +2558,7 @@ test_that("join(), crossJoin() and merge() on a DataFrame", {
   error_msg <- paste("joinType must be one of the following types:",
                  "'inner', 'cross', 'outer', 'full', 'fullouter', 'full_outer',",
                  "'left', 'leftouter', 'left_outer', 'right', 'rightouter', 'right_outer',",
-                 "'semi', 'leftsemi', 'left_semi', 'anti', 'leftanti' or 'left_anti'.")
+                 "'semi', 'leftsemi', 'left_semi', 'anti', 'leftanti', 'left_anti'")
   expect_error(join(df2, df, df2$name == df$name, "invalid"), error_msg)
 
   merged <- merge(df, df2, by.x = "name", by.y = "name", all.x = TRUE, all.y = TRUE)

From d8a2fa0e5b45d99ff0cbd4c869242fedb8541b55 Mon Sep 17 00:00:00 2001
From: Max Gekk <max.gekk@gmail.com>
Date: Mon, 4 May 2020 09:39:50 +0900
Subject: [PATCH 06/19] [SPARK-31527][SQL][TESTS][FOLLOWUP] Fix the number of
 rows in `DateTimeBenchmark`

### What changes were proposed in this pull request?
- Changed to the number of rows in benchmark cases from 3 to the actual number `N`.
- Regenerated benchmark results in the environment:

| Item | Description |
| ---- | ----|
| Region | us-west-2 (Oregon) |
| Instance | r3.xlarge |
| AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) |
| Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 |

### Why are the changes needed?
The changes are needed to have:
- Correct benchmark results
- Base line for other perf improvements that can be checked in the same environment.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
By running the benchmark and checking its output.

Closes #28440 from MaxGekk/SPARK-31527-DateTimeBenchmark-followup.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
---
 .../DateTimeBenchmark-jdk11-results.txt       | 474 +++++++++---------
 .../benchmarks/DateTimeBenchmark-results.txt  | 474 +++++++++---------
 .../benchmark/DateTimeBenchmark.scala         |   2 +-
 3 files changed, 475 insertions(+), 475 deletions(-)

diff --git a/sql/core/benchmarks/DateTimeBenchmark-jdk11-results.txt b/sql/core/benchmarks/DateTimeBenchmark-jdk11-results.txt
index 1004bcf1aa286..61b4c762a752e 100644
--- a/sql/core/benchmarks/DateTimeBenchmark-jdk11-results.txt
+++ b/sql/core/benchmarks/DateTimeBenchmark-jdk11-results.txt
@@ -2,456 +2,456 @@
 datetime +/- interval
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 datetime +/- interval:                    Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date + interval(m)                                  919            933          22          0.0   306237514.3       1.0X
-date + interval(m, d)                               910            916           9          0.0   303338619.0       1.0X
-date + interval(m, d, ms)                          3912           3923          16          0.0  1303942791.7       0.2X
-date - interval(m)                                  883            887           6          0.0   294268789.3       1.0X
-date - interval(m, d)                               898            911          18          0.0   299453403.0       1.0X
-date - interval(m, d, ms)                          3937           3944          11          0.0  1312269472.0       0.2X
-timestamp + interval(m)                            2226           2236          14          0.0   741972014.3       0.4X
-timestamp + interval(m, d)                         2264           2274          13          0.0   754709121.0       0.4X
-timestamp + interval(m, d, ms)                     2202           2223          30          0.0   734001075.0       0.4X
-timestamp - interval(m)                            1992           2005          17          0.0   664152744.7       0.5X
-timestamp - interval(m, d)                         2069           2075           9          0.0   689631159.0       0.4X
-timestamp - interval(m, d, ms)                     2240           2244           6          0.0   746538728.0       0.4X
+date + interval(m)                                 1485           1567         116          6.7         148.5       1.0X
+date + interval(m, d)                              1504           1510           9          6.6         150.4       1.0X
+date + interval(m, d, ms)                          7000           7013          18          1.4         700.0       0.2X
+date - interval(m)                                 1466           1478          17          6.8         146.6       1.0X
+date - interval(m, d)                              1533           1534           1          6.5         153.3       1.0X
+date - interval(m, d, ms)                          7014           7019           7          1.4         701.4       0.2X
+timestamp + interval(m)                            3062           3064           3          3.3         306.2       0.5X
+timestamp + interval(m, d)                         3133           3136           5          3.2         313.3       0.5X
+timestamp + interval(m, d, ms)                     3401           3402           3          2.9         340.1       0.4X
+timestamp - interval(m)                            3025           3037          17          3.3         302.5       0.5X
+timestamp - interval(m, d)                         3083           3120          51          3.2         308.3       0.5X
+timestamp - interval(m, d, ms)                     3371           3379          11          3.0         337.1       0.4X
 
 
 ================================================================================================
 Extract components
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 cast to timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast to timestamp wholestage off                    178            180           3         56.1          17.8       1.0X
-cast to timestamp wholestage on                     189            192           4         53.0          18.9       0.9X
+cast to timestamp wholestage off                    339            339           1         29.5          33.9       1.0X
+cast to timestamp wholestage on                     330            337           9         30.3          33.0       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 year of timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-year of timestamp wholestage off                    760            761           1         13.2          76.0       1.0X
-year of timestamp wholestage on                     731            741          10         13.7          73.1       1.0X
+year of timestamp wholestage off                   1226           1237          15          8.2         122.6       1.0X
+year of timestamp wholestage on                    1230           1242           9          8.1         123.0       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 quarter of timestamp:                     Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-quarter of timestamp wholestage off                1005           1013          10          9.9         100.5       1.0X
-quarter of timestamp wholestage on                  981            986           3         10.2          98.1       1.0X
+quarter of timestamp wholestage off                1602           1606           7          6.2         160.2       1.0X
+quarter of timestamp wholestage on                 1511           1514           3          6.6         151.1       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 month of timestamp:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-month of timestamp wholestage off                   754            758           6         13.3          75.4       1.0X
-month of timestamp wholestage on                    719            729          11         13.9          71.9       1.0X
+month of timestamp wholestage off                  1227           1233           8          8.1         122.7       1.0X
+month of timestamp wholestage on                   1226           1242          28          8.2         122.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 weekofyear of timestamp:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-weekofyear of timestamp wholestage off             1085           1088           4          9.2         108.5       1.0X
-weekofyear of timestamp wholestage on              1075           1091          13          9.3         107.5       1.0X
+weekofyear of timestamp wholestage off             1965           1980          20          5.1         196.5       1.0X
+weekofyear of timestamp wholestage on              1816           1833          17          5.5         181.6       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 day of timestamp:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-day of timestamp wholestage off                     751            770          27         13.3          75.1       1.0X
-day of timestamp wholestage on                      735            741           7         13.6          73.5       1.0X
+day of timestamp wholestage off                    1229           1231           3          8.1         122.9       1.0X
+day of timestamp wholestage on                     1222           1230          10          8.2         122.2       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 dayofyear of timestamp:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofyear of timestamp wholestage off               765            769           5         13.1          76.5       1.0X
-dayofyear of timestamp wholestage on                762            770           7         13.1          76.2       1.0X
+dayofyear of timestamp wholestage off              1294           1297           4          7.7         129.4       1.0X
+dayofyear of timestamp wholestage on               1257           1264           6          8.0         125.7       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 dayofmonth of timestamp:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofmonth of timestamp wholestage off              780            782           2         12.8          78.0       1.0X
-dayofmonth of timestamp wholestage on               720            736          12         13.9          72.0       1.1X
+dayofmonth of timestamp wholestage off             1247           1253           8          8.0         124.7       1.0X
+dayofmonth of timestamp wholestage on              1225           1229           4          8.2         122.5       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 dayofweek of timestamp:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofweek of timestamp wholestage off               887            899          17         11.3          88.7       1.0X
-dayofweek of timestamp wholestage on                820            847          20         12.2          82.0       1.1X
+dayofweek of timestamp wholestage off              1416           1416           0          7.1         141.6       1.0X
+dayofweek of timestamp wholestage on               1376           1382           8          7.3         137.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 weekday of timestamp:                     Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-weekday of timestamp wholestage off                 821            825           5         12.2          82.1       1.0X
-weekday of timestamp wholestage on                  802            814           9         12.5          80.2       1.0X
+weekday of timestamp wholestage off                1350           1351           1          7.4         135.0       1.0X
+weekday of timestamp wholestage on                 1308           1318          13          7.6         130.8       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 hour of timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-hour of timestamp wholestage off                    611            622          14         16.4          61.1       1.0X
-hour of timestamp wholestage on                     571            577           8         17.5          57.1       1.1X
+hour of timestamp wholestage off                   1004           1007           3         10.0         100.4       1.0X
+hour of timestamp wholestage on                     928            938           7         10.8          92.8       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 minute of timestamp:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-minute of timestamp wholestage off                  607            615          12         16.5          60.7       1.0X
-minute of timestamp wholestage on                   573            580           6         17.5          57.3       1.1X
+minute of timestamp wholestage off                 1009           1020          15          9.9         100.9       1.0X
+minute of timestamp wholestage on                   933            935           2         10.7          93.3       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 second of timestamp:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-second of timestamp wholestage off                  615            616           2         16.3          61.5       1.0X
-second of timestamp wholestage on                   564            575           8         17.7          56.4       1.1X
+second of timestamp wholestage off                  995            995           0         10.0          99.5       1.0X
+second of timestamp wholestage on                   932            937           8         10.7          93.2       1.1X
 
 
 ================================================================================================
 Current date and time
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 current_date:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-current_date wholestage off                         166            169           4         60.4          16.6       1.0X
-current_date wholestage on                          150            153           3         66.7          15.0       1.1X
+current_date wholestage off                         292            316          34         34.2          29.2       1.0X
+current_date wholestage on                          270            276           6         37.0          27.0       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 current_timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-current_timestamp wholestage off                    179            181           2         55.8          17.9       1.0X
-current_timestamp wholestage on                     162            324         138         61.9          16.2       1.1X
+current_timestamp wholestage off                    313            328          20         31.9          31.3       1.0X
+current_timestamp wholestage on                     270            331          95         37.0          27.0       1.2X
 
 
 ================================================================================================
 Date arithmetic
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 cast to date:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast to date wholestage off                         658            661           5         15.2          65.8       1.0X
-cast to date wholestage on                          644            654          10         15.5          64.4       1.0X
+cast to date wholestage off                        1078           1081           3          9.3         107.8       1.0X
+cast to date wholestage on                         1035           1040           7          9.7         103.5       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 last_day:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-last_day wholestage off                             768            772           5         13.0          76.8       1.0X
-last_day wholestage on                              737            750          12         13.6          73.7       1.0X
+last_day wholestage off                            1265           1266           3          7.9         126.5       1.0X
+last_day wholestage on                             1236           1246          10          8.1         123.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 next_day:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-next_day wholestage off                             691            704          17         14.5          69.1       1.0X
-next_day wholestage on                              664            676          10         15.1          66.4       1.0X
+next_day wholestage off                            1118           1118           1          8.9         111.8       1.0X
+next_day wholestage on                             1085           1090           8          9.2         108.5       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_add:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_add wholestage off                             646            646           0         15.5          64.6       1.0X
-date_add wholestage on                              623            640          13         16.1          62.3       1.0X
+date_add wholestage off                            1052           1054           4          9.5         105.2       1.0X
+date_add wholestage on                             1046           1051           6          9.6         104.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_sub:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_sub wholestage off                             638            645           9         15.7          63.8       1.0X
-date_sub wholestage on                              618            629           8         16.2          61.8       1.0X
+date_sub wholestage off                            1075           1075           0          9.3         107.5       1.0X
+date_sub wholestage on                             1043           1046           3          9.6         104.3       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 add_months:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-add_months wholestage off                           892            896           5         11.2          89.2       1.0X
-add_months wholestage on                            926            938           7         10.8          92.6       1.0X
+add_months wholestage off                          1409           1409           0          7.1         140.9       1.0X
+add_months wholestage on                           1448           1453           4          6.9         144.8       1.0X
 
 
 ================================================================================================
 Formatting dates
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 format date:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-format date wholestage off                         3395           3439          62          2.9         339.5       1.0X
-format date wholestage on                          3418           3438          14          2.9         341.8       1.0X
+format date wholestage off                         5373           5390          24          1.9         537.3       1.0X
+format date wholestage on                          5337           5346          12          1.9         533.7       1.0X
 
 
 ================================================================================================
 Formatting timestamps
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 from_unixtime:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-from_unixtime wholestage off                       4565           4592          38          2.2         456.5       1.0X
-from_unixtime wholestage on                        4608           4635          32          2.2         460.8       1.0X
+from_unixtime wholestage off                       7302           7308           9          1.4         730.2       1.0X
+from_unixtime wholestage on                        7298           7319          16          1.4         729.8       1.0X
 
 
 ================================================================================================
 Convert timestamps
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 from_utc_timestamp:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-from_utc_timestamp wholestage off                   801            807           9         12.5          80.1       1.0X
-from_utc_timestamp wholestage on                    819            830           7         12.2          81.9       1.0X
+from_utc_timestamp wholestage off                  1322           1355          48          7.6         132.2       1.0X
+from_utc_timestamp wholestage on                   1290           1294           5          7.8         129.0       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to_utc_timestamp:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_utc_timestamp wholestage off                    1108           1114           8          9.0         110.8       1.0X
-to_utc_timestamp wholestage on                     1067           1078          13          9.4         106.7       1.0X
+to_utc_timestamp wholestage off                    1692           1705          18          5.9         169.2       1.0X
+to_utc_timestamp wholestage on                     1653           1657           4          6.1         165.3       1.0X
 
 
 ================================================================================================
 Intervals
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 cast interval:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast interval wholestage off                        211            213           2         47.4          21.1       1.0X
-cast interval wholestage on                         185            188           3         54.1          18.5       1.1X
+cast interval wholestage off                        340            356          22         29.4          34.0       1.0X
+cast interval wholestage on                         293            296           2         34.1          29.3       1.2X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 datediff:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-datediff wholestage off                            1120           1120           1          8.9         112.0       1.0X
-datediff wholestage on                             1174           1205          19          8.5         117.4       1.0X
+datediff wholestage off                            1843           1862          28          5.4         184.3       1.0X
+datediff wholestage on                             1766           1780          16          5.7         176.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 months_between:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-months_between wholestage off                      3669           3688          26          2.7         366.9       1.0X
-months_between wholestage on                       3687           3819         181          2.7         368.7       1.0X
+months_between wholestage off                      5856           5858           2          1.7         585.6       1.0X
+months_between wholestage on                       5799           5815          14          1.7         579.9       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 window:                                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-window wholestage off                              1147           1148           1          0.9        1146.6       1.0X
-window wholestage on                              16997          17207         226          0.1       16996.7       0.1X
+window wholestage off                              2017           2147         183          0.5        2017.4       1.0X
+window wholestage on                              47789          47910          91          0.0       47788.6       0.0X
 
 
 ================================================================================================
 Truncation
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc YEAR:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YEAR wholestage off                     1824           1859          50          5.5         182.4       1.0X
-date_trunc YEAR wholestage on                      1844           1942          71          5.4         184.4       1.0X
+date_trunc YEAR wholestage off                     2689           2689           1          3.7         268.9       1.0X
+date_trunc YEAR wholestage on                      2655           2670          17          3.8         265.5       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc YYYY:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YYYY wholestage off                     1808           1815          11          5.5         180.8       1.0X
-date_trunc YYYY wholestage on                      1833           1864          49          5.5         183.3       1.0X
+date_trunc YYYY wholestage off                     2698           2700           3          3.7         269.8       1.0X
+date_trunc YYYY wholestage on                      2654           2660           6          3.8         265.4       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc YY:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YY wholestage off                       1867           1883          23          5.4         186.7       1.0X
-date_trunc YY wholestage on                        1843           1861          15          5.4         184.3       1.0X
+date_trunc YY wholestage off                       2692           2697           7          3.7         269.2       1.0X
+date_trunc YY wholestage on                        2653           2662           7          3.8         265.3       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc MON:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MON wholestage off                      1845           1858          18          5.4         184.5       1.0X
-date_trunc MON wholestage on                       1830           1893          42          5.5         183.0       1.0X
+date_trunc MON wholestage off                      2752           2756           6          3.6         275.2       1.0X
+date_trunc MON wholestage on                       2666           2675          15          3.8         266.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc MONTH:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MONTH wholestage off                    1822           1855          47          5.5         182.2       1.0X
-date_trunc MONTH wholestage on                     1832           1863          20          5.5         183.2       1.0X
+date_trunc MONTH wholestage off                    2743           2746           4          3.6         274.3       1.0X
+date_trunc MONTH wholestage on                     2667           2673           8          3.7         266.7       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc MM:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MM wholestage off                       1843           1848           7          5.4         184.3       1.0X
-date_trunc MM wholestage on                        1886           1905          14          5.3         188.6       1.0X
+date_trunc MM wholestage off                       2741           2741           1          3.6         274.1       1.0X
+date_trunc MM wholestage on                        2670           2678           7          3.7         267.0       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc DAY:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc DAY wholestage off                      1542           1545           4          6.5         154.2       1.0X
-date_trunc DAY wholestage on                       1610           1616           5          6.2         161.0       1.0X
+date_trunc DAY wholestage off                      2338           2342           6          4.3         233.8       1.0X
+date_trunc DAY wholestage on                       2269           2277           7          4.4         226.9       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc DD:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc DD wholestage off                       1521           1529          11          6.6         152.1       1.0X
-date_trunc DD wholestage on                        1595           1611          21          6.3         159.5       1.0X
+date_trunc DD wholestage off                       2324           2325           1          4.3         232.4       1.0X
+date_trunc DD wholestage on                        2270           2273           2          4.4         227.0       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc HOUR:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc HOUR wholestage off                     1496           1543          67          6.7         149.6       1.0X
-date_trunc HOUR wholestage on                      1567           1594          18          6.4         156.7       1.0X
+date_trunc HOUR wholestage off                     2325           2326           1          4.3         232.5       1.0X
+date_trunc HOUR wholestage on                      2284           2295           8          4.4         228.4       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc MINUTE:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MINUTE wholestage off                    230            230           1         43.5          23.0       1.0X
-date_trunc MINUTE wholestage on                     288            295           7         34.7          28.8       0.8X
+date_trunc MINUTE wholestage off                    407            408           0         24.5          40.7       1.0X
+date_trunc MINUTE wholestage on                     382            386           3         26.1          38.2       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc SECOND:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc SECOND wholestage off                    247            249           4         40.5          24.7       1.0X
-date_trunc SECOND wholestage on                     297            314          12         33.6          29.7       0.8X
+date_trunc SECOND wholestage off                    404            404           1         24.8          40.4       1.0X
+date_trunc SECOND wholestage on                     386            390           4         25.9          38.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc WEEK:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc WEEK wholestage off                     1786           1788           3          5.6         178.6       1.0X
-date_trunc WEEK wholestage on                      1786           1832          46          5.6         178.6       1.0X
+date_trunc WEEK wholestage off                     2693           2694           2          3.7         269.3       1.0X
+date_trunc WEEK wholestage on                      2619           2629          10          3.8         261.9       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc QUARTER:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc QUARTER wholestage off                  2319           2365          66          4.3         231.9       1.0X
-date_trunc QUARTER wholestage on                   2424           2551         182          4.1         242.4       1.0X
+date_trunc QUARTER wholestage off                  3454           3466          17          2.9         345.4       1.0X
+date_trunc QUARTER wholestage on                   3384           3404          24          3.0         338.4       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc year:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc year wholestage off                           180            189          12         55.5          18.0       1.0X
-trunc year wholestage on                            271            277           5         36.9          27.1       0.7X
+trunc year wholestage off                           339            340           1         29.5          33.9       1.0X
+trunc year wholestage on                            337            347           9         29.7          33.7       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc yyyy:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc yyyy wholestage off                           189            191           4         52.9          18.9       1.0X
-trunc yyyy wholestage on                            276            284           6         36.2          27.6       0.7X
+trunc yyyy wholestage off                           347            348           2         28.8          34.7       1.0X
+trunc yyyy wholestage on                            334            335           2         29.9          33.4       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc yy:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc yy wholestage off                             189            190           1         52.9          18.9       1.0X
-trunc yy wholestage on                              279            294          11         35.9          27.9       0.7X
+trunc yy wholestage off                             339            346          11         29.5          33.9       1.0X
+trunc yy wholestage on                              333            338           5         30.0          33.3       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc mon:                                Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc mon wholestage off                            185            186           1         54.1          18.5       1.0X
-trunc mon wholestage on                             272            285          13         36.8          27.2       0.7X
+trunc mon wholestage off                            339            347          11         29.5          33.9       1.0X
+trunc mon wholestage on                             331            336           4         30.2          33.1       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc month:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc month wholestage off                          190            190           1         52.6          19.0       1.0X
-trunc month wholestage on                           293            300           4         34.1          29.3       0.6X
+trunc month wholestage off                          341            344           3         29.3          34.1       1.0X
+trunc month wholestage on                           332            338           9         30.1          33.2       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc mm:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc mm wholestage off                             178            182           6         56.3          17.8       1.0X
-trunc mm wholestage on                              306            312           5         32.7          30.6       0.6X
+trunc mm wholestage off                             337            338           1         29.6          33.7       1.0X
+trunc mm wholestage on                              332            336           5         30.1          33.2       1.0X
 
 
 ================================================================================================
 Parsing
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to timestamp str:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to timestamp str wholestage off                     111            117           8          9.0         110.9       1.0X
-to timestamp str wholestage on                      101            109           6          9.9         100.6       1.1X
+to timestamp str wholestage off                     184            187           4          5.4         183.9       1.0X
+to timestamp str wholestage on                      159            162           2          6.3         159.4       1.2X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to_timestamp:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_timestamp wholestage off                         735            746          15          1.4         734.9       1.0X
-to_timestamp wholestage on                          708            725          11          1.4         708.2       1.0X
+to_timestamp wholestage off                        1683           1689           8          0.6        1683.3       1.0X
+to_timestamp wholestage on                         1722           1725           4          0.6        1721.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to_unix_timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_unix_timestamp wholestage off                    718            727          12          1.4         717.9       1.0X
-to_unix_timestamp wholestage on                     739            755          12          1.4         739.1       1.0X
+to_unix_timestamp wholestage off                   1733           1736           4          0.6        1733.1       1.0X
+to_unix_timestamp wholestage on                    1687           1690           4          0.6        1686.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to date str:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to date str wholestage off                          124            125           1          8.0         124.4       1.0X
-to date str wholestage on                           134            138           3          7.5         133.9       0.9X
+to date str wholestage off                          218            220           4          4.6         217.6       1.0X
+to date str wholestage on                           213            215           2          4.7         212.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to_date:                                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_date wholestage off                             1510           1544          48          0.7        1510.4       1.0X
-to_date wholestage on                              1544           1557          15          0.6        1544.2       1.0X
+to_date wholestage off                             3697           3699           2          0.3        3697.2       1.0X
+to_date wholestage on                              3603           3624          15          0.3        3602.7       1.0X
 
 
 ================================================================================================
 Conversion from/to external types
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 To/from Java's date-time:                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-From java.sql.Date                                  269            278           9         18.6          53.7       1.0X
-From java.time.LocalDate                            227            234           7         22.0          45.4       1.2X
-Collect java.sql.Date                              1164           1272         141          4.3         232.8       0.2X
-Collect java.time.LocalDate                        1070           1130          59          4.7         214.1       0.3X
-From java.sql.Timestamp                             246            248           2         20.3          49.2       1.1X
-From java.time.Instant                              214            216           2         23.4          42.8       1.3X
-Collect longs                                       814            831          15          6.1         162.7       0.3X
-Collect java.sql.Timestamp                         1016           1096          78          4.9         203.2       0.3X
-Collect java.time.Instant                          1012           1093          86          4.9         202.4       0.3X
+From java.sql.Date                                  432            436           7         11.6          86.4       1.0X
+From java.time.LocalDate                            343            347           6         14.6          68.6       1.3X
+Collect java.sql.Date                              1888           2453         971          2.6         377.6       0.2X
+Collect java.time.LocalDate                        1779           1820          42          2.8         355.7       0.2X
+From java.sql.Timestamp                             375            384           9         13.3          75.0       1.2X
+From java.time.Instant                              317            326           8         15.8          63.5       1.4X
+Collect longs                                      1338           1428         115          3.7         267.6       0.3X
+Collect java.sql.Timestamp                         1716           2014         281          2.9         343.1       0.3X
+Collect java.time.Instant                          1832           1970         122          2.7         366.5       0.2X
 
 
diff --git a/sql/core/benchmarks/DateTimeBenchmark-results.txt b/sql/core/benchmarks/DateTimeBenchmark-results.txt
index dba6c909be637..3ef2f922f95bf 100644
--- a/sql/core/benchmarks/DateTimeBenchmark-results.txt
+++ b/sql/core/benchmarks/DateTimeBenchmark-results.txt
@@ -2,456 +2,456 @@
 datetime +/- interval
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 datetime +/- interval:                    Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date + interval(m)                                 1003           1012          13          0.0   334353721.7       1.0X
-date + interval(m, d)                              1154           1174          29          0.0   384575202.7       0.9X
-date + interval(m, d, ms)                          4338           4366          40          0.0  1446002701.3       0.2X
-date - interval(m)                                  850            858           8          0.0   283424914.7       1.2X
-date - interval(m, d)                              1017           1031          19          0.0   339034354.7       1.0X
-date - interval(m, d, ms)                          4699           4717          25          0.0  1566218686.3       0.2X
-timestamp + interval(m)                            2044           2046           3          0.0   681382301.0       0.5X
-timestamp + interval(m, d)                         2215           2249          48          0.0   738464286.7       0.5X
-timestamp + interval(m, d, ms)                     2053           2063          13          0.0   684393366.0       0.5X
-timestamp - interval(m)                            1668           1677          12          0.0   556138256.7       0.6X
-timestamp - interval(m, d)                         1865           1882          25          0.0   621574795.3       0.5X
-timestamp - interval(m, d, ms)                     2075           2077           3          0.0   691569937.3       0.5X
+date + interval(m)                                 1613           1622          13          6.2         161.3       1.0X
+date + interval(m, d)                              1729           1752          32          5.8         172.9       0.9X
+date + interval(m, d, ms)                          6421           6424           5          1.6         642.1       0.3X
+date - interval(m)                                 1441           1443           2          6.9         144.1       1.1X
+date - interval(m, d)                              1687           1689           2          5.9         168.7       1.0X
+date - interval(m, d, ms)                          6617           6625          11          1.5         661.7       0.2X
+timestamp + interval(m)                            2713           2733          28          3.7         271.3       0.6X
+timestamp + interval(m, d)                         3027           3032           8          3.3         302.7       0.5X
+timestamp + interval(m, d, ms)                     3501           3509          12          2.9         350.1       0.5X
+timestamp - interval(m)                            2892           2895           4          3.5         289.2       0.6X
+timestamp - interval(m, d)                         3190           3196           9          3.1         319.0       0.5X
+timestamp - interval(m, d, ms)                     3497           3500           5          2.9         349.7       0.5X
 
 
 ================================================================================================
 Extract components
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 cast to timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast to timestamp wholestage off                    192            192           0         52.2          19.2       1.0X
-cast to timestamp wholestage on                     163            166           3         61.3          16.3       1.2X
+cast to timestamp wholestage off                    321            323           2         31.1          32.1       1.0X
+cast to timestamp wholestage on                     294            306          10         34.0          29.4       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 year of timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-year of timestamp wholestage off                    743            745           4         13.5          74.3       1.0X
-year of timestamp wholestage on                     708            715           5         14.1          70.8       1.0X
+year of timestamp wholestage off                   1235           1242           9          8.1         123.5       1.0X
+year of timestamp wholestage on                    1208           1216           8          8.3         120.8       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 quarter of timestamp:                     Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-quarter of timestamp wholestage off                 848            857          12         11.8          84.8       1.0X
-quarter of timestamp wholestage on                  803            813           6         12.5          80.3       1.1X
+quarter of timestamp wholestage off                1415           1424          12          7.1         141.5       1.0X
+quarter of timestamp wholestage on                 1338           1341           4          7.5         133.8       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 month of timestamp:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-month of timestamp wholestage off                   740            745           7         13.5          74.0       1.0X
-month of timestamp wholestage on                    703            710           5         14.2          70.3       1.1X
+month of timestamp wholestage off                  1224           1225           1          8.2         122.4       1.0X
+month of timestamp wholestage on                   1193           1202           8          8.4         119.3       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 weekofyear of timestamp:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-weekofyear of timestamp wholestage off             1162           1182          28          8.6         116.2       1.0X
-weekofyear of timestamp wholestage on              1093           1102           9          9.2         109.3       1.1X
+weekofyear of timestamp wholestage off             1864           1866           3          5.4         186.4       1.0X
+weekofyear of timestamp wholestage on              1827           1840           7          5.5         182.7       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 day of timestamp:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-day of timestamp wholestage off                     742            748           9         13.5          74.2       1.0X
-day of timestamp wholestage on                      703            713           7         14.2          70.3       1.1X
+day of timestamp wholestage off                    1209           1211           2          8.3         120.9       1.0X
+day of timestamp wholestage on                     1191           1194           6          8.4         119.1       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 dayofyear of timestamp:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofyear of timestamp wholestage off               791            799          11         12.6          79.1       1.0X
-dayofyear of timestamp wholestage on                732            744           9         13.7          73.2       1.1X
+dayofyear of timestamp wholestage off              1270           1271           2          7.9         127.0       1.0X
+dayofyear of timestamp wholestage on               1241           1250          12          8.1         124.1       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 dayofmonth of timestamp:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofmonth of timestamp wholestage off              738            752          20         13.6          73.8       1.0X
-dayofmonth of timestamp wholestage on               695            712           9         14.4          69.5       1.1X
+dayofmonth of timestamp wholestage off             1236           1250          20          8.1         123.6       1.0X
+dayofmonth of timestamp wholestage on              1193           1195           3          8.4         119.3       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 dayofweek of timestamp:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofweek of timestamp wholestage off               854            856           3         11.7          85.4       1.0X
-dayofweek of timestamp wholestage on                819            839          16         12.2          81.9       1.0X
+dayofweek of timestamp wholestage off              1402           1405           4          7.1         140.2       1.0X
+dayofweek of timestamp wholestage on               1352           1359           7          7.4         135.2       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 weekday of timestamp:                     Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-weekday of timestamp wholestage off                 816            821           7         12.3          81.6       1.0X
-weekday of timestamp wholestage on                  788            800           8         12.7          78.8       1.0X
+weekday of timestamp wholestage off                1346           1347           2          7.4         134.6       1.0X
+weekday of timestamp wholestage on                 1294           1299           7          7.7         129.4       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 hour of timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-hour of timestamp wholestage off                    595            595           1         16.8          59.5       1.0X
-hour of timestamp wholestage on                     533            541          10         18.8          53.3       1.1X
+hour of timestamp wholestage off                   1000           1008          11         10.0         100.0       1.0X
+hour of timestamp wholestage on                     936            941           6         10.7          93.6       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 minute of timestamp:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-minute of timestamp wholestage off                  585            588           4         17.1          58.5       1.0X
-minute of timestamp wholestage on                   532            545          11         18.8          53.2       1.1X
+minute of timestamp wholestage off                  969            976          10         10.3          96.9       1.0X
+minute of timestamp wholestage on                   933            936           4         10.7          93.3       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 second of timestamp:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-second of timestamp wholestage off                  579            589          13         17.3          57.9       1.0X
-second of timestamp wholestage on                   529            537           6         18.9          52.9       1.1X
+second of timestamp wholestage off                 1002           1005           3         10.0         100.2       1.0X
+second of timestamp wholestage on                   935            938           2         10.7          93.5       1.1X
 
 
 ================================================================================================
 Current date and time
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 current_date:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-current_date wholestage off                         171            174           4         58.4          17.1       1.0X
-current_date wholestage on                          152            155           3         65.6          15.2       1.1X
+current_date wholestage off                         308            316          11         32.5          30.8       1.0X
+current_date wholestage on                          265            275          12         37.8          26.5       1.2X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 current_timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-current_timestamp wholestage off                    178            181           4         56.2          17.8       1.0X
-current_timestamp wholestage on                     138            149           7         72.6          13.8       1.3X
+current_timestamp wholestage off                    307            312           7         32.6          30.7       1.0X
+current_timestamp wholestage on                     263            268           5         38.1          26.3       1.2X
 
 
 ================================================================================================
 Date arithmetic
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 cast to date:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast to date wholestage off                         630            640          14         15.9          63.0       1.0X
-cast to date wholestage on                          591            594           5         16.9          59.1       1.1X
+cast to date wholestage off                        1061           1065           5          9.4         106.1       1.0X
+cast to date wholestage on                          985            991          11         10.2          98.5       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 last_day:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-last_day wholestage off                             759            778          26         13.2          75.9       1.0X
-last_day wholestage on                              727            736           9         13.8          72.7       1.0X
+last_day wholestage off                            1261           1262           1          7.9         126.1       1.0X
+last_day wholestage on                             1223           1235          12          8.2         122.3       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 next_day:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-next_day wholestage off                             649            659          15         15.4          64.9       1.0X
-next_day wholestage on                              628            629           1         15.9          62.8       1.0X
+next_day wholestage off                            1114           1119           7          9.0         111.4       1.0X
+next_day wholestage on                             1034           1038           3          9.7         103.4       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_add:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_add wholestage off                             621            622           1         16.1          62.1       1.0X
-date_add wholestage on                              600            606           6         16.7          60.0       1.0X
+date_add wholestage off                            1059           1076          25          9.4         105.9       1.0X
+date_add wholestage on                             1012           1021           9          9.9         101.2       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_sub:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_sub wholestage off                             611            626          21         16.4          61.1       1.0X
-date_sub wholestage on                              588            600           7         17.0          58.8       1.0X
+date_sub wholestage off                            1046           1046           0          9.6         104.6       1.0X
+date_sub wholestage on                             1019           1023           3          9.8         101.9       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 add_months:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-add_months wholestage off                           843            845           2         11.9          84.3       1.0X
-add_months wholestage on                            818            831          11         12.2          81.8       1.0X
+add_months wholestage off                          1392           1393           1          7.2         139.2       1.0X
+add_months wholestage on                           1335           1346          14          7.5         133.5       1.0X
 
 
 ================================================================================================
 Formatting dates
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 format date:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-format date wholestage off                         3557           3569          18          2.8         355.7       1.0X
-format date wholestage on                          3564           3588          17          2.8         356.4       1.0X
+format date wholestage off                         5959           5994          50          1.7         595.9       1.0X
+format date wholestage on                          5991           6008          28          1.7         599.1       1.0X
 
 
 ================================================================================================
 Formatting timestamps
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 from_unixtime:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-from_unixtime wholestage off                       4875           4887          17          2.1         487.5       1.0X
-from_unixtime wholestage on                        4845           4870          16          2.1         484.5       1.0X
+from_unixtime wholestage off                       8851           8872          29          1.1         885.1       1.0X
+from_unixtime wholestage on                        8855           8872          10          1.1         885.5       1.0X
 
 
 ================================================================================================
 Convert timestamps
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 from_utc_timestamp:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-from_utc_timestamp wholestage off                   665            671           8         15.0          66.5       1.0X
-from_utc_timestamp wholestage on                    654            672          14         15.3          65.4       1.0X
+from_utc_timestamp wholestage off                  1105           1107           2          9.0         110.5       1.0X
+from_utc_timestamp wholestage on                   1072           1084          11          9.3         107.2       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to_utc_timestamp:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_utc_timestamp wholestage off                     982            983           1         10.2          98.2       1.0X
-to_utc_timestamp wholestage on                      877            889           9         11.4          87.7       1.1X
+to_utc_timestamp wholestage off                    1531           1534           3          6.5         153.1       1.0X
+to_utc_timestamp wholestage on                     1451           1463          14          6.9         145.1       1.1X
 
 
 ================================================================================================
 Intervals
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 cast interval:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast interval wholestage off                        200            206           9         50.1          20.0       1.0X
-cast interval wholestage on                         157            163           5         63.6          15.7       1.3X
+cast interval wholestage off                        360            366           8         27.8          36.0       1.0X
+cast interval wholestage on                         286            292           7         35.0          28.6       1.3X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 datediff:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-datediff wholestage off                            1065           1068           4          9.4         106.5       1.0X
-datediff wholestage on                             1028           1047          15          9.7         102.8       1.0X
+datediff wholestage off                            1809           1814           8          5.5         180.9       1.0X
+datediff wholestage on                             1742           1751           8          5.7         174.2       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 months_between:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-months_between wholestage off                      3102           3111          13          3.2         310.2       1.0X
-months_between wholestage on                       2970           3028          46          3.4         297.0       1.0X
+months_between wholestage off                      5007           5007           1          2.0         500.7       1.0X
+months_between wholestage on                       4957           4980          35          2.0         495.7       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 window:                                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-window wholestage off                              1142           1154          16          0.9        1142.2       1.0X
-window wholestage on                              14817          15049         257          0.1       14816.5       0.1X
+window wholestage off                              1945           2027         116          0.5        1945.3       1.0X
+window wholestage on                              45637          45648           8          0.0       45637.2       0.0X
 
 
 ================================================================================================
 Truncation
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc YEAR:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YEAR wholestage off                     1516           1518           2          6.6         151.6       1.0X
-date_trunc YEAR wholestage on                      1458           1468           9          6.9         145.8       1.0X
+date_trunc YEAR wholestage off                     2463           2465           2          4.1         246.3       1.0X
+date_trunc YEAR wholestage on                      2406           2409           3          4.2         240.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc YYYY:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YYYY wholestage off                     1535           1535           1          6.5         153.5       1.0X
-date_trunc YYYY wholestage on                      1453           1461           7          6.9         145.3       1.1X
+date_trunc YYYY wholestage off                     2462           2463           1          4.1         246.2       1.0X
+date_trunc YYYY wholestage on                      2407           2411           6          4.2         240.7       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc YY:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YY wholestage off                       1561           1567           9          6.4         156.1       1.0X
-date_trunc YY wholestage on                        1452           1467          16          6.9         145.2       1.1X
+date_trunc YY wholestage off                       2462           2466           6          4.1         246.2       1.0X
+date_trunc YY wholestage on                        2401           2406           4          4.2         240.1       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc MON:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MON wholestage off                      1522           1531          13          6.6         152.2       1.0X
-date_trunc MON wholestage on                       1458           1467           7          6.9         145.8       1.0X
+date_trunc MON wholestage off                      2437           2437           0          4.1         243.7       1.0X
+date_trunc MON wholestage on                       2416           2421           6          4.1         241.6       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc MONTH:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MONTH wholestage off                    1518           1519           0          6.6         151.8       1.0X
-date_trunc MONTH wholestage on                     1452           1465          16          6.9         145.2       1.0X
+date_trunc MONTH wholestage off                    2430           2437           9          4.1         243.0       1.0X
+date_trunc MONTH wholestage on                     2417           2423           5          4.1         241.7       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc MM:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MM wholestage off                       1531           1532           1          6.5         153.1       1.0X
-date_trunc MM wholestage on                        1453           1463           8          6.9         145.3       1.1X
+date_trunc MM wholestage off                       2429           2431           3          4.1         242.9       1.0X
+date_trunc MM wholestage on                        2417           2421           4          4.1         241.7       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc DAY:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc DAY wholestage off                      1287           1309          31          7.8         128.7       1.0X
-date_trunc DAY wholestage on                       1310           1337          16          7.6         131.0       1.0X
+date_trunc DAY wholestage off                      2074           2075           2          4.8         207.4       1.0X
+date_trunc DAY wholestage on                       2001           2010          16          5.0         200.1       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc DD:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc DD wholestage off                       1322           1328           9          7.6         132.2       1.0X
-date_trunc DD wholestage on                        1282           1324          28          7.8         128.2       1.0X
+date_trunc DD wholestage off                       2067           2067           0          4.8         206.7       1.0X
+date_trunc DD wholestage on                        2000           2003           3          5.0         200.0       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc HOUR:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc HOUR wholestage off                     1379           1393          20          7.3         137.9       1.0X
-date_trunc HOUR wholestage on                      1288           1302          11          7.8         128.8       1.1X
+date_trunc HOUR wholestage off                     2074           2084          14          4.8         207.4       1.0X
+date_trunc HOUR wholestage on                      2057           2067          10          4.9         205.7       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc MINUTE:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MINUTE wholestage off                    243            245           2         41.2          24.3       1.0X
-date_trunc MINUTE wholestage on                     213            219           8         47.0          21.3       1.1X
+date_trunc MINUTE wholestage off                    362            364           3         27.6          36.2       1.0X
+date_trunc MINUTE wholestage on                     319            333          14         31.3          31.9       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc SECOND:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc SECOND wholestage off                    238            245          11         42.1          23.8       1.0X
-date_trunc SECOND wholestage on                     201            210           9         49.7          20.1       1.2X
+date_trunc SECOND wholestage off                    361            366           7         27.7          36.1       1.0X
+date_trunc SECOND wholestage on                     324            341          23         30.9          32.4       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc WEEK:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc WEEK wholestage off                     1443           1477          49          6.9         144.3       1.0X
-date_trunc WEEK wholestage on                      1491           1516          17          6.7         149.1       1.0X
+date_trunc WEEK wholestage off                     2385           2393          11          4.2         238.5       1.0X
+date_trunc WEEK wholestage on                      2313           2322           6          4.3         231.3       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 date_trunc QUARTER:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc QUARTER wholestage off                  2017           2039          32          5.0         201.7       1.0X
-date_trunc QUARTER wholestage on                   1966           2005          36          5.1         196.6       1.0X
+date_trunc QUARTER wholestage off                  3278           3280           2          3.1         327.8       1.0X
+date_trunc QUARTER wholestage on                   3228           3234           8          3.1         322.8       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc year:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc year wholestage off                           206            206           1         48.6          20.6       1.0X
-trunc year wholestage on                            175            178           2         57.2          17.5       1.2X
+trunc year wholestage off                           328            331           4         30.5          32.8       1.0X
+trunc year wholestage on                            286            295           9         35.0          28.6       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc yyyy:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc yyyy wholestage off                           188            189           2         53.2          18.8       1.0X
-trunc yyyy wholestage on                            176            180           4         56.9          17.6       1.1X
+trunc yyyy wholestage off                           317            319           3         31.5          31.7       1.0X
+trunc yyyy wholestage on                            283            287           6         35.3          28.3       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc yy:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc yy wholestage off                             191            191           0         52.4          19.1       1.0X
-trunc yy wholestage on                              175            180           4         57.0          17.5       1.1X
+trunc yy wholestage off                             321            321           0         31.1          32.1       1.0X
+trunc yy wholestage on                              284            293          11         35.2          28.4       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc mon:                                Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc mon wholestage off                            203            205           3         49.3          20.3       1.0X
-trunc mon wholestage on                             183            186           2         54.8          18.3       1.1X
+trunc mon wholestage off                            318            319           1         31.4          31.8       1.0X
+trunc mon wholestage on                             283            287           4         35.4          28.3       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc month:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc month wholestage off                          199            199           0         50.3          19.9       1.0X
-trunc month wholestage on                           177            179           2         56.4          17.7       1.1X
+trunc month wholestage off                          319            321           3         31.3          31.9       1.0X
+trunc month wholestage on                           286            293           7         35.0          28.6       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 trunc mm:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc mm wholestage off                             198            198           1         50.5          19.8       1.0X
-trunc mm wholestage on                              180            183           3         55.7          18.0       1.1X
+trunc mm wholestage off                             317            319           2         31.5          31.7       1.0X
+trunc mm wholestage on                              282            285           3         35.4          28.2       1.1X
 
 
 ================================================================================================
 Parsing
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to timestamp str:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to timestamp str wholestage off                     138            139           2          7.2         138.2       1.0X
-to timestamp str wholestage on                      129            138           7          7.8         128.9       1.1X
+to timestamp str wholestage off                     219            220           0          4.6         219.4       1.0X
+to timestamp str wholestage on                      214            218           6          4.7         214.1       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to_timestamp:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_timestamp wholestage off                         885            889           5          1.1         885.3       1.0X
-to_timestamp wholestage on                          854            866          10          1.2         854.0       1.0X
+to_timestamp wholestage off                        1912           1913           2          0.5        1912.0       1.0X
+to_timestamp wholestage on                         1671           1675           7          0.6        1670.8       1.1X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to_unix_timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_unix_timestamp wholestage off                    848            856          12          1.2         848.1       1.0X
-to_unix_timestamp wholestage on                     826            850          18          1.2         826.4       1.0X
+to_unix_timestamp wholestage off                   1761           1763           3          0.6        1761.1       1.0X
+to_unix_timestamp wholestage on                    1695           1697           2          0.6        1695.4       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to date str:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to date str wholestage off                          167            171           5          6.0         167.2       1.0X
-to date str wholestage on                           165            173           4          6.1         165.0       1.0X
+to date str wholestage off                          267            272           7          3.7         266.9       1.0X
+to date str wholestage on                           266            267           2          3.8         265.8       1.0X
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 to_date:                                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_date wholestage off                             1612           1633          31          0.6        1611.7       1.0X
-to_date wholestage on                              1588           1605          19          0.6        1588.2       1.0X
+to_date wholestage off                             3705           3743          55          0.3        3704.6       1.0X
+to_date wholestage on                              3736           3746          11          0.3        3736.4       1.0X
 
 
 ================================================================================================
 Conversion from/to external types
 ================================================================================================
 
-Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
-Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 To/from Java's date-time:                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-From java.sql.Date                                  245            247           1         20.4          49.0       1.0X
-From java.time.LocalDate                            228            233           4         21.9          45.6       1.1X
-Collect java.sql.Date                              1239           1361         209          4.0         247.9       0.2X
-Collect java.time.LocalDate                        1049           1107          54          4.8         209.8       0.2X
-From java.sql.Timestamp                             247            252           4         20.2          49.5       1.0X
-From java.time.Instant                              156            158           3         32.1          31.2       1.6X
-Collect longs                                       854            910          59          5.9         170.8       0.3X
-Collect java.sql.Timestamp                         1133           1140          12          4.4         226.6       0.2X
-Collect java.time.Instant                          1108           1159          74          4.5         221.7       0.2X
+From java.sql.Date                                  400            406           6         12.5          80.1       1.0X
+From java.time.LocalDate                            343            349           7         14.6          68.6       1.2X
+Collect java.sql.Date                              1904           2739        1170          2.6         380.9       0.2X
+Collect java.time.LocalDate                        1477           1495          19          3.4         295.3       0.3X
+From java.sql.Timestamp                             376            388          10         13.3          75.2       1.1X
+From java.time.Instant                              237            239           3         21.1          47.4       1.7X
+Collect longs                                      1258           1356         111          4.0         251.7       0.3X
+Collect java.sql.Timestamp                         1878           1937          64          2.7         375.6       0.2X
+Collect java.time.Instant                          1667           1904         238          3.0         333.4       0.2X
 
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeBenchmark.scala
index 0034819b58893..f56efa3bba600 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeBenchmark.scala
@@ -61,7 +61,7 @@ object DateTimeBenchmark extends SqlBasedBenchmark {
       withSQLConf(SQLConf.SESSION_LOCAL_TIMEZONE.key -> LA.getId) {
         val N = 10000000
         runBenchmark("datetime +/- interval") {
-          val benchmark = new Benchmark("datetime +/- interval", 3, output = output)
+          val benchmark = new Benchmark("datetime +/- interval", N, output = output)
           val ts = "cast(id as timestamp)"
           val dt = s"cast($ts as date)"
           benchmark.addCase("date + interval(m)") { _ =>

From da32137d37d032a3fd2507b229e3f494cc612246 Mon Sep 17 00:00:00 2001
From: Tianshi Zhu <zhutianshirea@gmail.com>
Date: Mon, 4 May 2020 14:50:38 +0900
Subject: [PATCH 07/19] [SPARK-31267][SQL] Flaky test:
 WholeStageCodegenSparkSubmitSuite.Generated code on driver should not embed
 platform-specific constant

### What changes were proposed in this pull request?

Allow customized timeouts for `runSparkSubmit`, which will make flaky tests more likely to pass by using a larger timeout value.

I was able to reproduce the test failure on my laptop, which took 1.5 - 2 minutes to finish the test. After increasing the timeout, the test now can pass locally.

### Why are the changes needed?

This allows slow tests to use a larger timeout, so they are more likely to succeed.

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

The test was able to pass on my local env after the change.

Closes #28438 from tianshizz/SPARK-31267.

Authored-by: Tianshi Zhu <zhutianshirea@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
---
 .../scala/org/apache/spark/deploy/SparkSubmitSuite.scala     | 5 +++--
 .../sql/execution/WholeStageCodegenSparkSubmitSuite.scala    | 3 ++-
 2 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala
index 1f3243400a918..fd2d1f56ed9b6 100644
--- a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala
@@ -31,6 +31,7 @@ import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.fs.{FileStatus, FSDataInputStream, Path}
 import org.scalatest.{BeforeAndAfterEach, Matchers}
 import org.scalatest.concurrent.{Signaler, ThreadSignaler, TimeLimits}
+import org.scalatest.time.Span
 import org.scalatest.time.SpanSugar._
 
 import org.apache.spark._
@@ -1419,7 +1420,7 @@ object SparkSubmitSuite extends SparkFunSuite with TimeLimits {
   implicit val defaultSignaler: Signaler = ThreadSignaler
 
   // NOTE: This is an expensive operation in terms of time (10 seconds+). Use sparingly.
-  def runSparkSubmit(args: Seq[String], root: String = ".."): Unit = {
+  def runSparkSubmit(args: Seq[String], root: String = "..", timeout: Span = 1.minute): Unit = {
     val sparkHome = sys.props.getOrElse("spark.test.home", fail("spark.test.home is not set!"))
     val sparkSubmitFile = if (Utils.isWindows) {
       new File(s"$root\\bin\\spark-submit.cmd")
@@ -1432,7 +1433,7 @@ object SparkSubmitSuite extends SparkFunSuite with TimeLimits {
       Map("SPARK_TESTING" -> "1", "SPARK_HOME" -> sparkHome))
 
     try {
-      val exitCode = failAfter(1.minute) { process.waitFor() }
+      val exitCode = failAfter(timeout) { process.waitFor() }
       if (exitCode != 0) {
         fail(s"Process returned with exit code $exitCode. See the log4j logs for more detail.")
       }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSparkSubmitSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSparkSubmitSuite.scala
index f6814d8ff8a3d..c5a01de911962 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSparkSubmitSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSparkSubmitSuite.scala
@@ -19,6 +19,7 @@ package org.apache.spark.sql.execution
 
 import org.scalatest.{Assertions, BeforeAndAfterEach, Matchers}
 import org.scalatest.concurrent.TimeLimits
+import org.scalatest.time.SpanSugar._
 
 import org.apache.spark.{SparkFunSuite, TestUtils}
 import org.apache.spark.deploy.SparkSubmitSuite
@@ -50,7 +51,7 @@ class WholeStageCodegenSparkSubmitSuite extends SparkFunSuite
       "--conf", "spark.executor.extraJavaOptions=-XX:+UseCompressedOops",
       "--conf", "spark.sql.adaptive.enabled=false",
       unusedJar.toString)
-    SparkSubmitSuite.runSparkSubmit(argsForSparkSubmit, "../..")
+    SparkSubmitSuite.runSparkSubmit(argsForSparkSubmit, "../..", 3.minutes)
   }
 }
 

From 065871c30f8d505125f5197aa8ce6691ee8af92b Mon Sep 17 00:00:00 2001
From: Yuming Wang <yumwang@ebay.com>
Date: Mon, 4 May 2020 14:59:33 +0900
Subject: [PATCH 08/19] [SPARK-31626][SQL] Port HIVE-10415:
 hive.start.cleanup.scratchdir configuration is not taking effect

### What changes were proposed in this pull request?
This pr port [HIVE-10415](https://issues.apache.org/jira/browse/HIVE-10415): `hive.start.cleanup.scratchdir` configuration is not taking effect.

### Why are the changes needed?

I encountered this issue:
![image](https://user-images.githubusercontent.com/5399861/80869375-aeafd080-8cd2-11ea-8573-93ec4b422be1.png)
I'd like to make `hive.start.cleanup.scratchdir` effective to reduce this issue.

### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
Unit test

Closes #28436 from wangyum/SPARK-31626.

Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
---
 .../hive/thriftserver/HiveThriftServer2.scala |  3 ++
 .../HiveThriftServer2Suites.scala             | 33 +++++++++++++++++++
 2 files changed, 36 insertions(+)

diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala
index f15193b0dc3cc..f9f2ceeed8a75 100644
--- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala
+++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala
@@ -20,6 +20,7 @@ package org.apache.spark.sql.hive.thriftserver
 import java.util.Locale
 import java.util.concurrent.atomic.AtomicBoolean
 
+import org.apache.hadoop.hive.common.ServerUtils
 import org.apache.hadoop.hive.conf.HiveConf
 import org.apache.hadoop.hive.conf.HiveConf.ConfVars
 import org.apache.hive.service.cli.thrift.{ThriftBinaryCLIService, ThriftHttpCLIService}
@@ -101,6 +102,8 @@ object HiveThriftServer2 extends Logging {
       SparkSQLEnv.sqlContext.sessionState.newHadoopConf())
 
     try {
+      // Cleanup the scratch dir before starting
+      ServerUtils.cleanUpScratchDir(executionHive.conf)
       val server = new HiveThriftServer2(SparkSQLEnv.sqlContext)
       server.init(executionHive.conf)
       server.start()
diff --git a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
index 639dc4d13f673..0cec63460814c 100644
--- a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
+++ b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
@@ -924,6 +924,39 @@ class SingleSessionSuite extends HiveThriftJdbcTest {
   }
 }
 
+class HiveThriftCleanUpScratchDirSuite extends HiveThriftJdbcTest{
+  var tempScratchDir: File = _
+
+  override protected def beforeAll(): Unit = {
+    tempScratchDir = Utils.createTempDir()
+    tempScratchDir.setWritable(true, false)
+    assert(tempScratchDir.list().isEmpty)
+    new File(tempScratchDir.getAbsolutePath + File.separator + "SPARK-31626").createNewFile()
+    assert(tempScratchDir.list().nonEmpty)
+    super.beforeAll()
+  }
+
+  override def mode: ServerMode.Value = ServerMode.binary
+
+  override protected def extraConf: Seq[String] =
+    s" --hiveconf ${ConfVars.HIVE_START_CLEANUP_SCRATCHDIR}=true " ::
+       s"--hiveconf ${ConfVars.SCRATCHDIR}=${tempScratchDir.getAbsolutePath}" :: Nil
+
+  test("Cleanup the Hive scratchdir when starting the Hive Server") {
+    assert(!tempScratchDir.exists())
+    withJdbcStatement() { statement =>
+      val rs = statement.executeQuery("SELECT id FROM range(1)")
+      assert(rs.next())
+      assert(rs.getLong(1) === 0L)
+    }
+  }
+
+  override protected def afterAll(): Unit = {
+    Utils.deleteRecursively(tempScratchDir)
+    super.afterAll()
+  }
+}
+
 class HiveThriftHttpServerSuite extends HiveThriftJdbcTest {
   override def mode: ServerMode.Value = ServerMode.http
 

From 931c0bcd95087716c633eb9fd065d580a1d47353 Mon Sep 17 00:00:00 2001
From: Wenchen Fan <wenchen@databricks.com>
Date: Mon, 4 May 2020 15:30:10 +0900
Subject: [PATCH 09/19] [SPARK-31606][SQL] Reduce the perf regression of
 vectorized parquet reader caused by datetime rebase

### What changes were proposed in this pull request?

Push the rebase logic to the lower level of the parquet vectorized reader, to make the final code more vectorization-friendly.

### Why are the changes needed?

Parquet vectorized reader is carefully implemented, to make it more likely to be vectorized by the JVM. However, the newly added datetime rebase degrade the performance a lot, as it breaks vectorization, even if the datetime values don't need to rebase (this is very likely as dates before 1582 is rare).

### Does this PR introduce any user-facing change?

no

### How was this patch tested?

Run part of the `DateTimeRebaseBenchmark` locally. The results:
before this patch
```
[info] Load dates from parquet:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
[info] ------------------------------------------------------------------------------------------------------------------------
[info] after 1582, vec on, rebase off                     2677           2838         142         37.4          26.8       1.0X
[info] after 1582, vec on, rebase on                      3828           4331         805         26.1          38.3       0.7X
[info] before 1582, vec on, rebase off                    2903           2926          34         34.4          29.0       0.9X
[info] before 1582, vec on, rebase on                     4163           4197          38         24.0          41.6       0.6X

[info] Load timestamps from parquet:             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
[info] ------------------------------------------------------------------------------------------------------------------------
[info] after 1900, vec on, rebase off                     3537           3627         104         28.3          35.4       1.0X
[info] after 1900, vec on, rebase on                      6891           7010         105         14.5          68.9       0.5X
[info] before 1900, vec on, rebase off                    3692           3770          72         27.1          36.9       1.0X
[info] before 1900, vec on, rebase on                     7588           7610          30         13.2          75.9       0.5X
```

After this patch
```
[info] Load dates from parquet:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
[info] ------------------------------------------------------------------------------------------------------------------------
[info] after 1582, vec on, rebase off                     2758           2944         197         36.3          27.6       1.0X
[info] after 1582, vec on, rebase on                      2908           2966          51         34.4          29.1       0.9X
[info] before 1582, vec on, rebase off                    2840           2878          37         35.2          28.4       1.0X
[info] before 1582, vec on, rebase on                     3407           3433          24         29.4          34.1       0.8X

[info] Load timestamps from parquet:             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
[info] ------------------------------------------------------------------------------------------------------------------------
[info] after 1900, vec on, rebase off                     3861           4003         139         25.9          38.6       1.0X
[info] after 1900, vec on, rebase on                      4194           4283          77         23.8          41.9       0.9X
[info] before 1900, vec on, rebase off                    3849           3937          79         26.0          38.5       1.0X
[info] before 1900, vec on, rebase on                     7512           7546          55         13.3          75.1       0.5X
```

Date type is 30% faster if the values don't need to rebase, 20% faster if need to rebase.
Timestamp type is 60% faster if the values don't need to rebase, no difference if need to rebase.

Closes #28406 from cloud-fan/perf.

Lead-authored-by: Wenchen Fan <wenchen@databricks.com>
Co-authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
---
 .../sql/catalyst/util/RebaseDateTime.scala    |   4 +
 .../DateTimeRebaseBenchmark-jdk11-results.txt | 104 +++++++++---------
 .../DateTimeRebaseBenchmark-results.txt       | 104 +++++++++---------
 .../parquet/VectorizedColumnReader.java       |  22 +---
 .../parquet/VectorizedPlainValuesReader.java  |  55 +++++++++
 .../parquet/VectorizedRleValuesReader.java    |  85 ++++++++++++++
 .../parquet/VectorizedValuesReader.java       |   2 +
 .../benchmark/DateTimeRebaseBenchmark.scala   |  79 ++++++-------
 8 files changed, 295 insertions(+), 160 deletions(-)

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/RebaseDateTime.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/RebaseDateTime.scala
index 6848b0fa39c7c..040a97a14d451 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/RebaseDateTime.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/RebaseDateTime.scala
@@ -71,6 +71,8 @@ object RebaseDateTime {
     -719164, -682945, -646420, -609895, -536845, -500320, -463795,
     -390745, -354220, -317695, -244645, -208120, -171595, -141427)
 
+  final val lastSwitchJulianDay: Int = julianGregDiffSwitchDay.last
+
   // The first days of Common Era (CE) which is mapped to the '0001-01-01' date in Julian calendar.
   private final val julianCommonEraStartDay = julianGregDiffSwitchDay(0)
 
@@ -416,6 +418,8 @@ object RebaseDateTime {
   // in the interval: [julianGregDiffSwitchMicros(i), julianGregDiffSwitchMicros(i+1))
   private val julianGregRebaseMap = loadRebaseRecords("julian-gregorian-rebase-micros.json")
 
+  final val lastSwitchJulianTs: Long = julianGregRebaseMap.values.map(_.switches.last).max
+
   /**
    * An optimized version of [[rebaseJulianToGregorianMicros(ZoneId, Long)]]. This method leverages
    * the pre-calculated rebasing maps to save calculation. If the rebasing map doesn't contain
diff --git a/sql/core/benchmarks/DateTimeRebaseBenchmark-jdk11-results.txt b/sql/core/benchmarks/DateTimeRebaseBenchmark-jdk11-results.txt
index 2a9322a4b462a..03e0d7b8bc575 100644
--- a/sql/core/benchmarks/DateTimeRebaseBenchmark-jdk11-results.txt
+++ b/sql/core/benchmarks/DateTimeRebaseBenchmark-jdk11-results.txt
@@ -2,93 +2,93 @@
 Rebasing dates/timestamps in Parquet datasource
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save dates to parquet:                    Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                  21171          21171           0          4.7         211.7       1.0X
-before 1582, noop                                 11036          11036           0          9.1         110.4       1.9X
-after 1582, rebase off                            34321          34321           0          2.9         343.2       0.6X
-after 1582, rebase on                             33269          33269           0          3.0         332.7       0.6X
-before 1582, rebase off                           22016          22016           0          4.5         220.2       1.0X
-before 1582, rebase on                            23338          23338           0          4.3         233.4       0.9X
+after 1582, noop                                  20073          20073           0          5.0         200.7       1.0X
+before 1582, noop                                 10985          10985           0          9.1         109.9       1.8X
+after 1582, rebase off                            32245          32245           0          3.1         322.4       0.6X
+after 1582, rebase on                             31434          31434           0          3.2         314.3       0.6X
+before 1582, rebase off                           21590          21590           0          4.6         215.9       0.9X
+before 1582, rebase on                            22963          22963           0          4.4         229.6       0.9X
 
-OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load dates from parquet:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off, rebase off                   12791          13089         287          7.8         127.9       1.0X
-after 1582, vec off, rebase on                    13203          13271          81          7.6         132.0       1.0X
-after 1582, vec on, rebase off                     3709           3764          49         27.0          37.1       3.4X
-after 1582, vec on, rebase on                      5082           5114          29         19.7          50.8       2.5X
-before 1582, vec off, rebase off                  13059          13153          87          7.7         130.6       1.0X
-before 1582, vec off, rebase on                   14211          14236          27          7.0         142.1       0.9X
-before 1582, vec on, rebase off                    3687           3749          72         27.1          36.9       3.5X
-before 1582, vec on, rebase on                     5449           5497          56         18.4          54.5       2.3X
+after 1582, vec off, rebase off                   12815          12858          40          7.8         128.1       1.0X
+after 1582, vec off, rebase on                    13030          13167         148          7.7         130.3       1.0X
+after 1582, vec on, rebase off                     3705           3712           6         27.0          37.1       3.5X
+after 1582, vec on, rebase on                      3788           3791           3         26.4          37.9       3.4X
+before 1582, vec off, rebase off                  12873          12943          61          7.8         128.7       1.0X
+before 1582, vec off, rebase on                   14072          14165          80          7.1         140.7       0.9X
+before 1582, vec on, rebase off                    3694           3708          15         27.1          36.9       3.5X
+before 1582, vec on, rebase on                     4403           4484          81         22.7          44.0       2.9X
 
-OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save timestamps to parquet:               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                   2831           2831           0         35.3          28.3       1.0X
-before 1582, noop                                  2816           2816           0         35.5          28.2       1.0X
-after 1582, rebase off                            15543          15543           0          6.4         155.4       0.2X
-after 1582, rebase on                             18391          18391           0          5.4         183.9       0.2X
-before 1582, rebase off                           15747          15747           0          6.4         157.5       0.2X
-before 1582, rebase on                            18846          18846           0          5.3         188.5       0.2X
+after 1900, noop                                   3032           3032           0         33.0          30.3       1.0X
+before 1900, noop                                  3043           3043           0         32.9          30.4       1.0X
+after 1900, rebase off                            15634          15634           0          6.4         156.3       0.2X
+after 1900, rebase on                             18233          18233           0          5.5         182.3       0.2X
+before 1900, rebase off                           15820          15820           0          6.3         158.2       0.2X
+before 1900, rebase on                            19921          19921           0          5.0         199.2       0.2X
 
-OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load timestamps from parquet:             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off, rebase off                   16126          16216          78          6.2         161.3       1.0X
-after 1582, vec off, rebase on                    18277          18453         165          5.5         182.8       0.9X
-after 1582, vec on, rebase off                     5030           5067          42         19.9          50.3       3.2X
-after 1582, vec on, rebase on                      8553           8583          43         11.7          85.5       1.9X
-before 1582, vec off, rebase off                  15828          15872          39          6.3         158.3       1.0X
-before 1582, vec off, rebase on                   18899          18959         103          5.3         189.0       0.9X
-before 1582, vec on, rebase off                    4961           5009          43         20.2          49.6       3.3X
-before 1582, vec on, rebase on                     9099           9140          40         11.0          91.0       1.8X
+after 1900, vec off, rebase off                   14987          15008          18          6.7         149.9       1.0X
+after 1900, vec off, rebase on                    17500          17628         210          5.7         175.0       0.9X
+after 1900, vec on, rebase off                     5030           5036           7         19.9          50.3       3.0X
+after 1900, vec on, rebase on                      5066           5109          44         19.7          50.7       3.0X
+before 1900, vec off, rebase off                  15094          15213         121          6.6         150.9       1.0X
+before 1900, vec off, rebase on                   18098          18175         101          5.5         181.0       0.8X
+before 1900, vec on, rebase off                    5008           5012           4         20.0          50.1       3.0X
+before 1900, vec on, rebase on                     8803           8848          55         11.4          88.0       1.7X
 
 
 ================================================================================================
 Rebasing dates/timestamps in ORC datasource
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save dates to ORC:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                  21026          21026           0          4.8         210.3       1.0X
-before 1582, noop                                 11040          11040           0          9.1         110.4       1.9X
-after 1582                                        28171          28171           0          3.5         281.7       0.7X
-before 1582                                       18955          18955           0          5.3         189.5       1.1X
+after 1582, noop                                  19593          19593           0          5.1         195.9       1.0X
+before 1582, noop                                 10581          10581           0          9.5         105.8       1.9X
+after 1582                                        27843          27843           0          3.6         278.4       0.7X
+before 1582                                       19435          19435           0          5.1         194.4       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load dates from ORC:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off                               10876          10931          49          9.2         108.8       1.0X
-after 1582, vec on                                 3900           3913          20         25.6          39.0       2.8X
-before 1582, vec off                              11165          11174          12          9.0         111.6       1.0X
-before 1582, vec on                                4208           4214           7         23.8          42.1       2.6X
+after 1582, vec off                               10395          10507         119          9.6         103.9       1.0X
+after 1582, vec on                                 3921           3945          22         25.5          39.2       2.7X
+before 1582, vec off                              10762          10860         127          9.3         107.6       1.0X
+before 1582, vec on                                4194           4226          41         23.8          41.9       2.5X
 
-OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save timestamps to ORC:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                   2924           2924           0         34.2          29.2       1.0X
-before 1582, noop                                  2820           2820           0         35.5          28.2       1.0X
-after 1582                                        22228          22228           0          4.5         222.3       0.1X
-before 1582                                       22590          22590           0          4.4         225.9       0.1X
+after 1900, noop                                   3003           3003           0         33.3          30.0       1.0X
+before 1900, noop                                  3016           3016           0         33.2          30.2       1.0X
+after 1900                                        21804          21804           0          4.6         218.0       0.1X
+before 1900                                       23920          23920           0          4.2         239.2       0.1X
 
-OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load timestamps from ORC:                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off                               13591          13658          59          7.4         135.9       1.0X
-after 1582, vec on                                 7399           7488         126         13.5          74.0       1.8X
-before 1582, vec off                              14065          14096          30          7.1         140.7       1.0X
-before 1582, vec on                                7950           8127         249         12.6          79.5       1.7X
+after 1900, vec off                               14112          14128          17          7.1         141.1       1.0X
+after 1900, vec on                                 7347           7459         134         13.6          73.5       1.9X
+before 1900, vec off                              15170          15192          27          6.6         151.7       0.9X
+before 1900, vec on                                8280           8312          52         12.1          82.8       1.7X
 
 
diff --git a/sql/core/benchmarks/DateTimeRebaseBenchmark-results.txt b/sql/core/benchmarks/DateTimeRebaseBenchmark-results.txt
index 050950571511d..a32a1ad8af89e 100644
--- a/sql/core/benchmarks/DateTimeRebaseBenchmark-results.txt
+++ b/sql/core/benchmarks/DateTimeRebaseBenchmark-results.txt
@@ -2,93 +2,93 @@
 Rebasing dates/timestamps in Parquet datasource
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save dates to parquet:                    Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                  24114          24114           0          4.1         241.1       1.0X
-before 1582, noop                                 10250          10250           0          9.8         102.5       2.4X
-after 1582, rebase off                            36672          36672           0          2.7         366.7       0.7X
-after 1582, rebase on                             37123          37123           0          2.7         371.2       0.6X
-before 1582, rebase off                           21925          21925           0          4.6         219.2       1.1X
-before 1582, rebase on                            22341          22341           0          4.5         223.4       1.1X
+after 1582, noop                                  23088          23088           0          4.3         230.9       1.0X
+before 1582, noop                                 10782          10782           0          9.3         107.8       2.1X
+after 1582, rebase off                            34821          34821           0          2.9         348.2       0.7X
+after 1582, rebase on                             35040          35040           0          2.9         350.4       0.7X
+before 1582, rebase off                           22151          22151           0          4.5         221.5       1.0X
+before 1582, rebase on                            24677          24677           0          4.1         246.8       0.9X
 
-OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load dates from parquet:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off, rebase off                   12456          12601         126          8.0         124.6       1.0X
-after 1582, vec off, rebase on                    13299          13336          32          7.5         133.0       0.9X
-after 1582, vec on, rebase off                     3623           3660          40         27.6          36.2       3.4X
-after 1582, vec on, rebase on                      5160           5177          15         19.4          51.6       2.4X
-before 1582, vec off, rebase off                  13177          13264          76          7.6         131.8       0.9X
-before 1582, vec off, rebase on                   14102          14149          46          7.1         141.0       0.9X
-before 1582, vec on, rebase off                    3649           3670          34         27.4          36.5       3.4X
-before 1582, vec on, rebase on                     5652           5667          15         17.7          56.5       2.2X
+after 1582, vec off, rebase off                   13559          13650          79          7.4         135.6       1.0X
+after 1582, vec off, rebase on                    12942          12973          28          7.7         129.4       1.0X
+after 1582, vec on, rebase off                     3657           3689          29         27.3          36.6       3.7X
+after 1582, vec on, rebase on                      3859           3902          53         25.9          38.6       3.5X
+before 1582, vec off, rebase off                  12588          12607          17          7.9         125.9       1.1X
+before 1582, vec off, rebase on                   13396          13420          25          7.5         134.0       1.0X
+before 1582, vec on, rebase off                    3631           3650          19         27.5          36.3       3.7X
+before 1582, vec on, rebase on                     4706           4755          77         21.3          47.1       2.9X
 
-OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save timestamps to parquet:               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                   2871           2871           0         34.8          28.7       1.0X
-before 1582, noop                                  2753           2753           0         36.3          27.5       1.0X
-after 1582, rebase off                            15927          15927           0          6.3         159.3       0.2X
-after 1582, rebase on                             19138          19138           0          5.2         191.4       0.1X
-before 1582, rebase off                           16137          16137           0          6.2         161.4       0.2X
-before 1582, rebase on                            19584          19584           0          5.1         195.8       0.1X
+after 1900, noop                                   2681           2681           0         37.3          26.8       1.0X
+before 1900, noop                                  3051           3051           0         32.8          30.5       0.9X
+after 1900, rebase off                            16901          16901           0          5.9         169.0       0.2X
+after 1900, rebase on                             19725          19725           0          5.1         197.3       0.1X
+before 1900, rebase off                           16900          16900           0          5.9         169.0       0.2X
+before 1900, rebase on                            20381          20381           0          4.9         203.8       0.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load timestamps from parquet:             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off, rebase off                   14995          15047          47          6.7         150.0       1.0X
-after 1582, vec off, rebase on                    18111          18146          37          5.5         181.1       0.8X
-after 1582, vec on, rebase off                     4837           4873          44         20.7          48.4       3.1X
-after 1582, vec on, rebase on                      9542           9669         111         10.5          95.4       1.6X
-before 1582, vec off, rebase off                  14993          15090          94          6.7         149.9       1.0X
-before 1582, vec off, rebase on                   18675          18712          64          5.4         186.7       0.8X
-before 1582, vec on, rebase off                    4908           4923          15         20.4          49.1       3.1X
-before 1582, vec on, rebase on                    10128          10148          19          9.9         101.3       1.5X
+after 1900, vec off, rebase off                   15236          15291          62          6.6         152.4       1.0X
+after 1900, vec off, rebase on                    17832          18047         187          5.6         178.3       0.9X
+after 1900, vec on, rebase off                     4875           4901          31         20.5          48.7       3.1X
+after 1900, vec on, rebase on                      5354           5386          37         18.7          53.5       2.8X
+before 1900, vec off, rebase off                  15229          15338         108          6.6         152.3       1.0X
+before 1900, vec off, rebase on                   18626          18668          44          5.4         186.3       0.8X
+before 1900, vec on, rebase off                    4968           4975           6         20.1          49.7       3.1X
+before 1900, vec on, rebase on                     9913           9932          16         10.1          99.1       1.5X
 
 
 ================================================================================================
 Rebasing dates/timestamps in ORC datasource
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save dates to ORC:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                  23977          23977           0          4.2         239.8       1.0X
-before 1582, noop                                 10094          10094           0          9.9         100.9       2.4X
-after 1582                                        33115          33115           0          3.0         331.2       0.7X
-before 1582                                       19430          19430           0          5.1         194.3       1.2X
+after 1582, noop                                  22942          22942           0          4.4         229.4       1.0X
+before 1582, noop                                 11035          11035           0          9.1         110.4       2.1X
+after 1582                                        31341          31341           0          3.2         313.4       0.7X
+before 1582                                       20376          20376           0          4.9         203.8       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load dates from ORC:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off                               10217          10241          21          9.8         102.2       1.0X
-after 1582, vec on                                 3671           3691          31         27.2          36.7       2.8X
-before 1582, vec off                              10800          10874         114          9.3         108.0       0.9X
-before 1582, vec on                                4118           4165          74         24.3          41.2       2.5X
+after 1582, vec off                               10361          10378          29          9.7         103.6       1.0X
+after 1582, vec on                                 3820           3828          11         26.2          38.2       2.7X
+before 1582, vec off                              10709          10720          13          9.3         107.1       1.0X
+before 1582, vec on                                4136           4153          15         24.2          41.4       2.5X
 
-OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save timestamps to ORC:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                   2691           2691           0         37.2          26.9       1.0X
-before 1582, noop                                  2743           2743           0         36.5          27.4       1.0X
-after 1582                                        21409          21409           0          4.7         214.1       0.1X
-before 1582                                       22554          22554           0          4.4         225.5       0.1X
+after 1900, noop                                   2888           2888           0         34.6          28.9       1.0X
+before 1900, noop                                  2823           2823           0         35.4          28.2       1.0X
+after 1900                                        19790          19790           0          5.1         197.9       0.1X
+before 1900                                       20774          20774           0          4.8         207.7       0.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load timestamps from ORC:                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off                               14752          14855         103          6.8         147.5       1.0X
-after 1582, vec on                                 8146           8185          34         12.3          81.5       1.8X
-before 1582, vec off                              15247          15294          46          6.6         152.5       1.0X
-before 1582, vec on                                8414           8466          52         11.9          84.1       1.8X
+after 1900, vec off                               14649          14687          38          6.8         146.5       1.0X
+after 1900, vec on                                 7850           7937         130         12.7          78.5       1.9X
+before 1900, vec off                              15354          15417         108          6.5         153.5       1.0X
+before 1900, vec on                                8382           8408          22         11.9          83.8       1.7X
 
 
diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
index cfb873ff37379..7ae60f22aa790 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
@@ -423,15 +423,8 @@ private void readIntBatch(int rowId, int num, WritableColumnVector column) throw
           num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
     } else if (column.dataType() == DataTypes.DateType ) {
       if (rebaseDateTime) {
-        for (int i = 0; i < num; i++) {
-          if (defColumn.readInteger() == maxDefLevel) {
-            column.putInt(
-              rowId + i,
-              RebaseDateTime.rebaseJulianToGregorianDays(dataColumn.readInteger()));
-          } else {
-            column.putNull(rowId + i);
-          }
-        }
+        defColumn.readIntegersWithRebase(
+          num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
       } else {
         defColumn.readIntegers(
            num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
@@ -449,15 +442,8 @@ private void readLongBatch(int rowId, int num, WritableColumnVector column) thro
         num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
     } else if (originalType == OriginalType.TIMESTAMP_MICROS) {
       if (rebaseDateTime) {
-        for (int i = 0; i < num; i++) {
-          if (defColumn.readInteger() == maxDefLevel) {
-            column.putLong(
-              rowId + i,
-              RebaseDateTime.rebaseJulianToGregorianMicros(dataColumn.readLong()));
-          } else {
-            column.putNull(rowId + i);
-          }
-        }
+        defColumn.readLongsWithRebase(
+          num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
       } else {
         defColumn.readLongs(
           num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedPlainValuesReader.java b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedPlainValuesReader.java
index c62dc3d86386e..2ed2e11b60c03 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedPlainValuesReader.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedPlainValuesReader.java
@@ -22,6 +22,7 @@
 
 import org.apache.parquet.bytes.ByteBufferInputStream;
 import org.apache.parquet.io.ParquetDecodingException;
+import org.apache.spark.sql.catalyst.util.RebaseDateTime;
 import org.apache.spark.sql.execution.vectorized.WritableColumnVector;
 
 import org.apache.parquet.column.values.ValuesReader;
@@ -81,6 +82,33 @@ public final void readIntegers(int total, WritableColumnVector c, int rowId) {
     }
   }
 
+  // A fork of `readIntegers` to rebase the date values. For performance reasons, this method
+  // iterates the values twice: check if we need to rebase first, then go to the optimized branch
+  // if rebase is not needed.
+  @Override
+  public final void readIntegersWithRebase(int total, WritableColumnVector c, int rowId) {
+    int requiredBytes = total * 4;
+    ByteBuffer buffer = getBuffer(requiredBytes);
+    boolean rebase = false;
+    for (int i = 0; i < total; i += 1) {
+      rebase |= buffer.getInt(buffer.position() + i * 4) < RebaseDateTime.lastSwitchJulianDay();
+    }
+    if (rebase) {
+      for (int i = 0; i < total; i += 1) {
+        c.putInt(rowId + i, RebaseDateTime.rebaseJulianToGregorianDays(buffer.getInt()));
+      }
+    } else {
+      if (buffer.hasArray()) {
+        int offset = buffer.arrayOffset() + buffer.position();
+        c.putIntsLittleEndian(rowId, total, buffer.array(), offset);
+      } else {
+        for (int i = 0; i < total; i += 1) {
+          c.putInt(rowId + i, buffer.getInt());
+        }
+      }
+    }
+  }
+
   @Override
   public final void readLongs(int total, WritableColumnVector c, int rowId) {
     int requiredBytes = total * 8;
@@ -96,6 +124,33 @@ public final void readLongs(int total, WritableColumnVector c, int rowId) {
     }
   }
 
+  // A fork of `readLongs` to rebase the timestamp values. For performance reasons, this method
+  // iterates the values twice: check if we need to rebase first, then go to the optimized branch
+  // if rebase is not needed.
+  @Override
+  public final void readLongsWithRebase(int total, WritableColumnVector c, int rowId) {
+    int requiredBytes = total * 8;
+    ByteBuffer buffer = getBuffer(requiredBytes);
+    boolean rebase = false;
+    for (int i = 0; i < total; i += 1) {
+      rebase |= buffer.getLong(buffer.position() + i * 8) < RebaseDateTime.lastSwitchJulianTs();
+    }
+    if (rebase) {
+      for (int i = 0; i < total; i += 1) {
+        c.putLong(rowId + i, RebaseDateTime.rebaseJulianToGregorianMicros(buffer.getLong()));
+      }
+    } else {
+      if (buffer.hasArray()) {
+        int offset = buffer.arrayOffset() + buffer.position();
+        c.putLongsLittleEndian(rowId, total, buffer.array(), offset);
+      } else {
+        for (int i = 0; i < total; i += 1) {
+          c.putLong(rowId + i, buffer.getLong());
+        }
+      }
+    }
+  }
+
   @Override
   public final void readFloats(int total, WritableColumnVector c, int rowId) {
     int requiredBytes = total * 4;
diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedRleValuesReader.java b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedRleValuesReader.java
index fe3d31ae8e746..4d72a33fcf774 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedRleValuesReader.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedRleValuesReader.java
@@ -26,6 +26,7 @@
 import org.apache.parquet.io.ParquetDecodingException;
 import org.apache.parquet.io.api.Binary;
 
+import org.apache.spark.sql.catalyst.util.RebaseDateTime;
 import org.apache.spark.sql.execution.vectorized.WritableColumnVector;
 
 import java.io.IOException;
@@ -203,6 +204,43 @@ public void readIntegers(
     }
   }
 
+  // A fork of `readIntegers`, which rebases the date int value (days) before filling
+  // the Spark column vector.
+  public void readIntegersWithRebase(
+      int total,
+      WritableColumnVector c,
+      int rowId,
+      int level,
+      VectorizedValuesReader data) throws IOException {
+    int left = total;
+    while (left > 0) {
+      if (this.currentCount == 0) this.readNextGroup();
+      int n = Math.min(left, this.currentCount);
+      switch (mode) {
+        case RLE:
+          if (currentValue == level) {
+            data.readIntegersWithRebase(n, c, rowId);
+          } else {
+            c.putNulls(rowId, n);
+          }
+          break;
+        case PACKED:
+          for (int i = 0; i < n; ++i) {
+            if (currentBuffer[currentBufferIdx++] == level) {
+              c.putInt(rowId + i,
+                RebaseDateTime.rebaseJulianToGregorianDays(data.readInteger()));
+            } else {
+              c.putNull(rowId + i);
+            }
+          }
+          break;
+      }
+      rowId += n;
+      left -= n;
+      currentCount -= n;
+    }
+  }
+
   // TODO: can this code duplication be removed without a perf penalty?
   public void readBooleans(
       int total,
@@ -342,6 +380,43 @@ public void readLongs(
     }
   }
 
+  // A fork of `readLongs`, which rebases the timestamp long value (microseconds) before filling
+  // the Spark column vector.
+  public void readLongsWithRebase(
+      int total,
+      WritableColumnVector c,
+      int rowId,
+      int level,
+      VectorizedValuesReader data) throws IOException {
+    int left = total;
+    while (left > 0) {
+      if (this.currentCount == 0) this.readNextGroup();
+      int n = Math.min(left, this.currentCount);
+      switch (mode) {
+        case RLE:
+          if (currentValue == level) {
+            data.readLongsWithRebase(n, c, rowId);
+          } else {
+            c.putNulls(rowId, n);
+          }
+          break;
+        case PACKED:
+          for (int i = 0; i < n; ++i) {
+            if (currentBuffer[currentBufferIdx++] == level) {
+              c.putLong(rowId + i,
+                RebaseDateTime.rebaseJulianToGregorianMicros(data.readLong()));
+            } else {
+              c.putNull(rowId + i);
+            }
+          }
+          break;
+      }
+      rowId += n;
+      left -= n;
+      currentCount -= n;
+    }
+  }
+
   public void readFloats(
       int total,
       WritableColumnVector c,
@@ -508,6 +583,11 @@ public void readIntegers(int total, WritableColumnVector c, int rowId) {
     }
   }
 
+  @Override
+  public void readIntegersWithRebase(int total, WritableColumnVector c, int rowId) {
+    throw new UnsupportedOperationException("only readInts is valid.");
+  }
+
   @Override
   public byte readByte() {
     throw new UnsupportedOperationException("only readInts is valid.");
@@ -523,6 +603,11 @@ public void readLongs(int total, WritableColumnVector c, int rowId) {
     throw new UnsupportedOperationException("only readInts is valid.");
   }
 
+  @Override
+  public void readLongsWithRebase(int total, WritableColumnVector c, int rowId) {
+    throw new UnsupportedOperationException("only readInts is valid.");
+  }
+
   @Override
   public void readBinary(int total, WritableColumnVector c, int rowId) {
     throw new UnsupportedOperationException("only readInts is valid.");
diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedValuesReader.java b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedValuesReader.java
index 57d92ae27ece8..809ac44cc8272 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedValuesReader.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedValuesReader.java
@@ -40,7 +40,9 @@ public interface VectorizedValuesReader {
   void readBooleans(int total, WritableColumnVector c, int rowId);
   void readBytes(int total, WritableColumnVector c, int rowId);
   void readIntegers(int total, WritableColumnVector c, int rowId);
+  void readIntegersWithRebase(int total, WritableColumnVector c, int rowId);
   void readLongs(int total, WritableColumnVector c, int rowId);
+  void readLongsWithRebase(int total, WritableColumnVector c, int rowId);
   void readFloats(int total, WritableColumnVector c, int rowId);
   void readDoubles(int total, WritableColumnVector c, int rowId);
   void readBinary(int total, WritableColumnVector c, int rowId);
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeRebaseBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeRebaseBenchmark.scala
index 077ac28c149ee..7968836a00d0f 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeRebaseBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeRebaseBenchmark.scala
@@ -49,15 +49,15 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
       .select($"seconds".cast("timestamp").as("ts"))
   }
 
-  private def genTsAfter1582(cardinality: Int): DataFrame = {
-    val start = LocalDateTime.of(1582, 10, 15, 0, 0, 0)
+  private def genTsAfter1900(cardinality: Int): DataFrame = {
+    val start = LocalDateTime.of(1900, 1, 31, 0, 0, 0)
     val end = LocalDateTime.of(3000, 1, 1, 0, 0, 0)
     genTs(cardinality, start, end)
   }
 
-  private def genTsBefore1582(cardinality: Int): DataFrame = {
+  private def genTsBefore1900(cardinality: Int): DataFrame = {
     val start = LocalDateTime.of(10, 1, 1, 0, 0, 0)
-    val end = LocalDateTime.of(1580, 1, 1, 0, 0, 0)
+    val end = LocalDateTime.of(1900, 1, 1, 0, 0, 0)
     genTs(cardinality, start, end)
   }
 
@@ -71,34 +71,35 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
   }
 
   private def genDateAfter1582(cardinality: Int): DataFrame = {
-    val start = LocalDate.of(1582, 10, 15)
+    val start = LocalDate.of(1582, 10, 31)
     val end = LocalDate.of(3000, 1, 1)
     genDate(cardinality, start, end)
   }
 
   private def genDateBefore1582(cardinality: Int): DataFrame = {
     val start = LocalDate.of(10, 1, 1)
-    val end = LocalDate.of(1580, 1, 1)
+    val end = LocalDate.of(1580, 10, 1)
     genDate(cardinality, start, end)
   }
 
-  private def genDF(cardinality: Int, dateTime: String, after1582: Boolean): DataFrame = {
-    (dateTime, after1582) match {
+  private def genDF(cardinality: Int, dateTime: String, modernDates: Boolean): DataFrame = {
+    (dateTime, modernDates) match {
       case ("date", true) => genDateAfter1582(cardinality)
       case ("date", false) => genDateBefore1582(cardinality)
-      case ("timestamp", true) => genTsAfter1582(cardinality)
-      case ("timestamp", false) => genTsBefore1582(cardinality)
+      case ("timestamp", true) => genTsAfter1900(cardinality)
+      case ("timestamp", false) => genTsBefore1900(cardinality)
       case _ => throw new IllegalArgumentException(
-        s"cardinality = $cardinality dateTime = $dateTime after1582 = $after1582")
+        s"cardinality = $cardinality dateTime = $dateTime modernDates = $modernDates")
     }
   }
 
   private def benchmarkInputs(benchmark: Benchmark, rowsNum: Int, dateTime: String): Unit = {
-    benchmark.addCase("after 1582, noop", 1) { _ =>
-      genDF(rowsNum, dateTime, after1582 = true).noop()
+    val year = if (dateTime == "date") 1582 else 1900
+    benchmark.addCase(s"after $year, noop", 1) { _ =>
+      genDF(rowsNum, dateTime, modernDates = true).noop()
     }
-    benchmark.addCase("before 1582, noop", 1) { _ =>
-      genDF(rowsNum, dateTime, after1582 = false).noop()
+    benchmark.addCase(s"before $year, noop", 1) { _ =>
+      genDF(rowsNum, dateTime, modernDates = false).noop()
     }
   }
 
@@ -107,23 +108,26 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
   }
 
   private def caseName(
-      after1582: Boolean,
+      modernDates: Boolean,
+      dateTime: String,
       rebase: Option[Boolean] = None,
       vec: Option[Boolean] = None): String = {
-    val period = if (after1582) "after" else "before"
+    val period = if (modernDates) "after" else "before"
+    val year = if (dateTime == "date") 1582 else 1900
     val vecFlag = vec.map(flagToStr).map(flag => s", vec $flag").getOrElse("")
     val rebaseFlag = rebase.map(flagToStr).map(flag => s", rebase $flag").getOrElse("")
-    s"$period 1582$vecFlag$rebaseFlag"
+    s"$period $year$vecFlag$rebaseFlag"
   }
 
   private def getPath(
       basePath: File,
       dateTime: String,
-      after1582: Boolean,
+      modernDates: Boolean,
       rebase: Option[Boolean] = None): String = {
-    val period = if (after1582) "after" else "before"
+    val period = if (modernDates) "after" else "before"
+    val year = if (dateTime == "date") 1582 else 1900
     val rebaseFlag = rebase.map(flagToStr).map(flag => s"_$flag").getOrElse("")
-    basePath.getAbsolutePath + s"/${dateTime}_${period}_1582$rebaseFlag"
+    basePath.getAbsolutePath + s"/${dateTime}_${period}_$year$rebaseFlag"
   }
 
   override def runBenchmarkSuite(mainArgs: Array[String]): Unit = {
@@ -139,16 +143,16 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
                 rowsNum,
                 output = output)
               benchmarkInputs(benchmark, rowsNum, dateTime)
-              Seq(true, false).foreach { after1582 =>
+              Seq(true, false).foreach { modernDates =>
                 Seq(false, true).foreach { rebase =>
-                  benchmark.addCase(caseName(after1582, Some(rebase)), 1) { _ =>
+                  benchmark.addCase(caseName(modernDates, dateTime, Some(rebase)), 1) { _ =>
                     withSQLConf(
                       SQLConf.LEGACY_PARQUET_REBASE_DATETIME_IN_WRITE.key -> rebase.toString) {
-                      genDF(rowsNum, dateTime, after1582)
+                      genDF(rowsNum, dateTime, modernDates)
                         .write
                         .mode("overwrite")
                         .format("parquet")
-                        .save(getPath(path, dateTime, after1582, Some(rebase)))
+                        .save(getPath(path, dateTime, modernDates, Some(rebase)))
                     }
                   }
                 }
@@ -157,16 +161,15 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
 
               val benchmark2 = new Benchmark(
                 s"Load ${dateTime}s from parquet", rowsNum, output = output)
-              Seq(true, false).foreach { after1582 =>
+              Seq(true, false).foreach { modernDates =>
                 Seq(false, true).foreach { vec =>
                   Seq(false, true).foreach { rebase =>
-                    benchmark2.addCase(caseName(after1582, Some(rebase), Some(vec)), 3) { _ =>
-                      withSQLConf(
-                        SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> vec.toString,
-                        SQLConf.LEGACY_PARQUET_REBASE_DATETIME_IN_READ.key -> rebase.toString) {
+                    val name = caseName(modernDates, dateTime, Some(rebase), Some(vec))
+                    benchmark2.addCase(name, 3) { _ =>
+                      withSQLConf(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> vec.toString) {
                         spark.read
                           .format("parquet")
-                          .load(getPath(path, dateTime, after1582, Some(rebase)))
+                          .load(getPath(path, dateTime, modernDates, Some(rebase)))
                           .noop()
                       }
                     }
@@ -183,13 +186,13 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
             Seq("date", "timestamp").foreach { dateTime =>
               val benchmark = new Benchmark(s"Save ${dateTime}s to ORC", rowsNum, output = output)
               benchmarkInputs(benchmark, rowsNum, dateTime)
-              Seq(true, false).foreach { after1582 =>
-                benchmark.addCase(caseName(after1582), 1) { _ =>
-                  genDF(rowsNum, dateTime, after1582)
+              Seq(true, false).foreach { modernDates =>
+                benchmark.addCase(caseName(modernDates, dateTime), 1) { _ =>
+                  genDF(rowsNum, dateTime, modernDates)
                     .write
                     .mode("overwrite")
                     .format("orc")
-                    .save(getPath(path, dateTime, after1582))
+                    .save(getPath(path, dateTime, modernDates))
                 }
               }
               benchmark.run()
@@ -198,14 +201,14 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
                 s"Load ${dateTime}s from ORC",
                 rowsNum,
                 output = output)
-              Seq(true, false).foreach { after1582 =>
+              Seq(true, false).foreach { modernDates =>
                 Seq(false, true).foreach { vec =>
-                  benchmark2.addCase(caseName(after1582, vec = Some(vec)), 3) { _ =>
+                  benchmark2.addCase(caseName(modernDates, dateTime, vec = Some(vec)), 3) { _ =>
                     withSQLConf(SQLConf.ORC_VECTORIZED_READER_ENABLED.key -> vec.toString) {
                       spark
                         .read
                         .format("orc")
-                        .load(getPath(path, dateTime, after1582))
+                        .load(getPath(path, dateTime, modernDates))
                         .noop()
                     }
                   }

From ffd69c69772172311ad6969eaeac956cc72d30c6 Mon Sep 17 00:00:00 2001
From: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Date: Mon, 4 May 2020 16:53:50 +0900
Subject: [PATCH 10/19] [MINOR][DOCS] Fix typo in documents

### What changes were proposed in this pull request?
Fixed typo in `docs` directory and in `project/MimaExcludes.scala`

### Why are the changes needed?
Better readability of documents

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
No test needed

Closes #28447 from kiszk/typo_20200504.

Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
---
 docs/ml-classification-regression.md      |  4 ++--
 docs/spark-standalone.md                  |  2 +-
 docs/sql-migration-guide.md               |  6 +++---
 docs/sql-ref-functions-udf-hive.md        | 14 +++++++-------
 docs/sql-ref-functions.md                 |  2 +-
 docs/sql-ref-syntax-aux-describe-query.md |  2 +-
 docs/web-ui.md                            |  4 ++--
 7 files changed, 17 insertions(+), 17 deletions(-)

diff --git a/docs/ml-classification-regression.md b/docs/ml-classification-regression.md
index ce0831d3fb1a2..247989d16bcd7 100644
--- a/docs/ml-classification-regression.md
+++ b/docs/ml-classification-regression.md
@@ -567,7 +567,7 @@ Refer to the [Python API docs](api/python/pyspark.ml.html#pyspark.ml.classificat
 
 Refer to the [R API docs](api/R/spark.fmClassifier.html) for more details.
 
-Note: At the moment SparkR doesn't suport feature scaling.
+Note: At the moment SparkR doesn't support feature scaling.
 
 {% include_example r/ml/fmClassifier.R %}
 </div>
@@ -1105,7 +1105,7 @@ Refer to the [Python API docs](api/python/pyspark.ml.html#pyspark.ml.regression.
 
 Refer to the [R API documentation](api/R/spark.fmRegressor.html) for more details.
 
-Note: At the moment SparkR doesn't suport feature scaling.
+Note: At the moment SparkR doesn't support feature scaling.
 
 {% include_example r/ml/fmRegressor.R %}
 </div>
diff --git a/docs/spark-standalone.md b/docs/spark-standalone.md
index 2c2ed53b478c3..1e6f8c586d546 100644
--- a/docs/spark-standalone.md
+++ b/docs/spark-standalone.md
@@ -335,7 +335,7 @@ SPARK_WORKER_OPTS supports the following system properties:
     overlap with `spark.worker.cleanup.enabled`, as this enables cleanup of non-shuffle files in
     local directories of a dead executor, while `spark.worker.cleanup.enabled` enables cleanup of
     all files/subdirectories of a stopped and timeout application.
-    This only affects Standalone mode, support of other cluster manangers can be added in the future.
+    This only affects Standalone mode, support of other cluster managers can be added in the future.
   </td>
   <td>2.4.0</td>
 </tr>
diff --git a/docs/sql-migration-guide.md b/docs/sql-migration-guide.md
index 0d4075ab93001..9c113d658f090 100644
--- a/docs/sql-migration-guide.md
+++ b/docs/sql-migration-guide.md
@@ -42,7 +42,7 @@ license: |
 
   - In Spark 3.0, `CREATE TABLE` without a specific provider uses the value of `spark.sql.sources.default` as its provider. In Spark version 2.4 and below, it was Hive. To restore the behavior before Spark 3.0, you can set `spark.sql.legacy.createHiveTableByDefault.enabled` to `true`.
 
-  - In Spark 3.0, when inserting a value into a table column with a different data type, the type coercion is performed as per ANSI SQL standard. Certain unreasonable type conversions such as converting `string` to `int` and `double` to `boolean` are disallowed. A runtime exception is thrown if the value is out-of-range for the data type of the column. In Spark version 2.4 and below, type conversions during table insertion are allowed as long as they are valid `Cast`. When inserting an out-of-range value to a integral field, the low-order bits of the value is inserted(the same as Java/Scala numeric type casting). For example, if 257 is inserted to a field of byte type, the result is 1. The behavior is controlled by the option `spark.sql.storeAssignmentPolicy`, with a default value as "ANSI". Setting the option as "Legacy" restores the previous behavior.
+  - In Spark 3.0, when inserting a value into a table column with a different data type, the type coercion is performed as per ANSI SQL standard. Certain unreasonable type conversions such as converting `string` to `int` and `double` to `boolean` are disallowed. A runtime exception is thrown if the value is out-of-range for the data type of the column. In Spark version 2.4 and below, type conversions during table insertion are allowed as long as they are valid `Cast`. When inserting an out-of-range value to an integral field, the low-order bits of the value is inserted(the same as Java/Scala numeric type casting). For example, if 257 is inserted to a field of byte type, the result is 1. The behavior is controlled by the option `spark.sql.storeAssignmentPolicy`, with a default value as "ANSI". Setting the option as "Legacy" restores the previous behavior.
 
   - The `ADD JAR` command previously returned a result set with the single value 0. It now returns an empty result set.
 
@@ -50,7 +50,7 @@ license: |
 
   - Refreshing a cached table would trigger a table uncache operation and then a table cache (lazily) operation. In Spark version 2.4 and below, the cache name and storage level are not preserved before the uncache operation. Therefore, the cache name and storage level could be changed unexpectedly. In Spark 3.0, cache name and storage level are first preserved for cache recreation. It helps to maintain a consistent cache behavior upon table refreshing.
 
-  - In Spark 3.0, the properties listing below become reserved; commands fail if you specify reserved properties in places like `CREATE DATABASE ... WITH DBPROPERTIES` and `ALTER TABLE ... SET TBLPROPERTIES`. You need their specific clauses to specify them, for example, `CREATE DATABASE test COMMENT 'any comment' LOCATION 'some path'`. You can set `spark.sql.legacy.notReserveProperties` to `true` to ignore the `ParseException`, in this case, these properties will be silently removed, for example: `SET DBPROTERTIES('location'='/tmp')` will have no effect. In Spark version 2.4 and below, these properties are neither reserved nor have side effects, for example, `SET DBPROTERTIES('location'='/tmp')` do not change the location of the database but only create a headless property just like `'a'='b'`.
+  - In Spark 3.0, the properties listing below become reserved; commands fail if you specify reserved properties in places like `CREATE DATABASE ... WITH DBPROPERTIES` and `ALTER TABLE ... SET TBLPROPERTIES`. You need their specific clauses to specify them, for example, `CREATE DATABASE test COMMENT 'any comment' LOCATION 'some path'`. You can set `spark.sql.legacy.notReserveProperties` to `true` to ignore the `ParseException`, in this case, these properties will be silently removed, for example: `SET DBPROPERTIES('location'='/tmp')` will have no effect. In Spark version 2.4 and below, these properties are neither reserved nor have side effects, for example, `SET DBPROPERTIES('location'='/tmp')` do not change the location of the database but only create a headless property just like `'a'='b'`.
 
     | Property (case sensitive) | Database Reserved | Table Reserved | Remarks |
     | ------------------------- | ----------------- | -------------- | ------- |
@@ -130,7 +130,7 @@ license: |
 
   - In Spark 3.0, negative scale of decimal is not allowed by default, for example, data type of literal like `1E10BD` is `DecimalType(11, 0)`. In Spark version 2.4 and below, it was `DecimalType(2, -9)`. To restore the behavior before Spark 3.0, you can set `spark.sql.legacy.allowNegativeScaleOfDecimal` to `true`.
 
-  - In Spark 3.0, the unary arithmetic operator plus(`+`) only accepts string, numeric and interval type values as inputs. Besides, `+` with a integral string representation is coerced to a double value, for example, `+'1'` returns `1.0`. In Spark version 2.4 and below, this operator is ignored. There is no type checking for it, thus, all type values with a `+` prefix are valid, for example, `+ array(1, 2)` is valid and results `[1, 2]`. Besides, there is no type coercion for it at all, for example, in Spark 2.4, the result of `+'1'` is string `1`.
+  - In Spark 3.0, the unary arithmetic operator plus(`+`) only accepts string, numeric and interval type values as inputs. Besides, `+` with an integral string representation is coerced to a double value, for example, `+'1'` returns `1.0`. In Spark version 2.4 and below, this operator is ignored. There is no type checking for it, thus, all type values with a `+` prefix are valid, for example, `+ array(1, 2)` is valid and results `[1, 2]`. Besides, there is no type coercion for it at all, for example, in Spark 2.4, the result of `+'1'` is string `1`.
 
   - In Spark 3.0, Dataset query fails if it contains ambiguous column reference that is caused by self join. A typical example: `val df1 = ...; val df2 = df1.filter(...);`, then `df1.join(df2, df1("a") > df2("a"))` returns an empty result which is quite confusing. This is because Spark cannot resolve Dataset column references that point to tables being self joined, and `df1("a")` is exactly the same as `df2("a")` in Spark. To restore the behavior before Spark 3.0, you can set `spark.sql.analyzer.failAmbiguousSelfJoin` to `false`.
 
diff --git a/docs/sql-ref-functions-udf-hive.md b/docs/sql-ref-functions-udf-hive.md
index d3d2a221c94d8..7a7129de23836 100644
--- a/docs/sql-ref-functions-udf-hive.md
+++ b/docs/sql-ref-functions-udf-hive.md
@@ -28,9 +28,9 @@ Spark SQL supports integration of Hive UDFs, UDAFs and UDTFs. Similar to Spark U
 Hive has two UDF interfaces: [UDF](https://github.com/apache/hive/blob/master/udf/src/java/org/apache/hadoop/hive/ql/exec/UDF.java) and [GenericUDF](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDF.java).
 An example below uses [GenericUDFAbs](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDFAbs.java) derived from `GenericUDF`.
 
-```sql
+{% highlight sql %}
 -- Register `GenericUDFAbs` and use it in Spark SQL.
--- Note that, if you use your own programmed one, you need to add a JAR containig it
+-- Note that, if you use your own programmed one, you need to add a JAR containing it
 -- into a classpath,
 -- e.g., ADD JAR yourHiveUDF.jar;
 CREATE TEMPORARY FUNCTION testUDF AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDFAbs';
@@ -52,12 +52,12 @@ SELECT testUDF(value) FROM t;
 |           2.0|
 |           3.0|
 +--------------+
-```
+{% endhighlight %}
 
 
 An example below uses [GenericUDTFExplode](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDTFExplode.java) derived from [GenericUDTF](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDF.java).
 
-```sql
+{% highlight sql %}
 -- Register `GenericUDTFExplode` and use it in Spark SQL
 CREATE TEMPORARY FUNCTION hiveUDTF
     AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDTFExplode';
@@ -79,12 +79,12 @@ SELECT hiveUDTF(value) FROM t;
 |  3|
 |  4|
 +---+
-```
+{% endhighlight %}
 
 Hive has two UDAF interfaces: [UDAF](https://github.com/apache/hive/blob/master/udf/src/java/org/apache/hadoop/hive/ql/exec/UDAF.java) and [GenericUDAFResolver](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDAFResolver.java).
 An example below uses [GenericUDAFSum](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDAFSum.java) derived from `GenericUDAFResolver`.
 
-```sql
+{% highlight sql %}
 -- Register `GenericUDAFSum` and use it in Spark SQL
 CREATE TEMPORARY FUNCTION hiveUDAF
     AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDAFSum';
@@ -105,4 +105,4 @@ SELECT key, hiveUDAF(value) FROM t GROUP BY key;
 |  b|              3|
 |  a|              3|
 +---+---------------+
-```
\ No newline at end of file
+{% endhighlight %}
diff --git a/docs/sql-ref-functions.md b/docs/sql-ref-functions.md
index 7493b8bbb7cdf..67951a9695f5e 100644
--- a/docs/sql-ref-functions.md
+++ b/docs/sql-ref-functions.md
@@ -24,7 +24,7 @@ Built-in functions are commonly used routines that Spark SQL predefines and a co
 
 ### Built-in Functions
 
-Spark SQL has some categories of frequently-used built-in functions for aggregtion, arrays/maps, date/timestamp, and JSON data.
+Spark SQL has some categories of frequently-used built-in functions for aggregation, arrays/maps, date/timestamp, and JSON data.
 This subsection presents the usages and descriptions of these functions.
 
 #### Scalar Functions
diff --git a/docs/sql-ref-syntax-aux-describe-query.md b/docs/sql-ref-syntax-aux-describe-query.md
index 65e101d3dbf13..b2a74cbd06078 100644
--- a/docs/sql-ref-syntax-aux-describe-query.md
+++ b/docs/sql-ref-syntax-aux-describe-query.md
@@ -73,7 +73,7 @@ DESCRIBE QUERY WITH all_names_cte
 |    name|   string|   null|
 +--------+---------+-------+
 
--- Returns column metadata information for a inline table.
+-- Returns column metadata information for an inline table.
 DESC QUERY VALUES(100, 'John', 10000.20D) AS employee(id, name, salary);
 +--------+---------+-------+
 |col_name|data_type|comment|
diff --git a/docs/web-ui.md b/docs/web-ui.md
index c53af804d8d59..3c35dbeec86a2 100644
--- a/docs/web-ui.md
+++ b/docs/web-ui.md
@@ -99,7 +99,7 @@ This page displays the details of a specific job identified by its job ID.
 The Stages tab displays a summary page that shows the current state of all stages of all jobs in
 the Spark application.
 
-At the beginning of the page is the summary with the count of all stages by status (active, pending, completed, sikipped, and failed)
+At the beginning of the page is the summary with the count of all stages by status (active, pending, completed, skipped, and failed)
 
 <p style="text-align: center;">
   <img src="img/AllStagesPageDetail1.png" title="Stages header" alt="Stages header" width="30%">
@@ -136,7 +136,7 @@ Summary metrics for all task are represented in a table and in a timeline.
 * **[Tasks deserialization time](configuration.html#compression-and-serialization)**
 * **Duration of tasks**.
 * **GC time** is the total JVM garbage collection time.
-* **Result serialization time** is the time spent serializing the task result on a executor before sending it back to the driver.
+* **Result serialization time** is the time spent serializing the task result on an executor before sending it back to the driver.
 * **Getting result time** is the time that the driver spends fetching task results from workers.
 * **Scheduler delay** is the time the task waits to be scheduled for execution.
 * **Peak execution memory** is the maximum memory used by the internal data structures created during shuffles, aggregations and joins.

From 78758b6759c34fa2e80e580209557342b4997557 Mon Sep 17 00:00:00 2001
From: Burak Yavuz <brkyvz@gmail.com>
Date: Mon, 4 May 2020 12:22:29 +0000
Subject: [PATCH 11/19] [SPARK-31624] Fix SHOW TBLPROPERTIES for V2 tables that
 leverage the session catalog

## What changes were proposed in this pull request?

SHOW TBLPROPERTIES does not get the correct table properties for tables using the Session Catalog. This PR fixes that, by explicitly falling back to the V1 implementation if the table is in fact a V1 table. We also hide the reserved table properties for V2 tables, as users do not have control over setting these table properties. Henceforth, if they cannot be set or controlled by the user, then they shouldn't be displayed as such.

### Why are the changes needed?

Shows the incorrect table properties, i.e. only what exists in the Hive MetaStore for V2 tables that may have table properties outside of the MetaStore.

### Does this PR introduce _any_ user-facing change?

Fixes a bug

### How was this patch tested?

Regression test

Closes #28434 from brkyvz/ddlCommands.

Authored-by: Burak Yavuz <brkyvz@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
---
 .../analysis/ResolveSessionCatalog.scala       |  3 ++-
 .../v2/ShowTablePropertiesExec.scala           |  8 ++++++--
 .../DataSourceV2SQLSessionCatalogSuite.scala   | 18 +++++++++++++++++-
 .../sql/connector/DataSourceV2SQLSuite.scala   |  2 --
 4 files changed, 25 insertions(+), 6 deletions(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala b/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
index 58a7251f4ebd5..bf90875e511f8 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
@@ -559,7 +559,8 @@ class ResolveSessionCatalog(
             "SHOW VIEWS, only SessionCatalog supports this command.")
       }
 
-    case ShowTableProperties(r: ResolvedTable, propertyKey) if isSessionCatalog(r.catalog) =>
+    case ShowTableProperties(
+        r @ ResolvedTable(_, _, _: V1Table), propertyKey) if isSessionCatalog(r.catalog) =>
       ShowTablePropertiesCommand(r.identifier.asTableIdentifier, propertyKey)
 
     case ShowTableProperties(r: ResolvedView, propertyKey) =>
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala
index 0bcd7ea541045..fef63cb8253ca 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala
@@ -19,8 +19,8 @@ package org.apache.spark.sql.execution.datasources.v2
 
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.encoders.RowEncoder
-import org.apache.spark.sql.catalyst.expressions.{Attribute, GenericRowWithSchema}
-import org.apache.spark.sql.connector.catalog.Table
+import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeSet, GenericRowWithSchema}
+import org.apache.spark.sql.connector.catalog.{CatalogV2Util, Table, TableCatalog}
 
 /**
  * Physical plan node for showing table properties.
@@ -30,11 +30,15 @@ case class ShowTablePropertiesExec(
     catalogTable: Table,
     propertyKey: Option[String]) extends V2CommandExec {
 
+  override def producedAttributes: AttributeSet = AttributeSet(output)
+
   override protected def run(): Seq[InternalRow] = {
     import scala.collection.JavaConverters._
     val toRow = RowEncoder(schema).resolveAndBind().createSerializer()
 
+    // The reservered properties are accessible through DESCRIBE
     val properties = catalogTable.properties.asScala
+      .filter { case (k, v) => !CatalogV2Util.TABLE_RESERVED_PROPERTIES.contains(k) }
     propertyKey match {
       case Some(p) =>
         val propValue = properties
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSessionCatalogSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSessionCatalogSuite.scala
index 249b27c28b072..cf00b3b5e4410 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSessionCatalogSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSessionCatalogSuite.scala
@@ -17,7 +17,7 @@
 
 package org.apache.spark.sql.connector
 
-import org.apache.spark.sql.{DataFrame, SaveMode}
+import org.apache.spark.sql.{DataFrame, Row, SaveMode}
 import org.apache.spark.sql.connector.catalog.{Identifier, Table, TableCatalog}
 
 class DataSourceV2SQLSessionCatalogSuite
@@ -63,4 +63,20 @@ class DataSourceV2SQLSessionCatalogSuite
       }
     }
   }
+
+  test("SPARK-31624: SHOW TBLPROPERTIES working with V2 tables and the session catalog") {
+    val t1 = "tbl"
+    withTable(t1) {
+      sql(s"CREATE TABLE $t1 (id bigint, data string) USING $v2Format TBLPROPERTIES " +
+        "(key='v', key2='v2')")
+
+      checkAnswer(sql(s"SHOW TBLPROPERTIES $t1"), Seq(Row("key", "v"), Row("key2", "v2")))
+
+      checkAnswer(sql(s"SHOW TBLPROPERTIES $t1('key')"), Row("key", "v"))
+
+      checkAnswer(
+        sql(s"SHOW TBLPROPERTIES $t1('keyX')"),
+        Row("keyX", s"Table default.$t1 does not have property: keyX"))
+    }
+  }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala
index 3244684c33965..e947e15a179e8 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala
@@ -2122,8 +2122,6 @@ class DataSourceV2SQLSuite
         .add("value", StringType, nullable = false)
 
       val expected = Seq(
-        Row(TableCatalog.PROP_OWNER, defaultUser),
-        Row("provider", provider),
         Row("status", status),
         Row("user", user))
 

From 45f939f1afc70d782e67d87acd8be9945c16e7a0 Mon Sep 17 00:00:00 2001
From: Dongjoon Hyun <dongjoon@apache.org>
Date: Mon, 4 May 2020 08:14:12 -0700
Subject: [PATCH 12/19] [SPARK-31633][BUILD] Upgrade SLF4J from 1.7.16 to
 1.7.30

### What changes were proposed in this pull request?

This PR aims to upgrade SLF4J from 1.7.16 to 1.7.30.

### Why are the changes needed?

SLF4J 1.7.23+ is required to enable `slf4j-log4j12` with MDC feature to run under Java 9. Also, this will bring all latest bug fixes.
- http://www.slf4j.org/news.html

> When running under Java 9, log4j version 1.2.x is unable to correctly parse the "java.version" system property. Assuming an inccorect Java version, it proceeded to disable its MDC functionality. The slf4j-log4j12 module shipping in this release fixes the issue by tweaking MDC internals by reflection, allowing log4j to run under Java 9. See also SLF4J-393.

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Pass the Jenkins with the existing tests.

Closes #28446 from dongjoon-hyun/SPARK-31633.

Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
---
 dev/deps/spark-deps-hadoop-2.7-hive-1.2 | 8 ++++----
 dev/deps/spark-deps-hadoop-2.7-hive-2.3 | 8 ++++----
 dev/deps/spark-deps-hadoop-3.2-hive-2.3 | 8 ++++----
 pom.xml                                 | 2 +-
 4 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/dev/deps/spark-deps-hadoop-2.7-hive-1.2 b/dev/deps/spark-deps-hadoop-2.7-hive-1.2
index beaa7d42fbd0f..0f8da141249ca 100644
--- a/dev/deps/spark-deps-hadoop-2.7-hive-1.2
+++ b/dev/deps/spark-deps-hadoop-2.7-hive-1.2
@@ -112,7 +112,7 @@ javax.servlet-api/3.1.0//javax.servlet-api-3.1.0.jar
 javolution/5.5.1//javolution-5.5.1.jar
 jaxb-api/2.2.2//jaxb-api-2.2.2.jar
 jaxb-runtime/2.3.2//jaxb-runtime-2.3.2.jar
-jcl-over-slf4j/1.7.16//jcl-over-slf4j-1.7.16.jar
+jcl-over-slf4j/1.7.30//jcl-over-slf4j-1.7.30.jar
 jdo-api/3.0.1//jdo-api-3.0.1.jar
 jersey-client/2.30//jersey-client-2.30.jar
 jersey-common/2.30//jersey-common-2.30.jar
@@ -135,7 +135,7 @@ json4s-scalap_2.12/3.6.6//json4s-scalap_2.12-3.6.6.jar
 jsp-api/2.1//jsp-api-2.1.jar
 jsr305/3.0.0//jsr305-3.0.0.jar
 jta/1.1//jta-1.1.jar
-jul-to-slf4j/1.7.16//jul-to-slf4j-1.7.16.jar
+jul-to-slf4j/1.7.30//jul-to-slf4j-1.7.30.jar
 kryo-shaded/4.0.2//kryo-shaded-4.0.2.jar
 kubernetes-client/4.7.1//kubernetes-client-4.7.1.jar
 kubernetes-model-common/4.7.1//kubernetes-model-common-4.7.1.jar
@@ -184,8 +184,8 @@ scala-reflect/2.12.10//scala-reflect-2.12.10.jar
 scala-xml_2.12/1.2.0//scala-xml_2.12-1.2.0.jar
 shapeless_2.12/2.3.3//shapeless_2.12-2.3.3.jar
 shims/0.7.45//shims-0.7.45.jar
-slf4j-api/1.7.16//slf4j-api-1.7.16.jar
-slf4j-log4j12/1.7.16//slf4j-log4j12-1.7.16.jar
+slf4j-api/1.7.30//slf4j-api-1.7.30.jar
+slf4j-log4j12/1.7.30//slf4j-log4j12-1.7.30.jar
 snakeyaml/1.24//snakeyaml-1.24.jar
 snappy-java/1.1.7.3//snappy-java-1.1.7.3.jar
 snappy/0.2//snappy-0.2.jar
diff --git a/dev/deps/spark-deps-hadoop-2.7-hive-2.3 b/dev/deps/spark-deps-hadoop-2.7-hive-2.3
index 81c68e0bec983..6abdd7409eb14 100644
--- a/dev/deps/spark-deps-hadoop-2.7-hive-2.3
+++ b/dev/deps/spark-deps-hadoop-2.7-hive-2.3
@@ -126,7 +126,7 @@ javax.servlet-api/3.1.0//javax.servlet-api-3.1.0.jar
 javolution/5.5.1//javolution-5.5.1.jar
 jaxb-api/2.2.2//jaxb-api-2.2.2.jar
 jaxb-runtime/2.3.2//jaxb-runtime-2.3.2.jar
-jcl-over-slf4j/1.7.16//jcl-over-slf4j-1.7.16.jar
+jcl-over-slf4j/1.7.30//jcl-over-slf4j-1.7.30.jar
 jdo-api/3.0.1//jdo-api-3.0.1.jar
 jersey-client/2.30//jersey-client-2.30.jar
 jersey-common/2.30//jersey-common-2.30.jar
@@ -150,7 +150,7 @@ json4s-scalap_2.12/3.6.6//json4s-scalap_2.12-3.6.6.jar
 jsp-api/2.1//jsp-api-2.1.jar
 jsr305/3.0.0//jsr305-3.0.0.jar
 jta/1.1//jta-1.1.jar
-jul-to-slf4j/1.7.16//jul-to-slf4j-1.7.16.jar
+jul-to-slf4j/1.7.30//jul-to-slf4j-1.7.30.jar
 kryo-shaded/4.0.2//kryo-shaded-4.0.2.jar
 kubernetes-client/4.7.1//kubernetes-client-4.7.1.jar
 kubernetes-model-common/4.7.1//kubernetes-model-common-4.7.1.jar
@@ -198,8 +198,8 @@ scala-reflect/2.12.10//scala-reflect-2.12.10.jar
 scala-xml_2.12/1.2.0//scala-xml_2.12-1.2.0.jar
 shapeless_2.12/2.3.3//shapeless_2.12-2.3.3.jar
 shims/0.7.45//shims-0.7.45.jar
-slf4j-api/1.7.16//slf4j-api-1.7.16.jar
-slf4j-log4j12/1.7.16//slf4j-log4j12-1.7.16.jar
+slf4j-api/1.7.30//slf4j-api-1.7.30.jar
+slf4j-log4j12/1.7.30//slf4j-log4j12-1.7.30.jar
 snakeyaml/1.24//snakeyaml-1.24.jar
 snappy-java/1.1.7.3//snappy-java-1.1.7.3.jar
 spire-macros_2.12/0.17.0-M1//spire-macros_2.12-0.17.0-M1.jar
diff --git a/dev/deps/spark-deps-hadoop-3.2-hive-2.3 b/dev/deps/spark-deps-hadoop-3.2-hive-2.3
index 6966de94e46da..3553734b35fe6 100644
--- a/dev/deps/spark-deps-hadoop-3.2-hive-2.3
+++ b/dev/deps/spark-deps-hadoop-3.2-hive-2.3
@@ -126,7 +126,7 @@ javolution/5.5.1//javolution-5.5.1.jar
 jaxb-api/2.2.11//jaxb-api-2.2.11.jar
 jaxb-runtime/2.3.2//jaxb-runtime-2.3.2.jar
 jcip-annotations/1.0-1//jcip-annotations-1.0-1.jar
-jcl-over-slf4j/1.7.16//jcl-over-slf4j-1.7.16.jar
+jcl-over-slf4j/1.7.30//jcl-over-slf4j-1.7.30.jar
 jdo-api/3.0.1//jdo-api-3.0.1.jar
 jersey-client/2.30//jersey-client-2.30.jar
 jersey-common/2.30//jersey-common-2.30.jar
@@ -148,7 +148,7 @@ json4s-scalap_2.12/3.6.6//json4s-scalap_2.12-3.6.6.jar
 jsp-api/2.1//jsp-api-2.1.jar
 jsr305/3.0.0//jsr305-3.0.0.jar
 jta/1.1//jta-1.1.jar
-jul-to-slf4j/1.7.16//jul-to-slf4j-1.7.16.jar
+jul-to-slf4j/1.7.30//jul-to-slf4j-1.7.30.jar
 kerb-admin/1.0.1//kerb-admin-1.0.1.jar
 kerb-client/1.0.1//kerb-client-1.0.1.jar
 kerb-common/1.0.1//kerb-common-1.0.1.jar
@@ -214,8 +214,8 @@ scala-reflect/2.12.10//scala-reflect-2.12.10.jar
 scala-xml_2.12/1.2.0//scala-xml_2.12-1.2.0.jar
 shapeless_2.12/2.3.3//shapeless_2.12-2.3.3.jar
 shims/0.7.45//shims-0.7.45.jar
-slf4j-api/1.7.16//slf4j-api-1.7.16.jar
-slf4j-log4j12/1.7.16//slf4j-log4j12-1.7.16.jar
+slf4j-api/1.7.30//slf4j-api-1.7.30.jar
+slf4j-log4j12/1.7.30//slf4j-log4j12-1.7.30.jar
 snakeyaml/1.24//snakeyaml-1.24.jar
 snappy-java/1.1.7.3//snappy-java-1.1.7.3.jar
 spire-macros_2.12/0.17.0-M1//spire-macros_2.12-0.17.0-M1.jar
diff --git a/pom.xml b/pom.xml
index 8dbff24c5d8c8..9c55630786ce7 100644
--- a/pom.xml
+++ b/pom.xml
@@ -117,7 +117,7 @@
     <maven.compiler.target>${java.version}</maven.compiler.target>
     <maven.version>3.6.3</maven.version>
     <sbt.project.name>spark</sbt.project.name>
-    <slf4j.version>1.7.16</slf4j.version>
+    <slf4j.version>1.7.30</slf4j.version>
     <log4j.version>1.2.17</log4j.version>
     <hadoop.version>2.7.4</hadoop.version>
     <protobuf.version>2.5.0</protobuf.version>

From 6e340c8d77a659a507aa75051a748983568a7bf4 Mon Sep 17 00:00:00 2001
From: Huaxin Gao <huaxing@us.ibm.com>
Date: Mon, 4 May 2020 11:23:07 -0700
Subject: [PATCH 13/19] Revert "[SPARK-31624] Fix SHOW TBLPROPERTIES for V2
 tables that leverage the session catalog"

This reverts commit 78758b6759c34fa2e80e580209557342b4997557.
---
 .../analysis/ResolveSessionCatalog.scala       |  3 +--
 .../v2/ShowTablePropertiesExec.scala           |  8 ++------
 .../DataSourceV2SQLSessionCatalogSuite.scala   | 18 +-----------------
 .../sql/connector/DataSourceV2SQLSuite.scala   |  2 ++
 4 files changed, 6 insertions(+), 25 deletions(-)

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala b/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
index bf90875e511f8..58a7251f4ebd5 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
@@ -559,8 +559,7 @@ class ResolveSessionCatalog(
             "SHOW VIEWS, only SessionCatalog supports this command.")
       }
 
-    case ShowTableProperties(
-        r @ ResolvedTable(_, _, _: V1Table), propertyKey) if isSessionCatalog(r.catalog) =>
+    case ShowTableProperties(r: ResolvedTable, propertyKey) if isSessionCatalog(r.catalog) =>
       ShowTablePropertiesCommand(r.identifier.asTableIdentifier, propertyKey)
 
     case ShowTableProperties(r: ResolvedView, propertyKey) =>
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala
index fef63cb8253ca..0bcd7ea541045 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/ShowTablePropertiesExec.scala
@@ -19,8 +19,8 @@ package org.apache.spark.sql.execution.datasources.v2
 
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.encoders.RowEncoder
-import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeSet, GenericRowWithSchema}
-import org.apache.spark.sql.connector.catalog.{CatalogV2Util, Table, TableCatalog}
+import org.apache.spark.sql.catalyst.expressions.{Attribute, GenericRowWithSchema}
+import org.apache.spark.sql.connector.catalog.Table
 
 /**
  * Physical plan node for showing table properties.
@@ -30,15 +30,11 @@ case class ShowTablePropertiesExec(
     catalogTable: Table,
     propertyKey: Option[String]) extends V2CommandExec {
 
-  override def producedAttributes: AttributeSet = AttributeSet(output)
-
   override protected def run(): Seq[InternalRow] = {
     import scala.collection.JavaConverters._
     val toRow = RowEncoder(schema).resolveAndBind().createSerializer()
 
-    // The reservered properties are accessible through DESCRIBE
     val properties = catalogTable.properties.asScala
-      .filter { case (k, v) => !CatalogV2Util.TABLE_RESERVED_PROPERTIES.contains(k) }
     propertyKey match {
       case Some(p) =>
         val propValue = properties
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSessionCatalogSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSessionCatalogSuite.scala
index cf00b3b5e4410..249b27c28b072 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSessionCatalogSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSessionCatalogSuite.scala
@@ -17,7 +17,7 @@
 
 package org.apache.spark.sql.connector
 
-import org.apache.spark.sql.{DataFrame, Row, SaveMode}
+import org.apache.spark.sql.{DataFrame, SaveMode}
 import org.apache.spark.sql.connector.catalog.{Identifier, Table, TableCatalog}
 
 class DataSourceV2SQLSessionCatalogSuite
@@ -63,20 +63,4 @@ class DataSourceV2SQLSessionCatalogSuite
       }
     }
   }
-
-  test("SPARK-31624: SHOW TBLPROPERTIES working with V2 tables and the session catalog") {
-    val t1 = "tbl"
-    withTable(t1) {
-      sql(s"CREATE TABLE $t1 (id bigint, data string) USING $v2Format TBLPROPERTIES " +
-        "(key='v', key2='v2')")
-
-      checkAnswer(sql(s"SHOW TBLPROPERTIES $t1"), Seq(Row("key", "v"), Row("key2", "v2")))
-
-      checkAnswer(sql(s"SHOW TBLPROPERTIES $t1('key')"), Row("key", "v"))
-
-      checkAnswer(
-        sql(s"SHOW TBLPROPERTIES $t1('keyX')"),
-        Row("keyX", s"Table default.$t1 does not have property: keyX"))
-    }
-  }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala
index e947e15a179e8..3244684c33965 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala
@@ -2122,6 +2122,8 @@ class DataSourceV2SQLSuite
         .add("value", StringType, nullable = false)
 
       val expected = Seq(
+        Row(TableCatalog.PROP_OWNER, defaultUser),
+        Row("provider", provider),
         Row("status", status),
         Row("user", user))
 

From 368cdc8f8f6a3d7f3ae6304b62d506ff237763c4 Mon Sep 17 00:00:00 2001
From: Huaxin Gao <huaxing@us.ibm.com>
Date: Mon, 4 May 2020 11:23:27 -0700
Subject: [PATCH 14/19] Revert "[MINOR][DOCS] Fix typo in documents"

This reverts commit ffd69c69772172311ad6969eaeac956cc72d30c6.
---
 docs/ml-classification-regression.md      |  4 ++--
 docs/spark-standalone.md                  |  2 +-
 docs/sql-migration-guide.md               |  6 +++---
 docs/sql-ref-functions-udf-hive.md        | 14 +++++++-------
 docs/sql-ref-functions.md                 |  2 +-
 docs/sql-ref-syntax-aux-describe-query.md |  2 +-
 docs/web-ui.md                            |  4 ++--
 7 files changed, 17 insertions(+), 17 deletions(-)

diff --git a/docs/ml-classification-regression.md b/docs/ml-classification-regression.md
index 247989d16bcd7..ce0831d3fb1a2 100644
--- a/docs/ml-classification-regression.md
+++ b/docs/ml-classification-regression.md
@@ -567,7 +567,7 @@ Refer to the [Python API docs](api/python/pyspark.ml.html#pyspark.ml.classificat
 
 Refer to the [R API docs](api/R/spark.fmClassifier.html) for more details.
 
-Note: At the moment SparkR doesn't support feature scaling.
+Note: At the moment SparkR doesn't suport feature scaling.
 
 {% include_example r/ml/fmClassifier.R %}
 </div>
@@ -1105,7 +1105,7 @@ Refer to the [Python API docs](api/python/pyspark.ml.html#pyspark.ml.regression.
 
 Refer to the [R API documentation](api/R/spark.fmRegressor.html) for more details.
 
-Note: At the moment SparkR doesn't support feature scaling.
+Note: At the moment SparkR doesn't suport feature scaling.
 
 {% include_example r/ml/fmRegressor.R %}
 </div>
diff --git a/docs/spark-standalone.md b/docs/spark-standalone.md
index 1e6f8c586d546..2c2ed53b478c3 100644
--- a/docs/spark-standalone.md
+++ b/docs/spark-standalone.md
@@ -335,7 +335,7 @@ SPARK_WORKER_OPTS supports the following system properties:
     overlap with `spark.worker.cleanup.enabled`, as this enables cleanup of non-shuffle files in
     local directories of a dead executor, while `spark.worker.cleanup.enabled` enables cleanup of
     all files/subdirectories of a stopped and timeout application.
-    This only affects Standalone mode, support of other cluster managers can be added in the future.
+    This only affects Standalone mode, support of other cluster manangers can be added in the future.
   </td>
   <td>2.4.0</td>
 </tr>
diff --git a/docs/sql-migration-guide.md b/docs/sql-migration-guide.md
index 9c113d658f090..0d4075ab93001 100644
--- a/docs/sql-migration-guide.md
+++ b/docs/sql-migration-guide.md
@@ -42,7 +42,7 @@ license: |
 
   - In Spark 3.0, `CREATE TABLE` without a specific provider uses the value of `spark.sql.sources.default` as its provider. In Spark version 2.4 and below, it was Hive. To restore the behavior before Spark 3.0, you can set `spark.sql.legacy.createHiveTableByDefault.enabled` to `true`.
 
-  - In Spark 3.0, when inserting a value into a table column with a different data type, the type coercion is performed as per ANSI SQL standard. Certain unreasonable type conversions such as converting `string` to `int` and `double` to `boolean` are disallowed. A runtime exception is thrown if the value is out-of-range for the data type of the column. In Spark version 2.4 and below, type conversions during table insertion are allowed as long as they are valid `Cast`. When inserting an out-of-range value to an integral field, the low-order bits of the value is inserted(the same as Java/Scala numeric type casting). For example, if 257 is inserted to a field of byte type, the result is 1. The behavior is controlled by the option `spark.sql.storeAssignmentPolicy`, with a default value as "ANSI". Setting the option as "Legacy" restores the previous behavior.
+  - In Spark 3.0, when inserting a value into a table column with a different data type, the type coercion is performed as per ANSI SQL standard. Certain unreasonable type conversions such as converting `string` to `int` and `double` to `boolean` are disallowed. A runtime exception is thrown if the value is out-of-range for the data type of the column. In Spark version 2.4 and below, type conversions during table insertion are allowed as long as they are valid `Cast`. When inserting an out-of-range value to a integral field, the low-order bits of the value is inserted(the same as Java/Scala numeric type casting). For example, if 257 is inserted to a field of byte type, the result is 1. The behavior is controlled by the option `spark.sql.storeAssignmentPolicy`, with a default value as "ANSI". Setting the option as "Legacy" restores the previous behavior.
 
   - The `ADD JAR` command previously returned a result set with the single value 0. It now returns an empty result set.
 
@@ -50,7 +50,7 @@ license: |
 
   - Refreshing a cached table would trigger a table uncache operation and then a table cache (lazily) operation. In Spark version 2.4 and below, the cache name and storage level are not preserved before the uncache operation. Therefore, the cache name and storage level could be changed unexpectedly. In Spark 3.0, cache name and storage level are first preserved for cache recreation. It helps to maintain a consistent cache behavior upon table refreshing.
 
-  - In Spark 3.0, the properties listing below become reserved; commands fail if you specify reserved properties in places like `CREATE DATABASE ... WITH DBPROPERTIES` and `ALTER TABLE ... SET TBLPROPERTIES`. You need their specific clauses to specify them, for example, `CREATE DATABASE test COMMENT 'any comment' LOCATION 'some path'`. You can set `spark.sql.legacy.notReserveProperties` to `true` to ignore the `ParseException`, in this case, these properties will be silently removed, for example: `SET DBPROPERTIES('location'='/tmp')` will have no effect. In Spark version 2.4 and below, these properties are neither reserved nor have side effects, for example, `SET DBPROPERTIES('location'='/tmp')` do not change the location of the database but only create a headless property just like `'a'='b'`.
+  - In Spark 3.0, the properties listing below become reserved; commands fail if you specify reserved properties in places like `CREATE DATABASE ... WITH DBPROPERTIES` and `ALTER TABLE ... SET TBLPROPERTIES`. You need their specific clauses to specify them, for example, `CREATE DATABASE test COMMENT 'any comment' LOCATION 'some path'`. You can set `spark.sql.legacy.notReserveProperties` to `true` to ignore the `ParseException`, in this case, these properties will be silently removed, for example: `SET DBPROTERTIES('location'='/tmp')` will have no effect. In Spark version 2.4 and below, these properties are neither reserved nor have side effects, for example, `SET DBPROTERTIES('location'='/tmp')` do not change the location of the database but only create a headless property just like `'a'='b'`.
 
     | Property (case sensitive) | Database Reserved | Table Reserved | Remarks |
     | ------------------------- | ----------------- | -------------- | ------- |
@@ -130,7 +130,7 @@ license: |
 
   - In Spark 3.0, negative scale of decimal is not allowed by default, for example, data type of literal like `1E10BD` is `DecimalType(11, 0)`. In Spark version 2.4 and below, it was `DecimalType(2, -9)`. To restore the behavior before Spark 3.0, you can set `spark.sql.legacy.allowNegativeScaleOfDecimal` to `true`.
 
-  - In Spark 3.0, the unary arithmetic operator plus(`+`) only accepts string, numeric and interval type values as inputs. Besides, `+` with an integral string representation is coerced to a double value, for example, `+'1'` returns `1.0`. In Spark version 2.4 and below, this operator is ignored. There is no type checking for it, thus, all type values with a `+` prefix are valid, for example, `+ array(1, 2)` is valid and results `[1, 2]`. Besides, there is no type coercion for it at all, for example, in Spark 2.4, the result of `+'1'` is string `1`.
+  - In Spark 3.0, the unary arithmetic operator plus(`+`) only accepts string, numeric and interval type values as inputs. Besides, `+` with a integral string representation is coerced to a double value, for example, `+'1'` returns `1.0`. In Spark version 2.4 and below, this operator is ignored. There is no type checking for it, thus, all type values with a `+` prefix are valid, for example, `+ array(1, 2)` is valid and results `[1, 2]`. Besides, there is no type coercion for it at all, for example, in Spark 2.4, the result of `+'1'` is string `1`.
 
   - In Spark 3.0, Dataset query fails if it contains ambiguous column reference that is caused by self join. A typical example: `val df1 = ...; val df2 = df1.filter(...);`, then `df1.join(df2, df1("a") > df2("a"))` returns an empty result which is quite confusing. This is because Spark cannot resolve Dataset column references that point to tables being self joined, and `df1("a")` is exactly the same as `df2("a")` in Spark. To restore the behavior before Spark 3.0, you can set `spark.sql.analyzer.failAmbiguousSelfJoin` to `false`.
 
diff --git a/docs/sql-ref-functions-udf-hive.md b/docs/sql-ref-functions-udf-hive.md
index 7a7129de23836..d3d2a221c94d8 100644
--- a/docs/sql-ref-functions-udf-hive.md
+++ b/docs/sql-ref-functions-udf-hive.md
@@ -28,9 +28,9 @@ Spark SQL supports integration of Hive UDFs, UDAFs and UDTFs. Similar to Spark U
 Hive has two UDF interfaces: [UDF](https://github.com/apache/hive/blob/master/udf/src/java/org/apache/hadoop/hive/ql/exec/UDF.java) and [GenericUDF](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDF.java).
 An example below uses [GenericUDFAbs](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDFAbs.java) derived from `GenericUDF`.
 
-{% highlight sql %}
+```sql
 -- Register `GenericUDFAbs` and use it in Spark SQL.
--- Note that, if you use your own programmed one, you need to add a JAR containing it
+-- Note that, if you use your own programmed one, you need to add a JAR containig it
 -- into a classpath,
 -- e.g., ADD JAR yourHiveUDF.jar;
 CREATE TEMPORARY FUNCTION testUDF AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDFAbs';
@@ -52,12 +52,12 @@ SELECT testUDF(value) FROM t;
 |           2.0|
 |           3.0|
 +--------------+
-{% endhighlight %}
+```
 
 
 An example below uses [GenericUDTFExplode](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDTFExplode.java) derived from [GenericUDTF](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDF.java).
 
-{% highlight sql %}
+```sql
 -- Register `GenericUDTFExplode` and use it in Spark SQL
 CREATE TEMPORARY FUNCTION hiveUDTF
     AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDTFExplode';
@@ -79,12 +79,12 @@ SELECT hiveUDTF(value) FROM t;
 |  3|
 |  4|
 +---+
-{% endhighlight %}
+```
 
 Hive has two UDAF interfaces: [UDAF](https://github.com/apache/hive/blob/master/udf/src/java/org/apache/hadoop/hive/ql/exec/UDAF.java) and [GenericUDAFResolver](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDAFResolver.java).
 An example below uses [GenericUDAFSum](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDAFSum.java) derived from `GenericUDAFResolver`.
 
-{% highlight sql %}
+```sql
 -- Register `GenericUDAFSum` and use it in Spark SQL
 CREATE TEMPORARY FUNCTION hiveUDAF
     AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDAFSum';
@@ -105,4 +105,4 @@ SELECT key, hiveUDAF(value) FROM t GROUP BY key;
 |  b|              3|
 |  a|              3|
 +---+---------------+
-{% endhighlight %}
+```
\ No newline at end of file
diff --git a/docs/sql-ref-functions.md b/docs/sql-ref-functions.md
index 67951a9695f5e..7493b8bbb7cdf 100644
--- a/docs/sql-ref-functions.md
+++ b/docs/sql-ref-functions.md
@@ -24,7 +24,7 @@ Built-in functions are commonly used routines that Spark SQL predefines and a co
 
 ### Built-in Functions
 
-Spark SQL has some categories of frequently-used built-in functions for aggregation, arrays/maps, date/timestamp, and JSON data.
+Spark SQL has some categories of frequently-used built-in functions for aggregtion, arrays/maps, date/timestamp, and JSON data.
 This subsection presents the usages and descriptions of these functions.
 
 #### Scalar Functions
diff --git a/docs/sql-ref-syntax-aux-describe-query.md b/docs/sql-ref-syntax-aux-describe-query.md
index b2a74cbd06078..65e101d3dbf13 100644
--- a/docs/sql-ref-syntax-aux-describe-query.md
+++ b/docs/sql-ref-syntax-aux-describe-query.md
@@ -73,7 +73,7 @@ DESCRIBE QUERY WITH all_names_cte
 |    name|   string|   null|
 +--------+---------+-------+
 
--- Returns column metadata information for an inline table.
+-- Returns column metadata information for a inline table.
 DESC QUERY VALUES(100, 'John', 10000.20D) AS employee(id, name, salary);
 +--------+---------+-------+
 |col_name|data_type|comment|
diff --git a/docs/web-ui.md b/docs/web-ui.md
index 3c35dbeec86a2..c53af804d8d59 100644
--- a/docs/web-ui.md
+++ b/docs/web-ui.md
@@ -99,7 +99,7 @@ This page displays the details of a specific job identified by its job ID.
 The Stages tab displays a summary page that shows the current state of all stages of all jobs in
 the Spark application.
 
-At the beginning of the page is the summary with the count of all stages by status (active, pending, completed, skipped, and failed)
+At the beginning of the page is the summary with the count of all stages by status (active, pending, completed, sikipped, and failed)
 
 <p style="text-align: center;">
   <img src="img/AllStagesPageDetail1.png" title="Stages header" alt="Stages header" width="30%">
@@ -136,7 +136,7 @@ Summary metrics for all task are represented in a table and in a timeline.
 * **[Tasks deserialization time](configuration.html#compression-and-serialization)**
 * **Duration of tasks**.
 * **GC time** is the total JVM garbage collection time.
-* **Result serialization time** is the time spent serializing the task result on an executor before sending it back to the driver.
+* **Result serialization time** is the time spent serializing the task result on a executor before sending it back to the driver.
 * **Getting result time** is the time that the driver spends fetching task results from workers.
 * **Scheduler delay** is the time the task waits to be scheduled for execution.
 * **Peak execution memory** is the maximum memory used by the internal data structures created during shuffles, aggregations and joins.

From 0bd2ca5fc79cf88d6d9248c8fbc02f43a387b832 Mon Sep 17 00:00:00 2001
From: Huaxin Gao <huaxing@us.ibm.com>
Date: Mon, 4 May 2020 11:23:32 -0700
Subject: [PATCH 15/19] Revert "[SPARK-31606][SQL] Reduce the perf regression
 of vectorized parquet reader caused by datetime rebase"

This reverts commit 931c0bcd95087716c633eb9fd065d580a1d47353.
---
 .../sql/catalyst/util/RebaseDateTime.scala    |   4 -
 .../DateTimeRebaseBenchmark-jdk11-results.txt | 104 +++++++++---------
 .../DateTimeRebaseBenchmark-results.txt       | 104 +++++++++---------
 .../parquet/VectorizedColumnReader.java       |  22 +++-
 .../parquet/VectorizedPlainValuesReader.java  |  55 ---------
 .../parquet/VectorizedRleValuesReader.java    |  85 --------------
 .../parquet/VectorizedValuesReader.java       |   2 -
 .../benchmark/DateTimeRebaseBenchmark.scala   |  79 +++++++------
 8 files changed, 160 insertions(+), 295 deletions(-)

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/RebaseDateTime.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/RebaseDateTime.scala
index 040a97a14d451..6848b0fa39c7c 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/RebaseDateTime.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/RebaseDateTime.scala
@@ -71,8 +71,6 @@ object RebaseDateTime {
     -719164, -682945, -646420, -609895, -536845, -500320, -463795,
     -390745, -354220, -317695, -244645, -208120, -171595, -141427)
 
-  final val lastSwitchJulianDay: Int = julianGregDiffSwitchDay.last
-
   // The first days of Common Era (CE) which is mapped to the '0001-01-01' date in Julian calendar.
   private final val julianCommonEraStartDay = julianGregDiffSwitchDay(0)
 
@@ -418,8 +416,6 @@ object RebaseDateTime {
   // in the interval: [julianGregDiffSwitchMicros(i), julianGregDiffSwitchMicros(i+1))
   private val julianGregRebaseMap = loadRebaseRecords("julian-gregorian-rebase-micros.json")
 
-  final val lastSwitchJulianTs: Long = julianGregRebaseMap.values.map(_.switches.last).max
-
   /**
    * An optimized version of [[rebaseJulianToGregorianMicros(ZoneId, Long)]]. This method leverages
    * the pre-calculated rebasing maps to save calculation. If the rebasing map doesn't contain
diff --git a/sql/core/benchmarks/DateTimeRebaseBenchmark-jdk11-results.txt b/sql/core/benchmarks/DateTimeRebaseBenchmark-jdk11-results.txt
index 03e0d7b8bc575..2a9322a4b462a 100644
--- a/sql/core/benchmarks/DateTimeRebaseBenchmark-jdk11-results.txt
+++ b/sql/core/benchmarks/DateTimeRebaseBenchmark-jdk11-results.txt
@@ -2,93 +2,93 @@
 Rebasing dates/timestamps in Parquet datasource
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save dates to parquet:                    Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                  20073          20073           0          5.0         200.7       1.0X
-before 1582, noop                                 10985          10985           0          9.1         109.9       1.8X
-after 1582, rebase off                            32245          32245           0          3.1         322.4       0.6X
-after 1582, rebase on                             31434          31434           0          3.2         314.3       0.6X
-before 1582, rebase off                           21590          21590           0          4.6         215.9       0.9X
-before 1582, rebase on                            22963          22963           0          4.4         229.6       0.9X
+after 1582, noop                                  21171          21171           0          4.7         211.7       1.0X
+before 1582, noop                                 11036          11036           0          9.1         110.4       1.9X
+after 1582, rebase off                            34321          34321           0          2.9         343.2       0.6X
+after 1582, rebase on                             33269          33269           0          3.0         332.7       0.6X
+before 1582, rebase off                           22016          22016           0          4.5         220.2       1.0X
+before 1582, rebase on                            23338          23338           0          4.3         233.4       0.9X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load dates from parquet:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off, rebase off                   12815          12858          40          7.8         128.1       1.0X
-after 1582, vec off, rebase on                    13030          13167         148          7.7         130.3       1.0X
-after 1582, vec on, rebase off                     3705           3712           6         27.0          37.1       3.5X
-after 1582, vec on, rebase on                      3788           3791           3         26.4          37.9       3.4X
-before 1582, vec off, rebase off                  12873          12943          61          7.8         128.7       1.0X
-before 1582, vec off, rebase on                   14072          14165          80          7.1         140.7       0.9X
-before 1582, vec on, rebase off                    3694           3708          15         27.1          36.9       3.5X
-before 1582, vec on, rebase on                     4403           4484          81         22.7          44.0       2.9X
+after 1582, vec off, rebase off                   12791          13089         287          7.8         127.9       1.0X
+after 1582, vec off, rebase on                    13203          13271          81          7.6         132.0       1.0X
+after 1582, vec on, rebase off                     3709           3764          49         27.0          37.1       3.4X
+after 1582, vec on, rebase on                      5082           5114          29         19.7          50.8       2.5X
+before 1582, vec off, rebase off                  13059          13153          87          7.7         130.6       1.0X
+before 1582, vec off, rebase on                   14211          14236          27          7.0         142.1       0.9X
+before 1582, vec on, rebase off                    3687           3749          72         27.1          36.9       3.5X
+before 1582, vec on, rebase on                     5449           5497          56         18.4          54.5       2.3X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save timestamps to parquet:               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1900, noop                                   3032           3032           0         33.0          30.3       1.0X
-before 1900, noop                                  3043           3043           0         32.9          30.4       1.0X
-after 1900, rebase off                            15634          15634           0          6.4         156.3       0.2X
-after 1900, rebase on                             18233          18233           0          5.5         182.3       0.2X
-before 1900, rebase off                           15820          15820           0          6.3         158.2       0.2X
-before 1900, rebase on                            19921          19921           0          5.0         199.2       0.2X
+after 1582, noop                                   2831           2831           0         35.3          28.3       1.0X
+before 1582, noop                                  2816           2816           0         35.5          28.2       1.0X
+after 1582, rebase off                            15543          15543           0          6.4         155.4       0.2X
+after 1582, rebase on                             18391          18391           0          5.4         183.9       0.2X
+before 1582, rebase off                           15747          15747           0          6.4         157.5       0.2X
+before 1582, rebase on                            18846          18846           0          5.3         188.5       0.2X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load timestamps from parquet:             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1900, vec off, rebase off                   14987          15008          18          6.7         149.9       1.0X
-after 1900, vec off, rebase on                    17500          17628         210          5.7         175.0       0.9X
-after 1900, vec on, rebase off                     5030           5036           7         19.9          50.3       3.0X
-after 1900, vec on, rebase on                      5066           5109          44         19.7          50.7       3.0X
-before 1900, vec off, rebase off                  15094          15213         121          6.6         150.9       1.0X
-before 1900, vec off, rebase on                   18098          18175         101          5.5         181.0       0.8X
-before 1900, vec on, rebase off                    5008           5012           4         20.0          50.1       3.0X
-before 1900, vec on, rebase on                     8803           8848          55         11.4          88.0       1.7X
+after 1582, vec off, rebase off                   16126          16216          78          6.2         161.3       1.0X
+after 1582, vec off, rebase on                    18277          18453         165          5.5         182.8       0.9X
+after 1582, vec on, rebase off                     5030           5067          42         19.9          50.3       3.2X
+after 1582, vec on, rebase on                      8553           8583          43         11.7          85.5       1.9X
+before 1582, vec off, rebase off                  15828          15872          39          6.3         158.3       1.0X
+before 1582, vec off, rebase on                   18899          18959         103          5.3         189.0       0.9X
+before 1582, vec on, rebase off                    4961           5009          43         20.2          49.6       3.3X
+before 1582, vec on, rebase on                     9099           9140          40         11.0          91.0       1.8X
 
 
 ================================================================================================
 Rebasing dates/timestamps in ORC datasource
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save dates to ORC:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                  19593          19593           0          5.1         195.9       1.0X
-before 1582, noop                                 10581          10581           0          9.5         105.8       1.9X
-after 1582                                        27843          27843           0          3.6         278.4       0.7X
-before 1582                                       19435          19435           0          5.1         194.4       1.0X
+after 1582, noop                                  21026          21026           0          4.8         210.3       1.0X
+before 1582, noop                                 11040          11040           0          9.1         110.4       1.9X
+after 1582                                        28171          28171           0          3.5         281.7       0.7X
+before 1582                                       18955          18955           0          5.3         189.5       1.1X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load dates from ORC:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off                               10395          10507         119          9.6         103.9       1.0X
-after 1582, vec on                                 3921           3945          22         25.5          39.2       2.7X
-before 1582, vec off                              10762          10860         127          9.3         107.6       1.0X
-before 1582, vec on                                4194           4226          41         23.8          41.9       2.5X
+after 1582, vec off                               10876          10931          49          9.2         108.8       1.0X
+after 1582, vec on                                 3900           3913          20         25.6          39.0       2.8X
+before 1582, vec off                              11165          11174          12          9.0         111.6       1.0X
+before 1582, vec on                                4208           4214           7         23.8          42.1       2.6X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save timestamps to ORC:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1900, noop                                   3003           3003           0         33.3          30.0       1.0X
-before 1900, noop                                  3016           3016           0         33.2          30.2       1.0X
-after 1900                                        21804          21804           0          4.6         218.0       0.1X
-before 1900                                       23920          23920           0          4.2         239.2       0.1X
+after 1582, noop                                   2924           2924           0         34.2          29.2       1.0X
+before 1582, noop                                  2820           2820           0         35.5          28.2       1.0X
+after 1582                                        22228          22228           0          4.5         222.3       0.1X
+before 1582                                       22590          22590           0          4.4         225.9       0.1X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 11.0.6+10-post-Ubuntu-1ubuntu118.04.1 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load timestamps from ORC:                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1900, vec off                               14112          14128          17          7.1         141.1       1.0X
-after 1900, vec on                                 7347           7459         134         13.6          73.5       1.9X
-before 1900, vec off                              15170          15192          27          6.6         151.7       0.9X
-before 1900, vec on                                8280           8312          52         12.1          82.8       1.7X
+after 1582, vec off                               13591          13658          59          7.4         135.9       1.0X
+after 1582, vec on                                 7399           7488         126         13.5          74.0       1.8X
+before 1582, vec off                              14065          14096          30          7.1         140.7       1.0X
+before 1582, vec on                                7950           8127         249         12.6          79.5       1.7X
 
 
diff --git a/sql/core/benchmarks/DateTimeRebaseBenchmark-results.txt b/sql/core/benchmarks/DateTimeRebaseBenchmark-results.txt
index a32a1ad8af89e..050950571511d 100644
--- a/sql/core/benchmarks/DateTimeRebaseBenchmark-results.txt
+++ b/sql/core/benchmarks/DateTimeRebaseBenchmark-results.txt
@@ -2,93 +2,93 @@
 Rebasing dates/timestamps in Parquet datasource
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save dates to parquet:                    Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                  23088          23088           0          4.3         230.9       1.0X
-before 1582, noop                                 10782          10782           0          9.3         107.8       2.1X
-after 1582, rebase off                            34821          34821           0          2.9         348.2       0.7X
-after 1582, rebase on                             35040          35040           0          2.9         350.4       0.7X
-before 1582, rebase off                           22151          22151           0          4.5         221.5       1.0X
-before 1582, rebase on                            24677          24677           0          4.1         246.8       0.9X
+after 1582, noop                                  24114          24114           0          4.1         241.1       1.0X
+before 1582, noop                                 10250          10250           0          9.8         102.5       2.4X
+after 1582, rebase off                            36672          36672           0          2.7         366.7       0.7X
+after 1582, rebase on                             37123          37123           0          2.7         371.2       0.6X
+before 1582, rebase off                           21925          21925           0          4.6         219.2       1.1X
+before 1582, rebase on                            22341          22341           0          4.5         223.4       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load dates from parquet:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off, rebase off                   13559          13650          79          7.4         135.6       1.0X
-after 1582, vec off, rebase on                    12942          12973          28          7.7         129.4       1.0X
-after 1582, vec on, rebase off                     3657           3689          29         27.3          36.6       3.7X
-after 1582, vec on, rebase on                      3859           3902          53         25.9          38.6       3.5X
-before 1582, vec off, rebase off                  12588          12607          17          7.9         125.9       1.1X
-before 1582, vec off, rebase on                   13396          13420          25          7.5         134.0       1.0X
-before 1582, vec on, rebase off                    3631           3650          19         27.5          36.3       3.7X
-before 1582, vec on, rebase on                     4706           4755          77         21.3          47.1       2.9X
+after 1582, vec off, rebase off                   12456          12601         126          8.0         124.6       1.0X
+after 1582, vec off, rebase on                    13299          13336          32          7.5         133.0       0.9X
+after 1582, vec on, rebase off                     3623           3660          40         27.6          36.2       3.4X
+after 1582, vec on, rebase on                      5160           5177          15         19.4          51.6       2.4X
+before 1582, vec off, rebase off                  13177          13264          76          7.6         131.8       0.9X
+before 1582, vec off, rebase on                   14102          14149          46          7.1         141.0       0.9X
+before 1582, vec on, rebase off                    3649           3670          34         27.4          36.5       3.4X
+before 1582, vec on, rebase on                     5652           5667          15         17.7          56.5       2.2X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save timestamps to parquet:               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1900, noop                                   2681           2681           0         37.3          26.8       1.0X
-before 1900, noop                                  3051           3051           0         32.8          30.5       0.9X
-after 1900, rebase off                            16901          16901           0          5.9         169.0       0.2X
-after 1900, rebase on                             19725          19725           0          5.1         197.3       0.1X
-before 1900, rebase off                           16900          16900           0          5.9         169.0       0.2X
-before 1900, rebase on                            20381          20381           0          4.9         203.8       0.1X
+after 1582, noop                                   2871           2871           0         34.8          28.7       1.0X
+before 1582, noop                                  2753           2753           0         36.3          27.5       1.0X
+after 1582, rebase off                            15927          15927           0          6.3         159.3       0.2X
+after 1582, rebase on                             19138          19138           0          5.2         191.4       0.1X
+before 1582, rebase off                           16137          16137           0          6.2         161.4       0.2X
+before 1582, rebase on                            19584          19584           0          5.1         195.8       0.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load timestamps from parquet:             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1900, vec off, rebase off                   15236          15291          62          6.6         152.4       1.0X
-after 1900, vec off, rebase on                    17832          18047         187          5.6         178.3       0.9X
-after 1900, vec on, rebase off                     4875           4901          31         20.5          48.7       3.1X
-after 1900, vec on, rebase on                      5354           5386          37         18.7          53.5       2.8X
-before 1900, vec off, rebase off                  15229          15338         108          6.6         152.3       1.0X
-before 1900, vec off, rebase on                   18626          18668          44          5.4         186.3       0.8X
-before 1900, vec on, rebase off                    4968           4975           6         20.1          49.7       3.1X
-before 1900, vec on, rebase on                     9913           9932          16         10.1          99.1       1.5X
+after 1582, vec off, rebase off                   14995          15047          47          6.7         150.0       1.0X
+after 1582, vec off, rebase on                    18111          18146          37          5.5         181.1       0.8X
+after 1582, vec on, rebase off                     4837           4873          44         20.7          48.4       3.1X
+after 1582, vec on, rebase on                      9542           9669         111         10.5          95.4       1.6X
+before 1582, vec off, rebase off                  14993          15090          94          6.7         149.9       1.0X
+before 1582, vec off, rebase on                   18675          18712          64          5.4         186.7       0.8X
+before 1582, vec on, rebase off                    4908           4923          15         20.4          49.1       3.1X
+before 1582, vec on, rebase on                    10128          10148          19          9.9         101.3       1.5X
 
 
 ================================================================================================
 Rebasing dates/timestamps in ORC datasource
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save dates to ORC:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, noop                                  22942          22942           0          4.4         229.4       1.0X
-before 1582, noop                                 11035          11035           0          9.1         110.4       2.1X
-after 1582                                        31341          31341           0          3.2         313.4       0.7X
-before 1582                                       20376          20376           0          4.9         203.8       1.1X
+after 1582, noop                                  23977          23977           0          4.2         239.8       1.0X
+before 1582, noop                                 10094          10094           0          9.9         100.9       2.4X
+after 1582                                        33115          33115           0          3.0         331.2       0.7X
+before 1582                                       19430          19430           0          5.1         194.3       1.2X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load dates from ORC:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1582, vec off                               10361          10378          29          9.7         103.6       1.0X
-after 1582, vec on                                 3820           3828          11         26.2          38.2       2.7X
-before 1582, vec off                              10709          10720          13          9.3         107.1       1.0X
-before 1582, vec on                                4136           4153          15         24.2          41.4       2.5X
+after 1582, vec off                               10217          10241          21          9.8         102.2       1.0X
+after 1582, vec on                                 3671           3691          31         27.2          36.7       2.8X
+before 1582, vec off                              10800          10874         114          9.3         108.0       0.9X
+before 1582, vec on                                4118           4165          74         24.3          41.2       2.5X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Save timestamps to ORC:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1900, noop                                   2888           2888           0         34.6          28.9       1.0X
-before 1900, noop                                  2823           2823           0         35.4          28.2       1.0X
-after 1900                                        19790          19790           0          5.1         197.9       0.1X
-before 1900                                       20774          20774           0          4.8         207.7       0.1X
+after 1582, noop                                   2691           2691           0         37.2          26.9       1.0X
+before 1582, noop                                  2743           2743           0         36.5          27.4       1.0X
+after 1582                                        21409          21409           0          4.7         214.1       0.1X
+before 1582                                       22554          22554           0          4.4         225.5       0.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
+OpenJDK 64-Bit Server VM 1.8.0_242-8u242-b08-0ubuntu3~18.04-b08 on Linux 4.15.0-1063-aws
 Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
 Load timestamps from ORC:                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-after 1900, vec off                               14649          14687          38          6.8         146.5       1.0X
-after 1900, vec on                                 7850           7937         130         12.7          78.5       1.9X
-before 1900, vec off                              15354          15417         108          6.5         153.5       1.0X
-before 1900, vec on                                8382           8408          22         11.9          83.8       1.7X
+after 1582, vec off                               14752          14855         103          6.8         147.5       1.0X
+after 1582, vec on                                 8146           8185          34         12.3          81.5       1.8X
+before 1582, vec off                              15247          15294          46          6.6         152.5       1.0X
+before 1582, vec on                                8414           8466          52         11.9          84.1       1.8X
 
 
diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
index 7ae60f22aa790..cfb873ff37379 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
@@ -423,8 +423,15 @@ private void readIntBatch(int rowId, int num, WritableColumnVector column) throw
           num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
     } else if (column.dataType() == DataTypes.DateType ) {
       if (rebaseDateTime) {
-        defColumn.readIntegersWithRebase(
-          num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
+        for (int i = 0; i < num; i++) {
+          if (defColumn.readInteger() == maxDefLevel) {
+            column.putInt(
+              rowId + i,
+              RebaseDateTime.rebaseJulianToGregorianDays(dataColumn.readInteger()));
+          } else {
+            column.putNull(rowId + i);
+          }
+        }
       } else {
         defColumn.readIntegers(
            num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
@@ -442,8 +449,15 @@ private void readLongBatch(int rowId, int num, WritableColumnVector column) thro
         num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
     } else if (originalType == OriginalType.TIMESTAMP_MICROS) {
       if (rebaseDateTime) {
-        defColumn.readLongsWithRebase(
-          num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
+        for (int i = 0; i < num; i++) {
+          if (defColumn.readInteger() == maxDefLevel) {
+            column.putLong(
+              rowId + i,
+              RebaseDateTime.rebaseJulianToGregorianMicros(dataColumn.readLong()));
+          } else {
+            column.putNull(rowId + i);
+          }
+        }
       } else {
         defColumn.readLongs(
           num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedPlainValuesReader.java b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedPlainValuesReader.java
index 2ed2e11b60c03..c62dc3d86386e 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedPlainValuesReader.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedPlainValuesReader.java
@@ -22,7 +22,6 @@
 
 import org.apache.parquet.bytes.ByteBufferInputStream;
 import org.apache.parquet.io.ParquetDecodingException;
-import org.apache.spark.sql.catalyst.util.RebaseDateTime;
 import org.apache.spark.sql.execution.vectorized.WritableColumnVector;
 
 import org.apache.parquet.column.values.ValuesReader;
@@ -82,33 +81,6 @@ public final void readIntegers(int total, WritableColumnVector c, int rowId) {
     }
   }
 
-  // A fork of `readIntegers` to rebase the date values. For performance reasons, this method
-  // iterates the values twice: check if we need to rebase first, then go to the optimized branch
-  // if rebase is not needed.
-  @Override
-  public final void readIntegersWithRebase(int total, WritableColumnVector c, int rowId) {
-    int requiredBytes = total * 4;
-    ByteBuffer buffer = getBuffer(requiredBytes);
-    boolean rebase = false;
-    for (int i = 0; i < total; i += 1) {
-      rebase |= buffer.getInt(buffer.position() + i * 4) < RebaseDateTime.lastSwitchJulianDay();
-    }
-    if (rebase) {
-      for (int i = 0; i < total; i += 1) {
-        c.putInt(rowId + i, RebaseDateTime.rebaseJulianToGregorianDays(buffer.getInt()));
-      }
-    } else {
-      if (buffer.hasArray()) {
-        int offset = buffer.arrayOffset() + buffer.position();
-        c.putIntsLittleEndian(rowId, total, buffer.array(), offset);
-      } else {
-        for (int i = 0; i < total; i += 1) {
-          c.putInt(rowId + i, buffer.getInt());
-        }
-      }
-    }
-  }
-
   @Override
   public final void readLongs(int total, WritableColumnVector c, int rowId) {
     int requiredBytes = total * 8;
@@ -124,33 +96,6 @@ public final void readLongs(int total, WritableColumnVector c, int rowId) {
     }
   }
 
-  // A fork of `readLongs` to rebase the timestamp values. For performance reasons, this method
-  // iterates the values twice: check if we need to rebase first, then go to the optimized branch
-  // if rebase is not needed.
-  @Override
-  public final void readLongsWithRebase(int total, WritableColumnVector c, int rowId) {
-    int requiredBytes = total * 8;
-    ByteBuffer buffer = getBuffer(requiredBytes);
-    boolean rebase = false;
-    for (int i = 0; i < total; i += 1) {
-      rebase |= buffer.getLong(buffer.position() + i * 8) < RebaseDateTime.lastSwitchJulianTs();
-    }
-    if (rebase) {
-      for (int i = 0; i < total; i += 1) {
-        c.putLong(rowId + i, RebaseDateTime.rebaseJulianToGregorianMicros(buffer.getLong()));
-      }
-    } else {
-      if (buffer.hasArray()) {
-        int offset = buffer.arrayOffset() + buffer.position();
-        c.putLongsLittleEndian(rowId, total, buffer.array(), offset);
-      } else {
-        for (int i = 0; i < total; i += 1) {
-          c.putLong(rowId + i, buffer.getLong());
-        }
-      }
-    }
-  }
-
   @Override
   public final void readFloats(int total, WritableColumnVector c, int rowId) {
     int requiredBytes = total * 4;
diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedRleValuesReader.java b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedRleValuesReader.java
index 4d72a33fcf774..fe3d31ae8e746 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedRleValuesReader.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedRleValuesReader.java
@@ -26,7 +26,6 @@
 import org.apache.parquet.io.ParquetDecodingException;
 import org.apache.parquet.io.api.Binary;
 
-import org.apache.spark.sql.catalyst.util.RebaseDateTime;
 import org.apache.spark.sql.execution.vectorized.WritableColumnVector;
 
 import java.io.IOException;
@@ -204,43 +203,6 @@ public void readIntegers(
     }
   }
 
-  // A fork of `readIntegers`, which rebases the date int value (days) before filling
-  // the Spark column vector.
-  public void readIntegersWithRebase(
-      int total,
-      WritableColumnVector c,
-      int rowId,
-      int level,
-      VectorizedValuesReader data) throws IOException {
-    int left = total;
-    while (left > 0) {
-      if (this.currentCount == 0) this.readNextGroup();
-      int n = Math.min(left, this.currentCount);
-      switch (mode) {
-        case RLE:
-          if (currentValue == level) {
-            data.readIntegersWithRebase(n, c, rowId);
-          } else {
-            c.putNulls(rowId, n);
-          }
-          break;
-        case PACKED:
-          for (int i = 0; i < n; ++i) {
-            if (currentBuffer[currentBufferIdx++] == level) {
-              c.putInt(rowId + i,
-                RebaseDateTime.rebaseJulianToGregorianDays(data.readInteger()));
-            } else {
-              c.putNull(rowId + i);
-            }
-          }
-          break;
-      }
-      rowId += n;
-      left -= n;
-      currentCount -= n;
-    }
-  }
-
   // TODO: can this code duplication be removed without a perf penalty?
   public void readBooleans(
       int total,
@@ -380,43 +342,6 @@ public void readLongs(
     }
   }
 
-  // A fork of `readLongs`, which rebases the timestamp long value (microseconds) before filling
-  // the Spark column vector.
-  public void readLongsWithRebase(
-      int total,
-      WritableColumnVector c,
-      int rowId,
-      int level,
-      VectorizedValuesReader data) throws IOException {
-    int left = total;
-    while (left > 0) {
-      if (this.currentCount == 0) this.readNextGroup();
-      int n = Math.min(left, this.currentCount);
-      switch (mode) {
-        case RLE:
-          if (currentValue == level) {
-            data.readLongsWithRebase(n, c, rowId);
-          } else {
-            c.putNulls(rowId, n);
-          }
-          break;
-        case PACKED:
-          for (int i = 0; i < n; ++i) {
-            if (currentBuffer[currentBufferIdx++] == level) {
-              c.putLong(rowId + i,
-                RebaseDateTime.rebaseJulianToGregorianMicros(data.readLong()));
-            } else {
-              c.putNull(rowId + i);
-            }
-          }
-          break;
-      }
-      rowId += n;
-      left -= n;
-      currentCount -= n;
-    }
-  }
-
   public void readFloats(
       int total,
       WritableColumnVector c,
@@ -583,11 +508,6 @@ public void readIntegers(int total, WritableColumnVector c, int rowId) {
     }
   }
 
-  @Override
-  public void readIntegersWithRebase(int total, WritableColumnVector c, int rowId) {
-    throw new UnsupportedOperationException("only readInts is valid.");
-  }
-
   @Override
   public byte readByte() {
     throw new UnsupportedOperationException("only readInts is valid.");
@@ -603,11 +523,6 @@ public void readLongs(int total, WritableColumnVector c, int rowId) {
     throw new UnsupportedOperationException("only readInts is valid.");
   }
 
-  @Override
-  public void readLongsWithRebase(int total, WritableColumnVector c, int rowId) {
-    throw new UnsupportedOperationException("only readInts is valid.");
-  }
-
   @Override
   public void readBinary(int total, WritableColumnVector c, int rowId) {
     throw new UnsupportedOperationException("only readInts is valid.");
diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedValuesReader.java b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedValuesReader.java
index 809ac44cc8272..57d92ae27ece8 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedValuesReader.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedValuesReader.java
@@ -40,9 +40,7 @@ public interface VectorizedValuesReader {
   void readBooleans(int total, WritableColumnVector c, int rowId);
   void readBytes(int total, WritableColumnVector c, int rowId);
   void readIntegers(int total, WritableColumnVector c, int rowId);
-  void readIntegersWithRebase(int total, WritableColumnVector c, int rowId);
   void readLongs(int total, WritableColumnVector c, int rowId);
-  void readLongsWithRebase(int total, WritableColumnVector c, int rowId);
   void readFloats(int total, WritableColumnVector c, int rowId);
   void readDoubles(int total, WritableColumnVector c, int rowId);
   void readBinary(int total, WritableColumnVector c, int rowId);
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeRebaseBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeRebaseBenchmark.scala
index 7968836a00d0f..077ac28c149ee 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeRebaseBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeRebaseBenchmark.scala
@@ -49,15 +49,15 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
       .select($"seconds".cast("timestamp").as("ts"))
   }
 
-  private def genTsAfter1900(cardinality: Int): DataFrame = {
-    val start = LocalDateTime.of(1900, 1, 31, 0, 0, 0)
+  private def genTsAfter1582(cardinality: Int): DataFrame = {
+    val start = LocalDateTime.of(1582, 10, 15, 0, 0, 0)
     val end = LocalDateTime.of(3000, 1, 1, 0, 0, 0)
     genTs(cardinality, start, end)
   }
 
-  private def genTsBefore1900(cardinality: Int): DataFrame = {
+  private def genTsBefore1582(cardinality: Int): DataFrame = {
     val start = LocalDateTime.of(10, 1, 1, 0, 0, 0)
-    val end = LocalDateTime.of(1900, 1, 1, 0, 0, 0)
+    val end = LocalDateTime.of(1580, 1, 1, 0, 0, 0)
     genTs(cardinality, start, end)
   }
 
@@ -71,35 +71,34 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
   }
 
   private def genDateAfter1582(cardinality: Int): DataFrame = {
-    val start = LocalDate.of(1582, 10, 31)
+    val start = LocalDate.of(1582, 10, 15)
     val end = LocalDate.of(3000, 1, 1)
     genDate(cardinality, start, end)
   }
 
   private def genDateBefore1582(cardinality: Int): DataFrame = {
     val start = LocalDate.of(10, 1, 1)
-    val end = LocalDate.of(1580, 10, 1)
+    val end = LocalDate.of(1580, 1, 1)
     genDate(cardinality, start, end)
   }
 
-  private def genDF(cardinality: Int, dateTime: String, modernDates: Boolean): DataFrame = {
-    (dateTime, modernDates) match {
+  private def genDF(cardinality: Int, dateTime: String, after1582: Boolean): DataFrame = {
+    (dateTime, after1582) match {
       case ("date", true) => genDateAfter1582(cardinality)
       case ("date", false) => genDateBefore1582(cardinality)
-      case ("timestamp", true) => genTsAfter1900(cardinality)
-      case ("timestamp", false) => genTsBefore1900(cardinality)
+      case ("timestamp", true) => genTsAfter1582(cardinality)
+      case ("timestamp", false) => genTsBefore1582(cardinality)
       case _ => throw new IllegalArgumentException(
-        s"cardinality = $cardinality dateTime = $dateTime modernDates = $modernDates")
+        s"cardinality = $cardinality dateTime = $dateTime after1582 = $after1582")
     }
   }
 
   private def benchmarkInputs(benchmark: Benchmark, rowsNum: Int, dateTime: String): Unit = {
-    val year = if (dateTime == "date") 1582 else 1900
-    benchmark.addCase(s"after $year, noop", 1) { _ =>
-      genDF(rowsNum, dateTime, modernDates = true).noop()
+    benchmark.addCase("after 1582, noop", 1) { _ =>
+      genDF(rowsNum, dateTime, after1582 = true).noop()
     }
-    benchmark.addCase(s"before $year, noop", 1) { _ =>
-      genDF(rowsNum, dateTime, modernDates = false).noop()
+    benchmark.addCase("before 1582, noop", 1) { _ =>
+      genDF(rowsNum, dateTime, after1582 = false).noop()
     }
   }
 
@@ -108,26 +107,23 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
   }
 
   private def caseName(
-      modernDates: Boolean,
-      dateTime: String,
+      after1582: Boolean,
       rebase: Option[Boolean] = None,
       vec: Option[Boolean] = None): String = {
-    val period = if (modernDates) "after" else "before"
-    val year = if (dateTime == "date") 1582 else 1900
+    val period = if (after1582) "after" else "before"
     val vecFlag = vec.map(flagToStr).map(flag => s", vec $flag").getOrElse("")
     val rebaseFlag = rebase.map(flagToStr).map(flag => s", rebase $flag").getOrElse("")
-    s"$period $year$vecFlag$rebaseFlag"
+    s"$period 1582$vecFlag$rebaseFlag"
   }
 
   private def getPath(
       basePath: File,
       dateTime: String,
-      modernDates: Boolean,
+      after1582: Boolean,
       rebase: Option[Boolean] = None): String = {
-    val period = if (modernDates) "after" else "before"
-    val year = if (dateTime == "date") 1582 else 1900
+    val period = if (after1582) "after" else "before"
     val rebaseFlag = rebase.map(flagToStr).map(flag => s"_$flag").getOrElse("")
-    basePath.getAbsolutePath + s"/${dateTime}_${period}_$year$rebaseFlag"
+    basePath.getAbsolutePath + s"/${dateTime}_${period}_1582$rebaseFlag"
   }
 
   override def runBenchmarkSuite(mainArgs: Array[String]): Unit = {
@@ -143,16 +139,16 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
                 rowsNum,
                 output = output)
               benchmarkInputs(benchmark, rowsNum, dateTime)
-              Seq(true, false).foreach { modernDates =>
+              Seq(true, false).foreach { after1582 =>
                 Seq(false, true).foreach { rebase =>
-                  benchmark.addCase(caseName(modernDates, dateTime, Some(rebase)), 1) { _ =>
+                  benchmark.addCase(caseName(after1582, Some(rebase)), 1) { _ =>
                     withSQLConf(
                       SQLConf.LEGACY_PARQUET_REBASE_DATETIME_IN_WRITE.key -> rebase.toString) {
-                      genDF(rowsNum, dateTime, modernDates)
+                      genDF(rowsNum, dateTime, after1582)
                         .write
                         .mode("overwrite")
                         .format("parquet")
-                        .save(getPath(path, dateTime, modernDates, Some(rebase)))
+                        .save(getPath(path, dateTime, after1582, Some(rebase)))
                     }
                   }
                 }
@@ -161,15 +157,16 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
 
               val benchmark2 = new Benchmark(
                 s"Load ${dateTime}s from parquet", rowsNum, output = output)
-              Seq(true, false).foreach { modernDates =>
+              Seq(true, false).foreach { after1582 =>
                 Seq(false, true).foreach { vec =>
                   Seq(false, true).foreach { rebase =>
-                    val name = caseName(modernDates, dateTime, Some(rebase), Some(vec))
-                    benchmark2.addCase(name, 3) { _ =>
-                      withSQLConf(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> vec.toString) {
+                    benchmark2.addCase(caseName(after1582, Some(rebase), Some(vec)), 3) { _ =>
+                      withSQLConf(
+                        SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> vec.toString,
+                        SQLConf.LEGACY_PARQUET_REBASE_DATETIME_IN_READ.key -> rebase.toString) {
                         spark.read
                           .format("parquet")
-                          .load(getPath(path, dateTime, modernDates, Some(rebase)))
+                          .load(getPath(path, dateTime, after1582, Some(rebase)))
                           .noop()
                       }
                     }
@@ -186,13 +183,13 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
             Seq("date", "timestamp").foreach { dateTime =>
               val benchmark = new Benchmark(s"Save ${dateTime}s to ORC", rowsNum, output = output)
               benchmarkInputs(benchmark, rowsNum, dateTime)
-              Seq(true, false).foreach { modernDates =>
-                benchmark.addCase(caseName(modernDates, dateTime), 1) { _ =>
-                  genDF(rowsNum, dateTime, modernDates)
+              Seq(true, false).foreach { after1582 =>
+                benchmark.addCase(caseName(after1582), 1) { _ =>
+                  genDF(rowsNum, dateTime, after1582)
                     .write
                     .mode("overwrite")
                     .format("orc")
-                    .save(getPath(path, dateTime, modernDates))
+                    .save(getPath(path, dateTime, after1582))
                 }
               }
               benchmark.run()
@@ -201,14 +198,14 @@ object DateTimeRebaseBenchmark extends SqlBasedBenchmark {
                 s"Load ${dateTime}s from ORC",
                 rowsNum,
                 output = output)
-              Seq(true, false).foreach { modernDates =>
+              Seq(true, false).foreach { after1582 =>
                 Seq(false, true).foreach { vec =>
-                  benchmark2.addCase(caseName(modernDates, dateTime, vec = Some(vec)), 3) { _ =>
+                  benchmark2.addCase(caseName(after1582, vec = Some(vec)), 3) { _ =>
                     withSQLConf(SQLConf.ORC_VECTORIZED_READER_ENABLED.key -> vec.toString) {
                       spark
                         .read
                         .format("orc")
-                        .load(getPath(path, dateTime, modernDates))
+                        .load(getPath(path, dateTime, after1582))
                         .noop()
                     }
                   }

From d3d175b8c1f66ae0b20d6a203cab3988c5457002 Mon Sep 17 00:00:00 2001
From: Huaxin Gao <huaxing@us.ibm.com>
Date: Mon, 4 May 2020 11:23:35 -0700
Subject: [PATCH 16/19] Revert "[SPARK-31626][SQL] Port HIVE-10415:
 hive.start.cleanup.scratchdir configuration is not taking effect"

This reverts commit 065871c30f8d505125f5197aa8ce6691ee8af92b.
---
 .../hive/thriftserver/HiveThriftServer2.scala |  3 --
 .../HiveThriftServer2Suites.scala             | 33 -------------------
 2 files changed, 36 deletions(-)

diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala
index f9f2ceeed8a75..f15193b0dc3cc 100644
--- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala
+++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala
@@ -20,7 +20,6 @@ package org.apache.spark.sql.hive.thriftserver
 import java.util.Locale
 import java.util.concurrent.atomic.AtomicBoolean
 
-import org.apache.hadoop.hive.common.ServerUtils
 import org.apache.hadoop.hive.conf.HiveConf
 import org.apache.hadoop.hive.conf.HiveConf.ConfVars
 import org.apache.hive.service.cli.thrift.{ThriftBinaryCLIService, ThriftHttpCLIService}
@@ -102,8 +101,6 @@ object HiveThriftServer2 extends Logging {
       SparkSQLEnv.sqlContext.sessionState.newHadoopConf())
 
     try {
-      // Cleanup the scratch dir before starting
-      ServerUtils.cleanUpScratchDir(executionHive.conf)
       val server = new HiveThriftServer2(SparkSQLEnv.sqlContext)
       server.init(executionHive.conf)
       server.start()
diff --git a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
index 0cec63460814c..639dc4d13f673 100644
--- a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
+++ b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
@@ -924,39 +924,6 @@ class SingleSessionSuite extends HiveThriftJdbcTest {
   }
 }
 
-class HiveThriftCleanUpScratchDirSuite extends HiveThriftJdbcTest{
-  var tempScratchDir: File = _
-
-  override protected def beforeAll(): Unit = {
-    tempScratchDir = Utils.createTempDir()
-    tempScratchDir.setWritable(true, false)
-    assert(tempScratchDir.list().isEmpty)
-    new File(tempScratchDir.getAbsolutePath + File.separator + "SPARK-31626").createNewFile()
-    assert(tempScratchDir.list().nonEmpty)
-    super.beforeAll()
-  }
-
-  override def mode: ServerMode.Value = ServerMode.binary
-
-  override protected def extraConf: Seq[String] =
-    s" --hiveconf ${ConfVars.HIVE_START_CLEANUP_SCRATCHDIR}=true " ::
-       s"--hiveconf ${ConfVars.SCRATCHDIR}=${tempScratchDir.getAbsolutePath}" :: Nil
-
-  test("Cleanup the Hive scratchdir when starting the Hive Server") {
-    assert(!tempScratchDir.exists())
-    withJdbcStatement() { statement =>
-      val rs = statement.executeQuery("SELECT id FROM range(1)")
-      assert(rs.next())
-      assert(rs.getLong(1) === 0L)
-    }
-  }
-
-  override protected def afterAll(): Unit = {
-    Utils.deleteRecursively(tempScratchDir)
-    super.afterAll()
-  }
-}
-
 class HiveThriftHttpServerSuite extends HiveThriftJdbcTest {
   override def mode: ServerMode.Value = ServerMode.http
 

From 24eb041a098a86d5f8a6137c25ba32a5eb141eba Mon Sep 17 00:00:00 2001
From: Huaxin Gao <huaxing@us.ibm.com>
Date: Mon, 4 May 2020 11:23:37 -0700
Subject: [PATCH 17/19] Revert "[SPARK-31267][SQL] Flaky test:
 WholeStageCodegenSparkSubmitSuite.Generated code on driver should not embed
 platform-specific constant"

This reverts commit da32137d37d032a3fd2507b229e3f494cc612246.
---
 .../scala/org/apache/spark/deploy/SparkSubmitSuite.scala     | 5 ++---
 .../sql/execution/WholeStageCodegenSparkSubmitSuite.scala    | 3 +--
 2 files changed, 3 insertions(+), 5 deletions(-)

diff --git a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala
index fd2d1f56ed9b6..1f3243400a918 100644
--- a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala
@@ -31,7 +31,6 @@ import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.fs.{FileStatus, FSDataInputStream, Path}
 import org.scalatest.{BeforeAndAfterEach, Matchers}
 import org.scalatest.concurrent.{Signaler, ThreadSignaler, TimeLimits}
-import org.scalatest.time.Span
 import org.scalatest.time.SpanSugar._
 
 import org.apache.spark._
@@ -1420,7 +1419,7 @@ object SparkSubmitSuite extends SparkFunSuite with TimeLimits {
   implicit val defaultSignaler: Signaler = ThreadSignaler
 
   // NOTE: This is an expensive operation in terms of time (10 seconds+). Use sparingly.
-  def runSparkSubmit(args: Seq[String], root: String = "..", timeout: Span = 1.minute): Unit = {
+  def runSparkSubmit(args: Seq[String], root: String = ".."): Unit = {
     val sparkHome = sys.props.getOrElse("spark.test.home", fail("spark.test.home is not set!"))
     val sparkSubmitFile = if (Utils.isWindows) {
       new File(s"$root\\bin\\spark-submit.cmd")
@@ -1433,7 +1432,7 @@ object SparkSubmitSuite extends SparkFunSuite with TimeLimits {
       Map("SPARK_TESTING" -> "1", "SPARK_HOME" -> sparkHome))
 
     try {
-      val exitCode = failAfter(timeout) { process.waitFor() }
+      val exitCode = failAfter(1.minute) { process.waitFor() }
       if (exitCode != 0) {
         fail(s"Process returned with exit code $exitCode. See the log4j logs for more detail.")
       }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSparkSubmitSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSparkSubmitSuite.scala
index c5a01de911962..f6814d8ff8a3d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSparkSubmitSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSparkSubmitSuite.scala
@@ -19,7 +19,6 @@ package org.apache.spark.sql.execution
 
 import org.scalatest.{Assertions, BeforeAndAfterEach, Matchers}
 import org.scalatest.concurrent.TimeLimits
-import org.scalatest.time.SpanSugar._
 
 import org.apache.spark.{SparkFunSuite, TestUtils}
 import org.apache.spark.deploy.SparkSubmitSuite
@@ -51,7 +50,7 @@ class WholeStageCodegenSparkSubmitSuite extends SparkFunSuite
       "--conf", "spark.executor.extraJavaOptions=-XX:+UseCompressedOops",
       "--conf", "spark.sql.adaptive.enabled=false",
       unusedJar.toString)
-    SparkSubmitSuite.runSparkSubmit(argsForSparkSubmit, "../..", 3.minutes)
+    SparkSubmitSuite.runSparkSubmit(argsForSparkSubmit, "../..")
   }
 }
 

From 8f9e9b2dc167c275543f1584695118a4b231f87e Mon Sep 17 00:00:00 2001
From: Huaxin Gao <huaxing@us.ibm.com>
Date: Mon, 4 May 2020 11:23:40 -0700
Subject: [PATCH 18/19] Revert "[SPARK-31527][SQL][TESTS][FOLLOWUP] Fix the
 number of rows in `DateTimeBenchmark`"

This reverts commit d8a2fa0e5b45d99ff0cbd4c869242fedb8541b55.
---
 .../DateTimeBenchmark-jdk11-results.txt       | 474 +++++++++---------
 .../benchmarks/DateTimeBenchmark-results.txt  | 474 +++++++++---------
 .../benchmark/DateTimeBenchmark.scala         |   2 +-
 3 files changed, 475 insertions(+), 475 deletions(-)

diff --git a/sql/core/benchmarks/DateTimeBenchmark-jdk11-results.txt b/sql/core/benchmarks/DateTimeBenchmark-jdk11-results.txt
index 61b4c762a752e..1004bcf1aa286 100644
--- a/sql/core/benchmarks/DateTimeBenchmark-jdk11-results.txt
+++ b/sql/core/benchmarks/DateTimeBenchmark-jdk11-results.txt
@@ -2,456 +2,456 @@
 datetime +/- interval
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 datetime +/- interval:                    Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date + interval(m)                                 1485           1567         116          6.7         148.5       1.0X
-date + interval(m, d)                              1504           1510           9          6.6         150.4       1.0X
-date + interval(m, d, ms)                          7000           7013          18          1.4         700.0       0.2X
-date - interval(m)                                 1466           1478          17          6.8         146.6       1.0X
-date - interval(m, d)                              1533           1534           1          6.5         153.3       1.0X
-date - interval(m, d, ms)                          7014           7019           7          1.4         701.4       0.2X
-timestamp + interval(m)                            3062           3064           3          3.3         306.2       0.5X
-timestamp + interval(m, d)                         3133           3136           5          3.2         313.3       0.5X
-timestamp + interval(m, d, ms)                     3401           3402           3          2.9         340.1       0.4X
-timestamp - interval(m)                            3025           3037          17          3.3         302.5       0.5X
-timestamp - interval(m, d)                         3083           3120          51          3.2         308.3       0.5X
-timestamp - interval(m, d, ms)                     3371           3379          11          3.0         337.1       0.4X
+date + interval(m)                                  919            933          22          0.0   306237514.3       1.0X
+date + interval(m, d)                               910            916           9          0.0   303338619.0       1.0X
+date + interval(m, d, ms)                          3912           3923          16          0.0  1303942791.7       0.2X
+date - interval(m)                                  883            887           6          0.0   294268789.3       1.0X
+date - interval(m, d)                               898            911          18          0.0   299453403.0       1.0X
+date - interval(m, d, ms)                          3937           3944          11          0.0  1312269472.0       0.2X
+timestamp + interval(m)                            2226           2236          14          0.0   741972014.3       0.4X
+timestamp + interval(m, d)                         2264           2274          13          0.0   754709121.0       0.4X
+timestamp + interval(m, d, ms)                     2202           2223          30          0.0   734001075.0       0.4X
+timestamp - interval(m)                            1992           2005          17          0.0   664152744.7       0.5X
+timestamp - interval(m, d)                         2069           2075           9          0.0   689631159.0       0.4X
+timestamp - interval(m, d, ms)                     2240           2244           6          0.0   746538728.0       0.4X
 
 
 ================================================================================================
 Extract components
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 cast to timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast to timestamp wholestage off                    339            339           1         29.5          33.9       1.0X
-cast to timestamp wholestage on                     330            337           9         30.3          33.0       1.0X
+cast to timestamp wholestage off                    178            180           3         56.1          17.8       1.0X
+cast to timestamp wholestage on                     189            192           4         53.0          18.9       0.9X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 year of timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-year of timestamp wholestage off                   1226           1237          15          8.2         122.6       1.0X
-year of timestamp wholestage on                    1230           1242           9          8.1         123.0       1.0X
+year of timestamp wholestage off                    760            761           1         13.2          76.0       1.0X
+year of timestamp wholestage on                     731            741          10         13.7          73.1       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 quarter of timestamp:                     Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-quarter of timestamp wholestage off                1602           1606           7          6.2         160.2       1.0X
-quarter of timestamp wholestage on                 1511           1514           3          6.6         151.1       1.1X
+quarter of timestamp wholestage off                1005           1013          10          9.9         100.5       1.0X
+quarter of timestamp wholestage on                  981            986           3         10.2          98.1       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 month of timestamp:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-month of timestamp wholestage off                  1227           1233           8          8.1         122.7       1.0X
-month of timestamp wholestage on                   1226           1242          28          8.2         122.6       1.0X
+month of timestamp wholestage off                   754            758           6         13.3          75.4       1.0X
+month of timestamp wholestage on                    719            729          11         13.9          71.9       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 weekofyear of timestamp:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-weekofyear of timestamp wholestage off             1965           1980          20          5.1         196.5       1.0X
-weekofyear of timestamp wholestage on              1816           1833          17          5.5         181.6       1.1X
+weekofyear of timestamp wholestage off             1085           1088           4          9.2         108.5       1.0X
+weekofyear of timestamp wholestage on              1075           1091          13          9.3         107.5       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 day of timestamp:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-day of timestamp wholestage off                    1229           1231           3          8.1         122.9       1.0X
-day of timestamp wholestage on                     1222           1230          10          8.2         122.2       1.0X
+day of timestamp wholestage off                     751            770          27         13.3          75.1       1.0X
+day of timestamp wholestage on                      735            741           7         13.6          73.5       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 dayofyear of timestamp:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofyear of timestamp wholestage off              1294           1297           4          7.7         129.4       1.0X
-dayofyear of timestamp wholestage on               1257           1264           6          8.0         125.7       1.0X
+dayofyear of timestamp wholestage off               765            769           5         13.1          76.5       1.0X
+dayofyear of timestamp wholestage on                762            770           7         13.1          76.2       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 dayofmonth of timestamp:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofmonth of timestamp wholestage off             1247           1253           8          8.0         124.7       1.0X
-dayofmonth of timestamp wholestage on              1225           1229           4          8.2         122.5       1.0X
+dayofmonth of timestamp wholestage off              780            782           2         12.8          78.0       1.0X
+dayofmonth of timestamp wholestage on               720            736          12         13.9          72.0       1.1X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 dayofweek of timestamp:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofweek of timestamp wholestage off              1416           1416           0          7.1         141.6       1.0X
-dayofweek of timestamp wholestage on               1376           1382           8          7.3         137.6       1.0X
+dayofweek of timestamp wholestage off               887            899          17         11.3          88.7       1.0X
+dayofweek of timestamp wholestage on                820            847          20         12.2          82.0       1.1X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 weekday of timestamp:                     Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-weekday of timestamp wholestage off                1350           1351           1          7.4         135.0       1.0X
-weekday of timestamp wholestage on                 1308           1318          13          7.6         130.8       1.0X
+weekday of timestamp wholestage off                 821            825           5         12.2          82.1       1.0X
+weekday of timestamp wholestage on                  802            814           9         12.5          80.2       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 hour of timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-hour of timestamp wholestage off                   1004           1007           3         10.0         100.4       1.0X
-hour of timestamp wholestage on                     928            938           7         10.8          92.8       1.1X
+hour of timestamp wholestage off                    611            622          14         16.4          61.1       1.0X
+hour of timestamp wholestage on                     571            577           8         17.5          57.1       1.1X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 minute of timestamp:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-minute of timestamp wholestage off                 1009           1020          15          9.9         100.9       1.0X
-minute of timestamp wholestage on                   933            935           2         10.7          93.3       1.1X
+minute of timestamp wholestage off                  607            615          12         16.5          60.7       1.0X
+minute of timestamp wholestage on                   573            580           6         17.5          57.3       1.1X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 second of timestamp:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-second of timestamp wholestage off                  995            995           0         10.0          99.5       1.0X
-second of timestamp wholestage on                   932            937           8         10.7          93.2       1.1X
+second of timestamp wholestage off                  615            616           2         16.3          61.5       1.0X
+second of timestamp wholestage on                   564            575           8         17.7          56.4       1.1X
 
 
 ================================================================================================
 Current date and time
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 current_date:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-current_date wholestage off                         292            316          34         34.2          29.2       1.0X
-current_date wholestage on                          270            276           6         37.0          27.0       1.1X
+current_date wholestage off                         166            169           4         60.4          16.6       1.0X
+current_date wholestage on                          150            153           3         66.7          15.0       1.1X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 current_timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-current_timestamp wholestage off                    313            328          20         31.9          31.3       1.0X
-current_timestamp wholestage on                     270            331          95         37.0          27.0       1.2X
+current_timestamp wholestage off                    179            181           2         55.8          17.9       1.0X
+current_timestamp wholestage on                     162            324         138         61.9          16.2       1.1X
 
 
 ================================================================================================
 Date arithmetic
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 cast to date:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast to date wholestage off                        1078           1081           3          9.3         107.8       1.0X
-cast to date wholestage on                         1035           1040           7          9.7         103.5       1.0X
+cast to date wholestage off                         658            661           5         15.2          65.8       1.0X
+cast to date wholestage on                          644            654          10         15.5          64.4       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 last_day:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-last_day wholestage off                            1265           1266           3          7.9         126.5       1.0X
-last_day wholestage on                             1236           1246          10          8.1         123.6       1.0X
+last_day wholestage off                             768            772           5         13.0          76.8       1.0X
+last_day wholestage on                              737            750          12         13.6          73.7       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 next_day:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-next_day wholestage off                            1118           1118           1          8.9         111.8       1.0X
-next_day wholestage on                             1085           1090           8          9.2         108.5       1.0X
+next_day wholestage off                             691            704          17         14.5          69.1       1.0X
+next_day wholestage on                              664            676          10         15.1          66.4       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_add:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_add wholestage off                            1052           1054           4          9.5         105.2       1.0X
-date_add wholestage on                             1046           1051           6          9.6         104.6       1.0X
+date_add wholestage off                             646            646           0         15.5          64.6       1.0X
+date_add wholestage on                              623            640          13         16.1          62.3       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_sub:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_sub wholestage off                            1075           1075           0          9.3         107.5       1.0X
-date_sub wholestage on                             1043           1046           3          9.6         104.3       1.0X
+date_sub wholestage off                             638            645           9         15.7          63.8       1.0X
+date_sub wholestage on                              618            629           8         16.2          61.8       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 add_months:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-add_months wholestage off                          1409           1409           0          7.1         140.9       1.0X
-add_months wholestage on                           1448           1453           4          6.9         144.8       1.0X
+add_months wholestage off                           892            896           5         11.2          89.2       1.0X
+add_months wholestage on                            926            938           7         10.8          92.6       1.0X
 
 
 ================================================================================================
 Formatting dates
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 format date:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-format date wholestage off                         5373           5390          24          1.9         537.3       1.0X
-format date wholestage on                          5337           5346          12          1.9         533.7       1.0X
+format date wholestage off                         3395           3439          62          2.9         339.5       1.0X
+format date wholestage on                          3418           3438          14          2.9         341.8       1.0X
 
 
 ================================================================================================
 Formatting timestamps
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 from_unixtime:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-from_unixtime wholestage off                       7302           7308           9          1.4         730.2       1.0X
-from_unixtime wholestage on                        7298           7319          16          1.4         729.8       1.0X
+from_unixtime wholestage off                       4565           4592          38          2.2         456.5       1.0X
+from_unixtime wholestage on                        4608           4635          32          2.2         460.8       1.0X
 
 
 ================================================================================================
 Convert timestamps
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 from_utc_timestamp:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-from_utc_timestamp wholestage off                  1322           1355          48          7.6         132.2       1.0X
-from_utc_timestamp wholestage on                   1290           1294           5          7.8         129.0       1.0X
+from_utc_timestamp wholestage off                   801            807           9         12.5          80.1       1.0X
+from_utc_timestamp wholestage on                    819            830           7         12.2          81.9       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to_utc_timestamp:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_utc_timestamp wholestage off                    1692           1705          18          5.9         169.2       1.0X
-to_utc_timestamp wholestage on                     1653           1657           4          6.1         165.3       1.0X
+to_utc_timestamp wholestage off                    1108           1114           8          9.0         110.8       1.0X
+to_utc_timestamp wholestage on                     1067           1078          13          9.4         106.7       1.0X
 
 
 ================================================================================================
 Intervals
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 cast interval:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast interval wholestage off                        340            356          22         29.4          34.0       1.0X
-cast interval wholestage on                         293            296           2         34.1          29.3       1.2X
+cast interval wholestage off                        211            213           2         47.4          21.1       1.0X
+cast interval wholestage on                         185            188           3         54.1          18.5       1.1X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 datediff:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-datediff wholestage off                            1843           1862          28          5.4         184.3       1.0X
-datediff wholestage on                             1766           1780          16          5.7         176.6       1.0X
+datediff wholestage off                            1120           1120           1          8.9         112.0       1.0X
+datediff wholestage on                             1174           1205          19          8.5         117.4       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 months_between:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-months_between wholestage off                      5856           5858           2          1.7         585.6       1.0X
-months_between wholestage on                       5799           5815          14          1.7         579.9       1.0X
+months_between wholestage off                      3669           3688          26          2.7         366.9       1.0X
+months_between wholestage on                       3687           3819         181          2.7         368.7       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 window:                                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-window wholestage off                              2017           2147         183          0.5        2017.4       1.0X
-window wholestage on                              47789          47910          91          0.0       47788.6       0.0X
+window wholestage off                              1147           1148           1          0.9        1146.6       1.0X
+window wholestage on                              16997          17207         226          0.1       16996.7       0.1X
 
 
 ================================================================================================
 Truncation
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc YEAR:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YEAR wholestage off                     2689           2689           1          3.7         268.9       1.0X
-date_trunc YEAR wholestage on                      2655           2670          17          3.8         265.5       1.0X
+date_trunc YEAR wholestage off                     1824           1859          50          5.5         182.4       1.0X
+date_trunc YEAR wholestage on                      1844           1942          71          5.4         184.4       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc YYYY:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YYYY wholestage off                     2698           2700           3          3.7         269.8       1.0X
-date_trunc YYYY wholestage on                      2654           2660           6          3.8         265.4       1.0X
+date_trunc YYYY wholestage off                     1808           1815          11          5.5         180.8       1.0X
+date_trunc YYYY wholestage on                      1833           1864          49          5.5         183.3       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc YY:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YY wholestage off                       2692           2697           7          3.7         269.2       1.0X
-date_trunc YY wholestage on                        2653           2662           7          3.8         265.3       1.0X
+date_trunc YY wholestage off                       1867           1883          23          5.4         186.7       1.0X
+date_trunc YY wholestage on                        1843           1861          15          5.4         184.3       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc MON:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MON wholestage off                      2752           2756           6          3.6         275.2       1.0X
-date_trunc MON wholestage on                       2666           2675          15          3.8         266.6       1.0X
+date_trunc MON wholestage off                      1845           1858          18          5.4         184.5       1.0X
+date_trunc MON wholestage on                       1830           1893          42          5.5         183.0       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc MONTH:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MONTH wholestage off                    2743           2746           4          3.6         274.3       1.0X
-date_trunc MONTH wholestage on                     2667           2673           8          3.7         266.7       1.0X
+date_trunc MONTH wholestage off                    1822           1855          47          5.5         182.2       1.0X
+date_trunc MONTH wholestage on                     1832           1863          20          5.5         183.2       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc MM:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MM wholestage off                       2741           2741           1          3.6         274.1       1.0X
-date_trunc MM wholestage on                        2670           2678           7          3.7         267.0       1.0X
+date_trunc MM wholestage off                       1843           1848           7          5.4         184.3       1.0X
+date_trunc MM wholestage on                        1886           1905          14          5.3         188.6       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc DAY:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc DAY wholestage off                      2338           2342           6          4.3         233.8       1.0X
-date_trunc DAY wholestage on                       2269           2277           7          4.4         226.9       1.0X
+date_trunc DAY wholestage off                      1542           1545           4          6.5         154.2       1.0X
+date_trunc DAY wholestage on                       1610           1616           5          6.2         161.0       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc DD:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc DD wholestage off                       2324           2325           1          4.3         232.4       1.0X
-date_trunc DD wholestage on                        2270           2273           2          4.4         227.0       1.0X
+date_trunc DD wholestage off                       1521           1529          11          6.6         152.1       1.0X
+date_trunc DD wholestage on                        1595           1611          21          6.3         159.5       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc HOUR:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc HOUR wholestage off                     2325           2326           1          4.3         232.5       1.0X
-date_trunc HOUR wholestage on                      2284           2295           8          4.4         228.4       1.0X
+date_trunc HOUR wholestage off                     1496           1543          67          6.7         149.6       1.0X
+date_trunc HOUR wholestage on                      1567           1594          18          6.4         156.7       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc MINUTE:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MINUTE wholestage off                    407            408           0         24.5          40.7       1.0X
-date_trunc MINUTE wholestage on                     382            386           3         26.1          38.2       1.1X
+date_trunc MINUTE wholestage off                    230            230           1         43.5          23.0       1.0X
+date_trunc MINUTE wholestage on                     288            295           7         34.7          28.8       0.8X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc SECOND:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc SECOND wholestage off                    404            404           1         24.8          40.4       1.0X
-date_trunc SECOND wholestage on                     386            390           4         25.9          38.6       1.0X
+date_trunc SECOND wholestage off                    247            249           4         40.5          24.7       1.0X
+date_trunc SECOND wholestage on                     297            314          12         33.6          29.7       0.8X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc WEEK:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc WEEK wholestage off                     2693           2694           2          3.7         269.3       1.0X
-date_trunc WEEK wholestage on                      2619           2629          10          3.8         261.9       1.0X
+date_trunc WEEK wholestage off                     1786           1788           3          5.6         178.6       1.0X
+date_trunc WEEK wholestage on                      1786           1832          46          5.6         178.6       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc QUARTER:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc QUARTER wholestage off                  3454           3466          17          2.9         345.4       1.0X
-date_trunc QUARTER wholestage on                   3384           3404          24          3.0         338.4       1.0X
+date_trunc QUARTER wholestage off                  2319           2365          66          4.3         231.9       1.0X
+date_trunc QUARTER wholestage on                   2424           2551         182          4.1         242.4       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc year:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc year wholestage off                           339            340           1         29.5          33.9       1.0X
-trunc year wholestage on                            337            347           9         29.7          33.7       1.0X
+trunc year wholestage off                           180            189          12         55.5          18.0       1.0X
+trunc year wholestage on                            271            277           5         36.9          27.1       0.7X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc yyyy:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc yyyy wholestage off                           347            348           2         28.8          34.7       1.0X
-trunc yyyy wholestage on                            334            335           2         29.9          33.4       1.0X
+trunc yyyy wholestage off                           189            191           4         52.9          18.9       1.0X
+trunc yyyy wholestage on                            276            284           6         36.2          27.6       0.7X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc yy:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc yy wholestage off                             339            346          11         29.5          33.9       1.0X
-trunc yy wholestage on                              333            338           5         30.0          33.3       1.0X
+trunc yy wholestage off                             189            190           1         52.9          18.9       1.0X
+trunc yy wholestage on                              279            294          11         35.9          27.9       0.7X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc mon:                                Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc mon wholestage off                            339            347          11         29.5          33.9       1.0X
-trunc mon wholestage on                             331            336           4         30.2          33.1       1.0X
+trunc mon wholestage off                            185            186           1         54.1          18.5       1.0X
+trunc mon wholestage on                             272            285          13         36.8          27.2       0.7X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc month:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc month wholestage off                          341            344           3         29.3          34.1       1.0X
-trunc month wholestage on                           332            338           9         30.1          33.2       1.0X
+trunc month wholestage off                          190            190           1         52.6          19.0       1.0X
+trunc month wholestage on                           293            300           4         34.1          29.3       0.6X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc mm:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc mm wholestage off                             337            338           1         29.6          33.7       1.0X
-trunc mm wholestage on                              332            336           5         30.1          33.2       1.0X
+trunc mm wholestage off                             178            182           6         56.3          17.8       1.0X
+trunc mm wholestage on                              306            312           5         32.7          30.6       0.6X
 
 
 ================================================================================================
 Parsing
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to timestamp str:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to timestamp str wholestage off                     184            187           4          5.4         183.9       1.0X
-to timestamp str wholestage on                      159            162           2          6.3         159.4       1.2X
+to timestamp str wholestage off                     111            117           8          9.0         110.9       1.0X
+to timestamp str wholestage on                      101            109           6          9.9         100.6       1.1X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to_timestamp:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_timestamp wholestage off                        1683           1689           8          0.6        1683.3       1.0X
-to_timestamp wholestage on                         1722           1725           4          0.6        1721.6       1.0X
+to_timestamp wholestage off                         735            746          15          1.4         734.9       1.0X
+to_timestamp wholestage on                          708            725          11          1.4         708.2       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to_unix_timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_unix_timestamp wholestage off                   1733           1736           4          0.6        1733.1       1.0X
-to_unix_timestamp wholestage on                    1687           1690           4          0.6        1686.6       1.0X
+to_unix_timestamp wholestage off                    718            727          12          1.4         717.9       1.0X
+to_unix_timestamp wholestage on                     739            755          12          1.4         739.1       1.0X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to date str:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to date str wholestage off                          218            220           4          4.6         217.6       1.0X
-to date str wholestage on                           213            215           2          4.7         212.6       1.0X
+to date str wholestage off                          124            125           1          8.0         124.4       1.0X
+to date str wholestage on                           134            138           3          7.5         133.9       0.9X
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to_date:                                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_date wholestage off                             3697           3699           2          0.3        3697.2       1.0X
-to_date wholestage on                              3603           3624          15          0.3        3602.7       1.0X
+to_date wholestage off                             1510           1544          48          0.7        1510.4       1.0X
+to_date wholestage on                              1544           1557          15          0.6        1544.2       1.0X
 
 
 ================================================================================================
 Conversion from/to external types
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 11.0.7+10-post-Ubuntu-2ubuntu218.04 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 11.0.5+10-LTS on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 To/from Java's date-time:                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-From java.sql.Date                                  432            436           7         11.6          86.4       1.0X
-From java.time.LocalDate                            343            347           6         14.6          68.6       1.3X
-Collect java.sql.Date                              1888           2453         971          2.6         377.6       0.2X
-Collect java.time.LocalDate                        1779           1820          42          2.8         355.7       0.2X
-From java.sql.Timestamp                             375            384           9         13.3          75.0       1.2X
-From java.time.Instant                              317            326           8         15.8          63.5       1.4X
-Collect longs                                      1338           1428         115          3.7         267.6       0.3X
-Collect java.sql.Timestamp                         1716           2014         281          2.9         343.1       0.3X
-Collect java.time.Instant                          1832           1970         122          2.7         366.5       0.2X
+From java.sql.Date                                  269            278           9         18.6          53.7       1.0X
+From java.time.LocalDate                            227            234           7         22.0          45.4       1.2X
+Collect java.sql.Date                              1164           1272         141          4.3         232.8       0.2X
+Collect java.time.LocalDate                        1070           1130          59          4.7         214.1       0.3X
+From java.sql.Timestamp                             246            248           2         20.3          49.2       1.1X
+From java.time.Instant                              214            216           2         23.4          42.8       1.3X
+Collect longs                                       814            831          15          6.1         162.7       0.3X
+Collect java.sql.Timestamp                         1016           1096          78          4.9         203.2       0.3X
+Collect java.time.Instant                          1012           1093          86          4.9         202.4       0.3X
 
 
diff --git a/sql/core/benchmarks/DateTimeBenchmark-results.txt b/sql/core/benchmarks/DateTimeBenchmark-results.txt
index 3ef2f922f95bf..dba6c909be637 100644
--- a/sql/core/benchmarks/DateTimeBenchmark-results.txt
+++ b/sql/core/benchmarks/DateTimeBenchmark-results.txt
@@ -2,456 +2,456 @@
 datetime +/- interval
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 datetime +/- interval:                    Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date + interval(m)                                 1613           1622          13          6.2         161.3       1.0X
-date + interval(m, d)                              1729           1752          32          5.8         172.9       0.9X
-date + interval(m, d, ms)                          6421           6424           5          1.6         642.1       0.3X
-date - interval(m)                                 1441           1443           2          6.9         144.1       1.1X
-date - interval(m, d)                              1687           1689           2          5.9         168.7       1.0X
-date - interval(m, d, ms)                          6617           6625          11          1.5         661.7       0.2X
-timestamp + interval(m)                            2713           2733          28          3.7         271.3       0.6X
-timestamp + interval(m, d)                         3027           3032           8          3.3         302.7       0.5X
-timestamp + interval(m, d, ms)                     3501           3509          12          2.9         350.1       0.5X
-timestamp - interval(m)                            2892           2895           4          3.5         289.2       0.6X
-timestamp - interval(m, d)                         3190           3196           9          3.1         319.0       0.5X
-timestamp - interval(m, d, ms)                     3497           3500           5          2.9         349.7       0.5X
+date + interval(m)                                 1003           1012          13          0.0   334353721.7       1.0X
+date + interval(m, d)                              1154           1174          29          0.0   384575202.7       0.9X
+date + interval(m, d, ms)                          4338           4366          40          0.0  1446002701.3       0.2X
+date - interval(m)                                  850            858           8          0.0   283424914.7       1.2X
+date - interval(m, d)                              1017           1031          19          0.0   339034354.7       1.0X
+date - interval(m, d, ms)                          4699           4717          25          0.0  1566218686.3       0.2X
+timestamp + interval(m)                            2044           2046           3          0.0   681382301.0       0.5X
+timestamp + interval(m, d)                         2215           2249          48          0.0   738464286.7       0.5X
+timestamp + interval(m, d, ms)                     2053           2063          13          0.0   684393366.0       0.5X
+timestamp - interval(m)                            1668           1677          12          0.0   556138256.7       0.6X
+timestamp - interval(m, d)                         1865           1882          25          0.0   621574795.3       0.5X
+timestamp - interval(m, d, ms)                     2075           2077           3          0.0   691569937.3       0.5X
 
 
 ================================================================================================
 Extract components
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 cast to timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast to timestamp wholestage off                    321            323           2         31.1          32.1       1.0X
-cast to timestamp wholestage on                     294            306          10         34.0          29.4       1.1X
+cast to timestamp wholestage off                    192            192           0         52.2          19.2       1.0X
+cast to timestamp wholestage on                     163            166           3         61.3          16.3       1.2X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 year of timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-year of timestamp wholestage off                   1235           1242           9          8.1         123.5       1.0X
-year of timestamp wholestage on                    1208           1216           8          8.3         120.8       1.0X
+year of timestamp wholestage off                    743            745           4         13.5          74.3       1.0X
+year of timestamp wholestage on                     708            715           5         14.1          70.8       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 quarter of timestamp:                     Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-quarter of timestamp wholestage off                1415           1424          12          7.1         141.5       1.0X
-quarter of timestamp wholestage on                 1338           1341           4          7.5         133.8       1.1X
+quarter of timestamp wholestage off                 848            857          12         11.8          84.8       1.0X
+quarter of timestamp wholestage on                  803            813           6         12.5          80.3       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 month of timestamp:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-month of timestamp wholestage off                  1224           1225           1          8.2         122.4       1.0X
-month of timestamp wholestage on                   1193           1202           8          8.4         119.3       1.0X
+month of timestamp wholestage off                   740            745           7         13.5          74.0       1.0X
+month of timestamp wholestage on                    703            710           5         14.2          70.3       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 weekofyear of timestamp:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-weekofyear of timestamp wholestage off             1864           1866           3          5.4         186.4       1.0X
-weekofyear of timestamp wholestage on              1827           1840           7          5.5         182.7       1.0X
+weekofyear of timestamp wholestage off             1162           1182          28          8.6         116.2       1.0X
+weekofyear of timestamp wholestage on              1093           1102           9          9.2         109.3       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 day of timestamp:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-day of timestamp wholestage off                    1209           1211           2          8.3         120.9       1.0X
-day of timestamp wholestage on                     1191           1194           6          8.4         119.1       1.0X
+day of timestamp wholestage off                     742            748           9         13.5          74.2       1.0X
+day of timestamp wholestage on                      703            713           7         14.2          70.3       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 dayofyear of timestamp:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofyear of timestamp wholestage off              1270           1271           2          7.9         127.0       1.0X
-dayofyear of timestamp wholestage on               1241           1250          12          8.1         124.1       1.0X
+dayofyear of timestamp wholestage off               791            799          11         12.6          79.1       1.0X
+dayofyear of timestamp wholestage on                732            744           9         13.7          73.2       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 dayofmonth of timestamp:                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofmonth of timestamp wholestage off             1236           1250          20          8.1         123.6       1.0X
-dayofmonth of timestamp wholestage on              1193           1195           3          8.4         119.3       1.0X
+dayofmonth of timestamp wholestage off              738            752          20         13.6          73.8       1.0X
+dayofmonth of timestamp wholestage on               695            712           9         14.4          69.5       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 dayofweek of timestamp:                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-dayofweek of timestamp wholestage off              1402           1405           4          7.1         140.2       1.0X
-dayofweek of timestamp wholestage on               1352           1359           7          7.4         135.2       1.0X
+dayofweek of timestamp wholestage off               854            856           3         11.7          85.4       1.0X
+dayofweek of timestamp wholestage on                819            839          16         12.2          81.9       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 weekday of timestamp:                     Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-weekday of timestamp wholestage off                1346           1347           2          7.4         134.6       1.0X
-weekday of timestamp wholestage on                 1294           1299           7          7.7         129.4       1.0X
+weekday of timestamp wholestage off                 816            821           7         12.3          81.6       1.0X
+weekday of timestamp wholestage on                  788            800           8         12.7          78.8       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 hour of timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-hour of timestamp wholestage off                   1000           1008          11         10.0         100.0       1.0X
-hour of timestamp wholestage on                     936            941           6         10.7          93.6       1.1X
+hour of timestamp wholestage off                    595            595           1         16.8          59.5       1.0X
+hour of timestamp wholestage on                     533            541          10         18.8          53.3       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 minute of timestamp:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-minute of timestamp wholestage off                  969            976          10         10.3          96.9       1.0X
-minute of timestamp wholestage on                   933            936           4         10.7          93.3       1.0X
+minute of timestamp wholestage off                  585            588           4         17.1          58.5       1.0X
+minute of timestamp wholestage on                   532            545          11         18.8          53.2       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 second of timestamp:                      Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-second of timestamp wholestage off                 1002           1005           3         10.0         100.2       1.0X
-second of timestamp wholestage on                   935            938           2         10.7          93.5       1.1X
+second of timestamp wholestage off                  579            589          13         17.3          57.9       1.0X
+second of timestamp wholestage on                   529            537           6         18.9          52.9       1.1X
 
 
 ================================================================================================
 Current date and time
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 current_date:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-current_date wholestage off                         308            316          11         32.5          30.8       1.0X
-current_date wholestage on                          265            275          12         37.8          26.5       1.2X
+current_date wholestage off                         171            174           4         58.4          17.1       1.0X
+current_date wholestage on                          152            155           3         65.6          15.2       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 current_timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-current_timestamp wholestage off                    307            312           7         32.6          30.7       1.0X
-current_timestamp wholestage on                     263            268           5         38.1          26.3       1.2X
+current_timestamp wholestage off                    178            181           4         56.2          17.8       1.0X
+current_timestamp wholestage on                     138            149           7         72.6          13.8       1.3X
 
 
 ================================================================================================
 Date arithmetic
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 cast to date:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast to date wholestage off                        1061           1065           5          9.4         106.1       1.0X
-cast to date wholestage on                          985            991          11         10.2          98.5       1.1X
+cast to date wholestage off                         630            640          14         15.9          63.0       1.0X
+cast to date wholestage on                          591            594           5         16.9          59.1       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 last_day:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-last_day wholestage off                            1261           1262           1          7.9         126.1       1.0X
-last_day wholestage on                             1223           1235          12          8.2         122.3       1.0X
+last_day wholestage off                             759            778          26         13.2          75.9       1.0X
+last_day wholestage on                              727            736           9         13.8          72.7       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 next_day:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-next_day wholestage off                            1114           1119           7          9.0         111.4       1.0X
-next_day wholestage on                             1034           1038           3          9.7         103.4       1.1X
+next_day wholestage off                             649            659          15         15.4          64.9       1.0X
+next_day wholestage on                              628            629           1         15.9          62.8       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_add:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_add wholestage off                            1059           1076          25          9.4         105.9       1.0X
-date_add wholestage on                             1012           1021           9          9.9         101.2       1.0X
+date_add wholestage off                             621            622           1         16.1          62.1       1.0X
+date_add wholestage on                              600            606           6         16.7          60.0       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_sub:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_sub wholestage off                            1046           1046           0          9.6         104.6       1.0X
-date_sub wholestage on                             1019           1023           3          9.8         101.9       1.0X
+date_sub wholestage off                             611            626          21         16.4          61.1       1.0X
+date_sub wholestage on                              588            600           7         17.0          58.8       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 add_months:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-add_months wholestage off                          1392           1393           1          7.2         139.2       1.0X
-add_months wholestage on                           1335           1346          14          7.5         133.5       1.0X
+add_months wholestage off                           843            845           2         11.9          84.3       1.0X
+add_months wholestage on                            818            831          11         12.2          81.8       1.0X
 
 
 ================================================================================================
 Formatting dates
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 format date:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-format date wholestage off                         5959           5994          50          1.7         595.9       1.0X
-format date wholestage on                          5991           6008          28          1.7         599.1       1.0X
+format date wholestage off                         3557           3569          18          2.8         355.7       1.0X
+format date wholestage on                          3564           3588          17          2.8         356.4       1.0X
 
 
 ================================================================================================
 Formatting timestamps
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 from_unixtime:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-from_unixtime wholestage off                       8851           8872          29          1.1         885.1       1.0X
-from_unixtime wholestage on                        8855           8872          10          1.1         885.5       1.0X
+from_unixtime wholestage off                       4875           4887          17          2.1         487.5       1.0X
+from_unixtime wholestage on                        4845           4870          16          2.1         484.5       1.0X
 
 
 ================================================================================================
 Convert timestamps
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 from_utc_timestamp:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-from_utc_timestamp wholestage off                  1105           1107           2          9.0         110.5       1.0X
-from_utc_timestamp wholestage on                   1072           1084          11          9.3         107.2       1.0X
+from_utc_timestamp wholestage off                   665            671           8         15.0          66.5       1.0X
+from_utc_timestamp wholestage on                    654            672          14         15.3          65.4       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to_utc_timestamp:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_utc_timestamp wholestage off                    1531           1534           3          6.5         153.1       1.0X
-to_utc_timestamp wholestage on                     1451           1463          14          6.9         145.1       1.1X
+to_utc_timestamp wholestage off                     982            983           1         10.2          98.2       1.0X
+to_utc_timestamp wholestage on                      877            889           9         11.4          87.7       1.1X
 
 
 ================================================================================================
 Intervals
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 cast interval:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-cast interval wholestage off                        360            366           8         27.8          36.0       1.0X
-cast interval wholestage on                         286            292           7         35.0          28.6       1.3X
+cast interval wholestage off                        200            206           9         50.1          20.0       1.0X
+cast interval wholestage on                         157            163           5         63.6          15.7       1.3X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 datediff:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-datediff wholestage off                            1809           1814           8          5.5         180.9       1.0X
-datediff wholestage on                             1742           1751           8          5.7         174.2       1.0X
+datediff wholestage off                            1065           1068           4          9.4         106.5       1.0X
+datediff wholestage on                             1028           1047          15          9.7         102.8       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 months_between:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-months_between wholestage off                      5007           5007           1          2.0         500.7       1.0X
-months_between wholestage on                       4957           4980          35          2.0         495.7       1.0X
+months_between wholestage off                      3102           3111          13          3.2         310.2       1.0X
+months_between wholestage on                       2970           3028          46          3.4         297.0       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 window:                                   Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-window wholestage off                              1945           2027         116          0.5        1945.3       1.0X
-window wholestage on                              45637          45648           8          0.0       45637.2       0.0X
+window wholestage off                              1142           1154          16          0.9        1142.2       1.0X
+window wholestage on                              14817          15049         257          0.1       14816.5       0.1X
 
 
 ================================================================================================
 Truncation
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc YEAR:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YEAR wholestage off                     2463           2465           2          4.1         246.3       1.0X
-date_trunc YEAR wholestage on                      2406           2409           3          4.2         240.6       1.0X
+date_trunc YEAR wholestage off                     1516           1518           2          6.6         151.6       1.0X
+date_trunc YEAR wholestage on                      1458           1468           9          6.9         145.8       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc YYYY:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YYYY wholestage off                     2462           2463           1          4.1         246.2       1.0X
-date_trunc YYYY wholestage on                      2407           2411           6          4.2         240.7       1.0X
+date_trunc YYYY wholestage off                     1535           1535           1          6.5         153.5       1.0X
+date_trunc YYYY wholestage on                      1453           1461           7          6.9         145.3       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc YY:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc YY wholestage off                       2462           2466           6          4.1         246.2       1.0X
-date_trunc YY wholestage on                        2401           2406           4          4.2         240.1       1.0X
+date_trunc YY wholestage off                       1561           1567           9          6.4         156.1       1.0X
+date_trunc YY wholestage on                        1452           1467          16          6.9         145.2       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc MON:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MON wholestage off                      2437           2437           0          4.1         243.7       1.0X
-date_trunc MON wholestage on                       2416           2421           6          4.1         241.6       1.0X
+date_trunc MON wholestage off                      1522           1531          13          6.6         152.2       1.0X
+date_trunc MON wholestage on                       1458           1467           7          6.9         145.8       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc MONTH:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MONTH wholestage off                    2430           2437           9          4.1         243.0       1.0X
-date_trunc MONTH wholestage on                     2417           2423           5          4.1         241.7       1.0X
+date_trunc MONTH wholestage off                    1518           1519           0          6.6         151.8       1.0X
+date_trunc MONTH wholestage on                     1452           1465          16          6.9         145.2       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc MM:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MM wholestage off                       2429           2431           3          4.1         242.9       1.0X
-date_trunc MM wholestage on                        2417           2421           4          4.1         241.7       1.0X
+date_trunc MM wholestage off                       1531           1532           1          6.5         153.1       1.0X
+date_trunc MM wholestage on                        1453           1463           8          6.9         145.3       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc DAY:                           Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc DAY wholestage off                      2074           2075           2          4.8         207.4       1.0X
-date_trunc DAY wholestage on                       2001           2010          16          5.0         200.1       1.0X
+date_trunc DAY wholestage off                      1287           1309          31          7.8         128.7       1.0X
+date_trunc DAY wholestage on                       1310           1337          16          7.6         131.0       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc DD:                            Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc DD wholestage off                       2067           2067           0          4.8         206.7       1.0X
-date_trunc DD wholestage on                        2000           2003           3          5.0         200.0       1.0X
+date_trunc DD wholestage off                       1322           1328           9          7.6         132.2       1.0X
+date_trunc DD wholestage on                        1282           1324          28          7.8         128.2       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc HOUR:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc HOUR wholestage off                     2074           2084          14          4.8         207.4       1.0X
-date_trunc HOUR wholestage on                      2057           2067          10          4.9         205.7       1.0X
+date_trunc HOUR wholestage off                     1379           1393          20          7.3         137.9       1.0X
+date_trunc HOUR wholestage on                      1288           1302          11          7.8         128.8       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc MINUTE:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc MINUTE wholestage off                    362            364           3         27.6          36.2       1.0X
-date_trunc MINUTE wholestage on                     319            333          14         31.3          31.9       1.1X
+date_trunc MINUTE wholestage off                    243            245           2         41.2          24.3       1.0X
+date_trunc MINUTE wholestage on                     213            219           8         47.0          21.3       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc SECOND:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc SECOND wholestage off                    361            366           7         27.7          36.1       1.0X
-date_trunc SECOND wholestage on                     324            341          23         30.9          32.4       1.1X
+date_trunc SECOND wholestage off                    238            245          11         42.1          23.8       1.0X
+date_trunc SECOND wholestage on                     201            210           9         49.7          20.1       1.2X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc WEEK:                          Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc WEEK wholestage off                     2385           2393          11          4.2         238.5       1.0X
-date_trunc WEEK wholestage on                      2313           2322           6          4.3         231.3       1.0X
+date_trunc WEEK wholestage off                     1443           1477          49          6.9         144.3       1.0X
+date_trunc WEEK wholestage on                      1491           1516          17          6.7         149.1       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 date_trunc QUARTER:                       Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-date_trunc QUARTER wholestage off                  3278           3280           2          3.1         327.8       1.0X
-date_trunc QUARTER wholestage on                   3228           3234           8          3.1         322.8       1.0X
+date_trunc QUARTER wholestage off                  2017           2039          32          5.0         201.7       1.0X
+date_trunc QUARTER wholestage on                   1966           2005          36          5.1         196.6       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc year:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc year wholestage off                           328            331           4         30.5          32.8       1.0X
-trunc year wholestage on                            286            295           9         35.0          28.6       1.1X
+trunc year wholestage off                           206            206           1         48.6          20.6       1.0X
+trunc year wholestage on                            175            178           2         57.2          17.5       1.2X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc yyyy:                               Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc yyyy wholestage off                           317            319           3         31.5          31.7       1.0X
-trunc yyyy wholestage on                            283            287           6         35.3          28.3       1.1X
+trunc yyyy wholestage off                           188            189           2         53.2          18.8       1.0X
+trunc yyyy wholestage on                            176            180           4         56.9          17.6       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc yy:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc yy wholestage off                             321            321           0         31.1          32.1       1.0X
-trunc yy wholestage on                              284            293          11         35.2          28.4       1.1X
+trunc yy wholestage off                             191            191           0         52.4          19.1       1.0X
+trunc yy wholestage on                              175            180           4         57.0          17.5       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc mon:                                Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc mon wholestage off                            318            319           1         31.4          31.8       1.0X
-trunc mon wholestage on                             283            287           4         35.4          28.3       1.1X
+trunc mon wholestage off                            203            205           3         49.3          20.3       1.0X
+trunc mon wholestage on                             183            186           2         54.8          18.3       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc month:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc month wholestage off                          319            321           3         31.3          31.9       1.0X
-trunc month wholestage on                           286            293           7         35.0          28.6       1.1X
+trunc month wholestage off                          199            199           0         50.3          19.9       1.0X
+trunc month wholestage on                           177            179           2         56.4          17.7       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 trunc mm:                                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-trunc mm wholestage off                             317            319           2         31.5          31.7       1.0X
-trunc mm wholestage on                              282            285           3         35.4          28.2       1.1X
+trunc mm wholestage off                             198            198           1         50.5          19.8       1.0X
+trunc mm wholestage on                              180            183           3         55.7          18.0       1.1X
 
 
 ================================================================================================
 Parsing
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to timestamp str:                         Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to timestamp str wholestage off                     219            220           0          4.6         219.4       1.0X
-to timestamp str wholestage on                      214            218           6          4.7         214.1       1.0X
+to timestamp str wholestage off                     138            139           2          7.2         138.2       1.0X
+to timestamp str wholestage on                      129            138           7          7.8         128.9       1.1X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to_timestamp:                             Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_timestamp wholestage off                        1912           1913           2          0.5        1912.0       1.0X
-to_timestamp wholestage on                         1671           1675           7          0.6        1670.8       1.1X
+to_timestamp wholestage off                         885            889           5          1.1         885.3       1.0X
+to_timestamp wholestage on                          854            866          10          1.2         854.0       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to_unix_timestamp:                        Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_unix_timestamp wholestage off                   1761           1763           3          0.6        1761.1       1.0X
-to_unix_timestamp wholestage on                    1695           1697           2          0.6        1695.4       1.0X
+to_unix_timestamp wholestage off                    848            856          12          1.2         848.1       1.0X
+to_unix_timestamp wholestage on                     826            850          18          1.2         826.4       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to date str:                              Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to date str wholestage off                          267            272           7          3.7         266.9       1.0X
-to date str wholestage on                           266            267           2          3.8         265.8       1.0X
+to date str wholestage off                          167            171           5          6.0         167.2       1.0X
+to date str wholestage on                           165            173           4          6.1         165.0       1.0X
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 to_date:                                  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-to_date wholestage off                             3705           3743          55          0.3        3704.6       1.0X
-to_date wholestage on                              3736           3746          11          0.3        3736.4       1.0X
+to_date wholestage off                             1612           1633          31          0.6        1611.7       1.0X
+to_date wholestage on                              1588           1605          19          0.6        1588.2       1.0X
 
 
 ================================================================================================
 Conversion from/to external types
 ================================================================================================
 
-OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.4
+Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
 To/from Java's date-time:                 Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
 ------------------------------------------------------------------------------------------------------------------------
-From java.sql.Date                                  400            406           6         12.5          80.1       1.0X
-From java.time.LocalDate                            343            349           7         14.6          68.6       1.2X
-Collect java.sql.Date                              1904           2739        1170          2.6         380.9       0.2X
-Collect java.time.LocalDate                        1477           1495          19          3.4         295.3       0.3X
-From java.sql.Timestamp                             376            388          10         13.3          75.2       1.1X
-From java.time.Instant                              237            239           3         21.1          47.4       1.7X
-Collect longs                                      1258           1356         111          4.0         251.7       0.3X
-Collect java.sql.Timestamp                         1878           1937          64          2.7         375.6       0.2X
-Collect java.time.Instant                          1667           1904         238          3.0         333.4       0.2X
+From java.sql.Date                                  245            247           1         20.4          49.0       1.0X
+From java.time.LocalDate                            228            233           4         21.9          45.6       1.1X
+Collect java.sql.Date                              1239           1361         209          4.0         247.9       0.2X
+Collect java.time.LocalDate                        1049           1107          54          4.8         209.8       0.2X
+From java.sql.Timestamp                             247            252           4         20.2          49.5       1.0X
+From java.time.Instant                              156            158           3         32.1          31.2       1.6X
+Collect longs                                       854            910          59          5.9         170.8       0.3X
+Collect java.sql.Timestamp                         1133           1140          12          4.4         226.6       0.2X
+Collect java.time.Instant                          1108           1159          74          4.5         221.7       0.2X
 
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeBenchmark.scala
index f56efa3bba600..0034819b58893 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DateTimeBenchmark.scala
@@ -61,7 +61,7 @@ object DateTimeBenchmark extends SqlBasedBenchmark {
       withSQLConf(SQLConf.SESSION_LOCAL_TIMEZONE.key -> LA.getId) {
         val N = 10000000
         runBenchmark("datetime +/- interval") {
-          val benchmark = new Benchmark("datetime +/- interval", N, output = output)
+          val benchmark = new Benchmark("datetime +/- interval", 3, output = output)
           val ts = "cast(id as timestamp)"
           val dt = s"cast($ts as date)"
           benchmark.addCase("date + interval(m)") { _ =>

From 760decec89c9dc42eb0d1a62c45ecbdf9a69a80d Mon Sep 17 00:00:00 2001
From: Huaxin Gao <huaxing@us.ibm.com>
Date: Mon, 4 May 2020 11:23:43 -0700
Subject: [PATCH 19/19] Revert "[SPARK-31571][R] Overhaul stop/message/warning
 calls to be more canonical"

This reverts commit 0c8146a062e14042a8f865282636d157c0e4e029.
---
 R/pkg/R/DataFrame.R                   | 40 +++++++++--------
 R/pkg/R/RDD.R                         |  2 +-
 R/pkg/R/SQLContext.R                  | 17 ++++----
 R/pkg/R/client.R                      |  7 +--
 R/pkg/R/context.R                     |  8 ++--
 R/pkg/R/deserialize.R                 |  2 +-
 R/pkg/R/group.R                       |  4 +-
 R/pkg/R/install.R                     | 62 ++++++++++++++++-----------
 R/pkg/R/mllib_classification.R        |  4 +-
 R/pkg/R/mllib_stat.R                  |  3 +-
 R/pkg/R/pairRDD.R                     |  2 +-
 R/pkg/R/schema.R                      |  2 +-
 R/pkg/R/serialize.R                   |  4 +-
 R/pkg/R/sparkR.R                      |  9 ++--
 R/pkg/R/utils.R                       | 53 ++++++++++++-----------
 R/pkg/tests/fulltests/test_sparkSQL.R |  2 +-
 16 files changed, 118 insertions(+), 103 deletions(-)

diff --git a/R/pkg/R/DataFrame.R b/R/pkg/R/DataFrame.R
index 15b3ce2935427..09e831814b893 100644
--- a/R/pkg/R/DataFrame.R
+++ b/R/pkg/R/DataFrame.R
@@ -431,7 +431,7 @@ setMethod("coltypes",
                 if (is.null(type)) {
                   specialtype <- specialtypeshandle(x)
                   if (is.null(specialtype)) {
-                    stop("Unsupported data type: ", x)
+                    stop(paste("Unsupported data type: ", x))
                   }
                   type <- PRIMITIVE_TYPES[[specialtype]]
                 }
@@ -829,8 +829,8 @@ setMethod("repartitionByRange",
                 jcol <- lapply(cols, function(c) { c@jc })
                 sdf <- callJMethod(x@sdf, "repartitionByRange", numToInt(numPartitions), jcol)
               } else {
-                stop("numPartitions and col must be numeric and Column; however, got ",
-                     class(numPartitions), " and ", class(col))
+                stop(paste("numPartitions and col must be numeric and Column; however, got",
+                           class(numPartitions), "and", class(col)))
               }
             } else if (!is.null(col))  {
               # only columns are specified
@@ -839,7 +839,7 @@ setMethod("repartitionByRange",
                 jcol <- lapply(cols, function(c) { c@jc })
                 sdf <- callJMethod(x@sdf, "repartitionByRange", jcol)
               } else {
-                stop("col must be Column; however, got ", class(col))
+                stop(paste("col must be Column; however, got", class(col)))
               }
             } else if (!is.null(numPartitions)) {
               # only numPartitions is specified
@@ -1068,10 +1068,10 @@ setMethod("sample",
           signature(x = "SparkDataFrame"),
           function(x, withReplacement = FALSE, fraction, seed) {
             if (!is.numeric(fraction)) {
-              stop("fraction must be numeric; however, got ", class(fraction))
+              stop(paste("fraction must be numeric; however, got", class(fraction)))
             }
             if (!is.logical(withReplacement)) {
-              stop("withReplacement must be logical; however, got ", class(withReplacement))
+              stop(paste("withReplacement must be logical; however, got", class(withReplacement)))
             }
 
             if (!missing(seed)) {
@@ -1211,10 +1211,11 @@ setMethod("collect",
                 checkSchemaInArrow(schema(x))
                 TRUE
               }, error = function(e) {
-                warning("The conversion from Spark DataFrame to R DataFrame was attempted ",
-                        "with Arrow optimization because ",
-                        "'spark.sql.execution.arrow.sparkr.enabled' is set to true; ",
-                        "however, failed, attempting non-optimization. Reason: ", e)
+                warning(paste0("The conversion from Spark DataFrame to R DataFrame was attempted ",
+                               "with Arrow optimization because ",
+                               "'spark.sql.execution.arrow.sparkr.enabled' is set to true; ",
+                               "however, failed, attempting non-optimization. Reason: ",
+                               e))
                 FALSE
               })
             }
@@ -1507,8 +1508,8 @@ dapplyInternal <- function(x, func, schema) {
     if (inherits(schema, "structType")) {
       checkSchemaInArrow(schema)
     } else if (is.null(schema)) {
-      stop("Arrow optimization does not support 'dapplyCollect' yet. Please disable ",
-           "Arrow optimization or use 'collect' and 'dapply' APIs instead.")
+      stop(paste0("Arrow optimization does not support 'dapplyCollect' yet. Please disable ",
+                  "Arrow optimization or use 'collect' and 'dapply' APIs instead."))
     } else {
       stop("'schema' should be DDL-formatted string or structType.")
     }
@@ -2011,8 +2012,8 @@ setMethod("[", signature(x = "SparkDataFrame"),
               x
             } else {
               if (class(i) != "Column") {
-                stop("Expressions other than filtering predicates are not supported ",
-                      "in the first parameter of extract operator [ or subset() method.")
+                stop(paste0("Expressions other than filtering predicates are not supported ",
+                      "in the first parameter of extract operator [ or subset() method."))
               }
               filter(x, i)
             }
@@ -2603,17 +2604,18 @@ setMethod("join",
               if (is.null(joinType)) {
                 sdf <- callJMethod(x@sdf, "join", y@sdf, joinExpr@jc)
               } else {
-                validJoinTypes <- c("inner", "cross",
+                if (joinType %in% c("inner", "cross",
                     "outer", "full", "fullouter", "full_outer",
                     "left", "leftouter", "left_outer",
                     "right", "rightouter", "right_outer",
-                    "semi", "leftsemi", "left_semi", "anti", "leftanti", "left_anti")
-                if (joinType %in% validJoinTypes) {
+                    "semi", "left_semi", "leftsemi", "anti", "left_anti", "leftanti")) {
                   joinType <- gsub("_", "", joinType, fixed = TRUE)
                   sdf <- callJMethod(x@sdf, "join", y@sdf, joinExpr@jc, joinType)
                 } else {
-                  stop("joinType must be one of the following types: ",
-                       "'", paste(validJoinTypes, collapse = "', '"), "'")
+                  stop(paste("joinType must be one of the following types:",
+                       "'inner', 'cross', 'outer', 'full', 'fullouter', 'full_outer',",
+                       "'left', 'leftouter', 'left_outer', 'right', 'rightouter', 'right_outer',",
+                       "'semi', 'leftsemi', 'left_semi', 'anti', 'leftanti' or 'left_anti'."))
                 }
               }
             }
diff --git a/R/pkg/R/RDD.R b/R/pkg/R/RDD.R
index 7a1d157bb8a36..7ee725d90d550 100644
--- a/R/pkg/R/RDD.R
+++ b/R/pkg/R/RDD.R
@@ -947,7 +947,7 @@ setMethod("takeSample", signature(x = "RDD", withReplacement = "logical",
             MAXINT <- .Machine$integer.max
 
             if (num < 0)
-              stop("Negative number of elements requested")
+              stop(paste("Negative number of elements requested"))
 
             if (initialCount > MAXINT - 1) {
               maxSelected <- MAXINT - 1
diff --git a/R/pkg/R/SQLContext.R b/R/pkg/R/SQLContext.R
index c0ac68332ec41..1ef2641742704 100644
--- a/R/pkg/R/SQLContext.R
+++ b/R/pkg/R/SQLContext.R
@@ -34,7 +34,7 @@ getInternalType <- function(x) {
          Date = "date",
          POSIXlt = "timestamp",
          POSIXct = "timestamp",
-         stop("Unsupported type for SparkDataFrame: ", class(x)))
+         stop(paste("Unsupported type for SparkDataFrame:", class(x))))
 }
 
 #' return the SparkSession
@@ -112,9 +112,9 @@ sparkR.conf <- function(key, defaultValue) {
               error = function(e) {
                 estr <- as.character(e)
                 if (any(grepl("java.util.NoSuchElementException", estr, fixed = TRUE))) {
-                  stop("Config '", key, "' is not set")
+                  stop(paste0("Config '", key, "' is not set"))
                 } else {
-                  stop("Unknown error: ", estr)
+                  stop(paste0("Unknown error: ", estr))
                 }
               })
     } else {
@@ -208,7 +208,7 @@ getSchema <- function(schema, firstRow = NULL, rdd = NULL) {
     names <- lapply(names, function(n) {
       nn <- gsub(".", "_", n, fixed = TRUE)
       if (nn != n) {
-        warning("Use ", nn, " instead of ", n, " as column name")
+        warning(paste("Use", nn, "instead of", n, "as column name"))
       }
       nn
     })
@@ -290,9 +290,10 @@ createDataFrame <- function(data, schema = NULL, samplingRatio = 1.0,
         TRUE
       },
       error = function(e) {
-        warning("createDataFrame attempted Arrow optimization because ",
-                "'spark.sql.execution.arrow.sparkr.enabled' is set to true; however, ",
-                "failed, attempting non-optimization. Reason: ", e)
+        warning(paste0("createDataFrame attempted Arrow optimization because ",
+                       "'spark.sql.execution.arrow.sparkr.enabled' is set to true; however, ",
+                       "failed, attempting non-optimization. Reason: ",
+                       e))
         FALSE
       })
     }
@@ -325,7 +326,7 @@ createDataFrame <- function(data, schema = NULL, samplingRatio = 1.0,
   } else if (inherits(data, "RDD")) {
     rdd <- data
   } else {
-    stop("unexpected type: ", class(data))
+    stop(paste("unexpected type:", class(data)))
   }
 
   schema <- getSchema(schema, firstRow, rdd)
diff --git a/R/pkg/R/client.R b/R/pkg/R/client.R
index 797a5c7da1549..872b21443eaad 100644
--- a/R/pkg/R/client.R
+++ b/R/pkg/R/client.R
@@ -102,9 +102,10 @@ checkJavaVersion <- function() {
     javaVersionNum <- as.integer(versions[1])
   }
   if (javaVersionNum < minJavaVersion || javaVersionNum >= maxJavaVersion) {
-    stop("Java version, greater than or equal to ", minJavaVersion,
-         " and less than ", maxJavaVersion, ", is required for this ",
-         "package; found version: ", javaVersionStr)
+    stop(paste0("Java version, greater than or equal to ", minJavaVersion,
+                " and less than ", maxJavaVersion,
+                ", is required for this package; found version: ",
+                javaVersionStr))
   }
   return(javaVersionNum)
 }
diff --git a/R/pkg/R/context.R b/R/pkg/R/context.R
index e3c9d9f8793d6..d96a287f818a2 100644
--- a/R/pkg/R/context.R
+++ b/R/pkg/R/context.R
@@ -144,13 +144,13 @@ parallelize <- function(sc, coll, numSlices = 1) {
   if ((!is.list(coll) && !is.vector(coll)) || is.data.frame(coll)) {
   # nolint end
     if (is.data.frame(coll)) {
-      message("context.R: A data frame is parallelized by columns.")
+      message(paste("context.R: A data frame is parallelized by columns."))
     } else {
       if (is.matrix(coll)) {
-        message("context.R: A matrix is parallelized by elements.")
+        message(paste("context.R: A matrix is parallelized by elements."))
       } else {
-        message("context.R: parallelize() currently only supports lists and vectors. ",
-                "Calling as.list() to coerce coll into a list.")
+        message(paste("context.R: parallelize() currently only supports lists and vectors.",
+                      "Calling as.list() to coerce coll into a list."))
       }
     }
     coll <- as.list(coll)
diff --git a/R/pkg/R/deserialize.R b/R/pkg/R/deserialize.R
index 3e7c456bd548d..ca4a6e342d772 100644
--- a/R/pkg/R/deserialize.R
+++ b/R/pkg/R/deserialize.R
@@ -57,7 +57,7 @@ readTypedObject <- function(con, type) {
     "s" = readStruct(con),
     "n" = NULL,
     "j" = getJobj(readString(con)),
-    stop("Unsupported type for deserialization ", type))
+    stop(paste("Unsupported type for deserialization", type)))
 }
 
 readStringData <- function(con, len) {
diff --git a/R/pkg/R/group.R b/R/pkg/R/group.R
index 99d62240a3b2a..2b7995e1e37f6 100644
--- a/R/pkg/R/group.R
+++ b/R/pkg/R/group.R
@@ -234,8 +234,8 @@ gapplyInternal <- function(x, func, schema) {
     if (inherits(schema, "structType")) {
       checkSchemaInArrow(schema)
     } else if (is.null(schema)) {
-      stop("Arrow optimization does not support 'gapplyCollect' yet. Please disable ",
-           "Arrow optimization or use 'collect' and 'gapply' APIs instead.")
+      stop(paste0("Arrow optimization does not support 'gapplyCollect' yet. Please disable ",
+                  "Arrow optimization or use 'collect' and 'gapply' APIs instead."))
     } else {
       stop("'schema' should be DDL-formatted string or structType.")
     }
diff --git a/R/pkg/R/install.R b/R/pkg/R/install.R
index ea2c0b4c0f42f..8c5355a8324f9 100644
--- a/R/pkg/R/install.R
+++ b/R/pkg/R/install.R
@@ -89,8 +89,8 @@ install.spark <- function(hadoopVersion = "2.7", mirrorUrl = NULL,
   }
 
   if (overwrite) {
-    message("Overwrite = TRUE: download and overwrite the tar file",
-            "and Spark package directory if they exist.")
+    message(paste0("Overwrite = TRUE: download and overwrite the tar file",
+                   "and Spark package directory if they exist."))
   }
 
   releaseUrl <- Sys.getenv("SPARKR_RELEASE_DOWNLOAD_URL")
@@ -103,11 +103,12 @@ install.spark <- function(hadoopVersion = "2.7", mirrorUrl = NULL,
   # can use dir.exists(packageLocalDir) under R 3.2.0 or later
   if (!is.na(file.info(packageLocalDir)$isdir) && !overwrite) {
     if (releaseUrl != "") {
-      message(packageName, " found, setting SPARK_HOME to ", packageLocalDir)
+      message(paste(packageName, "found, setting SPARK_HOME to", packageLocalDir))
     } else {
-      message(version, " for Hadoop ",
-              if (hadoopVersion == "without") "Free build" else hadoopVersion,
-              " found, setting SPARK_HOME to ", packageLocalDir)
+      fmt <- "%s for Hadoop %s found, setting SPARK_HOME to %s"
+      msg <- sprintf(fmt, version, ifelse(hadoopVersion == "without", "Free build", hadoopVersion),
+                     packageLocalDir)
+      message(msg)
     }
     Sys.setenv(SPARK_HOME = packageLocalDir)
     return(invisible(packageLocalDir))
@@ -126,23 +127,26 @@ install.spark <- function(hadoopVersion = "2.7", mirrorUrl = NULL,
       success <- downloadUrl(releaseUrl, packageLocalPath)
       if (!success) {
         unlink(packageLocalPath)
-        stop("Fetch failed from ", releaseUrl)
+        stop(paste0("Fetch failed from ", releaseUrl))
       }
     } else {
       robustDownloadTar(mirrorUrl, version, hadoopVersion, packageName, packageLocalPath)
     }
   }
 
-  message("Installing to ", localDir)
+  message(sprintf("Installing to %s", localDir))
   # There are two ways untar can fail - untar could stop() on errors like incomplete block on file
   # or, tar command can return failure code
   success <- tryCatch(untar(tarfile = packageLocalPath, exdir = localDir) == 0,
                      error = function(e) {
-                       message(e, "\n")
+                       message(e)
+                       message()
                        FALSE
                      },
                      warning = function(w) {
-                       message(w, "\n")
+                       # Treat warning as error, add an empty line with message()
+                       message(w)
+                       message()
                        FALSE
                      })
   if (!tarExists || overwrite || !success) {
@@ -156,7 +160,7 @@ install.spark <- function(hadoopVersion = "2.7", mirrorUrl = NULL,
   if (!success) stop("Extract archive failed.")
   message("DONE.")
   Sys.setenv(SPARK_HOME = packageLocalDir)
-  message("SPARK_HOME set to ", packageLocalDir)
+  message(paste("SPARK_HOME set to", packageLocalDir))
   invisible(packageLocalDir)
 }
 
@@ -169,7 +173,7 @@ robustDownloadTar <- function(mirrorUrl, version, hadoopVersion, packageName, pa
     if (success) {
       return()
     } else {
-      message("Unable to download from mirrorUrl: ", mirrorUrl)
+      message(paste0("Unable to download from mirrorUrl: ", mirrorUrl))
     }
   } else {
     message("MirrorUrl not provided.")
@@ -197,9 +201,11 @@ robustDownloadTar <- function(mirrorUrl, version, hadoopVersion, packageName, pa
     # remove any partially downloaded file
     unlink(packageLocalPath)
     message("Unable to download from default mirror site: ", mirrorUrl)
-    stop("Unable to download Spark ", version,
-         " for Hadoop ", if (hadoopVersion == "without") "Free build" else hadoopVersion,
-         ". Please check network connection, Hadoop version, or provide other mirror sites.")
+    msg <- sprintf(paste("Unable to download Spark %s for Hadoop %s.",
+                         "Please check network connection, Hadoop version,",
+                         "or provide other mirror sites."),
+                   version, ifelse(hadoopVersion == "without", "Free build", hadoopVersion))
+    stop(msg)
   }
 }
 
@@ -216,7 +222,7 @@ getPreferredMirror <- function(version, packageName) {
     endPos <- matchInfo + attr(matchInfo, "match.length") - 2
     mirrorPreferred <- base::substr(linePreferred, startPos, endPos)
     mirrorPreferred <- paste0(mirrorPreferred, "spark")
-    message("Preferred mirror site found: ", mirrorPreferred)
+    message(sprintf("Preferred mirror site found: %s", mirrorPreferred))
   } else {
     mirrorPreferred <- NULL
   }
@@ -225,20 +231,24 @@ getPreferredMirror <- function(version, packageName) {
 
 directDownloadTar <- function(mirrorUrl, version, hadoopVersion, packageName, packageLocalPath) {
   packageRemotePath <- paste0(file.path(mirrorUrl, version, packageName), ".tgz")
-  message("Downloading ", version, " for Hadoop ",
-          if (hadoopVersion == "without") "Free build" else hadoopVersion,
-          " from:\n- ", packageRemotePath)
+  fmt <- "Downloading %s for Hadoop %s from:\n- %s"
+  msg <- sprintf(fmt, version, ifelse(hadoopVersion == "without", "Free build", hadoopVersion),
+                 packageRemotePath)
+  message(msg)
   downloadUrl(packageRemotePath, packageLocalPath)
 }
 
 downloadUrl <- function(remotePath, localPath) {
   isFail <- tryCatch(download.file(remotePath, localPath),
                      error = function(e) {
-                       message(e, "\n")
+                       message(e)
+                       message()
                        TRUE
                      },
                      warning = function(w) {
-                       message(w, "\n")
+                       # Treat warning as error, add an empty line with message()
+                       message(w)
+                       message()
                        TRUE
                      })
   !isFail
@@ -269,9 +279,9 @@ sparkCachePath <- function() {
       winAppPath <- Sys.getenv("USERPROFILE", unset = NA)
     }
     if (is.na(winAppPath)) {
-      stop("%LOCALAPPDATA% and %USERPROFILE% not found. ",
-           "Please define the environment variable ",
-           "or restart and enter an installation path in localDir.")
+      stop(paste("%LOCALAPPDATA% and %USERPROFILE% not found.",
+                   "Please define the environment variable",
+                   "or restart and enter an installation path in localDir."))
     } else {
       path <- file.path(winAppPath, "Apache", "Spark", "Cache")
     }
@@ -283,7 +293,7 @@ sparkCachePath <- function() {
         Sys.getenv("XDG_CACHE_HOME", file.path(Sys.getenv("HOME"), ".cache")), "spark")
     }
   } else {
-    stop("Unknown OS: ", .Platform$OS.type)
+    stop(sprintf("Unknown OS: %s", .Platform$OS.type))
   }
   normalizePath(path, mustWork = FALSE)
 }
@@ -312,7 +322,7 @@ installInstruction <- function(mode) {
            "If you need further help, ",
            "contact the administrators of the cluster.")
   } else {
-    stop("No instruction found for mode ", mode)
+    stop(paste0("No instruction found for ", mode, " mode."))
   }
 }
 
diff --git a/R/pkg/R/mllib_classification.R b/R/pkg/R/mllib_classification.R
index ec83b6bd406a7..5cc97ea723afc 100644
--- a/R/pkg/R/mllib_classification.R
+++ b/R/pkg/R/mllib_classification.R
@@ -337,8 +337,8 @@ setMethod("spark.logit", signature(data = "SparkDataFrame", formula = "formula")
 
               if (!is.null(lowerBoundsOnCoefficients) && (row != nrow(upperBoundsOnCoefficients)
                 || col != ncol(upperBoundsOnCoefficients))) {
-                stop("dimension of upperBoundsOnCoefficients ",
-                     "is not the same as lowerBoundsOnCoefficients")
+                stop(paste0("dimension of upperBoundsOnCoefficients ",
+                            "is not the same as lowerBoundsOnCoefficients"))
               }
 
               if (is.null(lowerBoundsOnCoefficients)) {
diff --git a/R/pkg/R/mllib_stat.R b/R/pkg/R/mllib_stat.R
index 6db4d5d4831dd..f8c3329359961 100644
--- a/R/pkg/R/mllib_stat.R
+++ b/R/pkg/R/mllib_stat.R
@@ -69,7 +69,8 @@ setMethod("spark.kstest", signature(data = "SparkDataFrame"),
           function(data, testCol = "test", nullHypothesis = c("norm"), distParams = c(0, 1)) {
             tryCatch(match.arg(nullHypothesis),
                      error = function(e) {
-                       stop("Distribution ", nullHypothesis, " is not supported.")
+                       msg <- paste("Distribution", nullHypothesis, "is not supported.")
+                       stop(msg)
                      })
             if (nullHypothesis == "norm") {
               distParams <- as.numeric(distParams)
diff --git a/R/pkg/R/pairRDD.R b/R/pkg/R/pairRDD.R
index b29381bb900fb..9c2e57d3067db 100644
--- a/R/pkg/R/pairRDD.R
+++ b/R/pkg/R/pairRDD.R
@@ -906,7 +906,7 @@ setMethod("sampleByKey",
 
             for (elem in fractions) {
               if (elem < 0.0) {
-                stop("Negative fraction value ", fractions[which(fractions == elem)])
+                stop(paste("Negative fraction value ", fractions[which(fractions == elem)]))
               }
             }
 
diff --git a/R/pkg/R/schema.R b/R/pkg/R/schema.R
index 7044ede0cc58b..89d5c2cd1a5e2 100644
--- a/R/pkg/R/schema.R
+++ b/R/pkg/R/schema.R
@@ -199,7 +199,7 @@ checkType <- function(type) {
             })
   }
 
-  stop("Unsupported type for SparkDataframe: ", type)
+  stop(paste("Unsupported type for SparkDataframe:", type))
 }
 
 #' @param type The data type of the field
diff --git a/R/pkg/R/serialize.R b/R/pkg/R/serialize.R
index 7760d9be16f0b..cb3c1c59d12ed 100644
--- a/R/pkg/R/serialize.R
+++ b/R/pkg/R/serialize.R
@@ -84,7 +84,7 @@ writeObject <- function(con, object, writeType = TRUE) {
          Date = writeDate(con, object),
          POSIXlt = writeTime(con, object),
          POSIXct = writeTime(con, object),
-         stop("Unsupported type for serialization ", type))
+         stop(paste("Unsupported type for serialization", type)))
 }
 
 writeVoid <- function(con) {
@@ -158,7 +158,7 @@ writeType <- function(con, class) {
                  Date = "D",
                  POSIXlt = "t",
                  POSIXct = "t",
-                 stop("Unsupported type for serialization ", class))
+                 stop(paste("Unsupported type for serialization", class)))
   writeBin(charToRaw(type), con)
 }
 
diff --git a/R/pkg/R/sparkR.R b/R/pkg/R/sparkR.R
index e4a11a5f78a71..9ba36ad46740a 100644
--- a/R/pkg/R/sparkR.R
+++ b/R/pkg/R/sparkR.R
@@ -154,8 +154,8 @@ sparkR.sparkContext <- function(
   connectionTimeout <- as.numeric(Sys.getenv("SPARKR_BACKEND_CONNECTION_TIMEOUT", "6000"))
   if (existingPort != "") {
     if (length(packages) != 0) {
-      warning("sparkPackages has no effect when using spark-submit or sparkR shell, ",
-              "please use the --packages commandline instead")
+      warning(paste("sparkPackages has no effect when using spark-submit or sparkR shell",
+                    " please use the --packages commandline instead", sep = ","))
     }
     backendPort <- existingPort
     authSecret <- Sys.getenv("SPARKR_BACKEND_AUTH_SECRET")
@@ -439,9 +439,8 @@ sparkR.session <- function(
   rPackageVersion <- paste0(packageVersion("SparkR"))
 
   if (jvmVersionStrip != rPackageVersion) {
-    warning("Version mismatch between Spark JVM and SparkR package. ",
-            "JVM version was ", jvmVersion,
-            ", while R package version was ", rPackageVersion)
+    warning(paste("Version mismatch between Spark JVM and SparkR package. JVM version was",
+                  jvmVersion, ", while R package version was", rPackageVersion))
   }
 
   sparkSession
diff --git a/R/pkg/R/utils.R b/R/pkg/R/utils.R
index 65db9c21d9dbb..c60e4db1496d0 100644
--- a/R/pkg/R/utils.R
+++ b/R/pkg/R/utils.R
@@ -46,9 +46,9 @@ convertJListToRList <- function(jList, flatten, logicalUpperBound = NULL,
                 res <- list(unserialize(keyBytes),
                   unserialize(valBytes))
               } else {
-                stop("utils.R: convertJListToRList only supports ",
-                  "RDD[Array[Byte]] and ",
-                  "JavaPairRDD[Array[Byte], Array[Byte]] for now")
+                stop(paste("utils.R: convertJListToRList only supports",
+                  "RDD[Array[Byte]] and",
+                  "JavaPairRDD[Array[Byte], Array[Byte]] for now"))
               }
             } else {
               if (inherits(obj, "raw")) {
@@ -354,8 +354,8 @@ varargsToStrEnv <- function(...) {
       } else {
         value <- pairs[[name]]
         if (!(is.logical(value) || is.numeric(value) || is.character(value) || is.null(value))) {
-          stop("Unsupported type for ", name, " : ", toString(class(value)), ". ",
-               "Supported types are logical, numeric, character and NULL.", call. = FALSE)
+          stop(paste0("Unsupported type for ", name, " : ", class(value),
+               ". Supported types are logical, numeric, character and NULL."), call. = FALSE)
         }
         if (is.logical(value)) {
           env[[name]] <- tolower(as.character(value))
@@ -369,7 +369,8 @@ varargsToStrEnv <- function(...) {
   }
 
   if (length(ignoredNames) != 0) {
-    warning("Unnamed arguments ignored: ", toString(ignoredNames), ".", call. = FALSE)
+    warning(paste0("Unnamed arguments ignored: ", paste(ignoredNames, collapse = ", "), "."),
+            call. = FALSE)
   }
   env
 }
@@ -448,7 +449,7 @@ storageLevelToString <- function(levelObj) {
 # the user to type (for example) `5` instead of `5L` to avoid a confusing error message.
 numToInt <- function(num) {
   if (as.integer(num) != num) {
-    warning("Coercing ", as.list(sys.call())[[2L]], " to integer.")
+    warning(paste("Coercing", as.list(sys.call())[[2]], "to integer."))
   }
   as.integer(num)
 }
@@ -649,8 +650,8 @@ mergePartitions <- function(rdd, zip) {
         # For zip operation, check if corresponding partitions
         # of both RDDs have the same number of elements.
         if (zip && lengthOfKeys != lengthOfValues) {
-          stop("Can only zip RDDs with same number of elements ",
-               "in each pair of corresponding partitions.")
+          stop(paste("Can only zip RDDs with same number of elements",
+                     "in each pair of corresponding partitions."))
         }
 
         if (lengthOfKeys > 1) {
@@ -803,7 +804,7 @@ handledCallJMethod <- function(obj, method, ...) {
 
 captureJVMException <- function(e, method) {
   rawmsg <- as.character(e)
-  if (any(grepl("^Error in .*?: ", rawmsg))) {
+  if (any(grep("^Error in .*?: ", rawmsg))) {
     # If the exception message starts with "Error in ...", this is possibly
     # "Error in invokeJava(...)". Here, it replaces the characters to
     # `paste("Error in", method, ":")` in order to identify which function
@@ -817,58 +818,58 @@ captureJVMException <- function(e, method) {
   }
 
   # StreamingQueryException could wrap an IllegalArgumentException, so look for that first
-  if (any(grepl("org.apache.spark.sql.streaming.StreamingQueryException: ",
-                stacktrace, fixed = TRUE))) {
+  if (any(grep("org.apache.spark.sql.streaming.StreamingQueryException: ",
+               stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "org.apache.spark.sql.streaming.StreamingQueryException: ",
                     fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(rmsg, "streaming query error - ", first, call. = FALSE)
-  } else if (any(grepl("java.lang.IllegalArgumentException: ", stacktrace, fixed = TRUE))) {
+    stop(paste0(rmsg, "streaming query error - ", first), call. = FALSE)
+  } else if (any(grep("java.lang.IllegalArgumentException: ", stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "java.lang.IllegalArgumentException: ", fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(rmsg, "illegal argument - ", first, call. = FALSE)
-  } else if (any(grepl("org.apache.spark.sql.AnalysisException: ", stacktrace, fixed = TRUE))) {
+    stop(paste0(rmsg, "illegal argument - ", first), call. = FALSE)
+  } else if (any(grep("org.apache.spark.sql.AnalysisException: ", stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "org.apache.spark.sql.AnalysisException: ", fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(rmsg, "analysis error - ", first, call. = FALSE)
+    stop(paste0(rmsg, "analysis error - ", first), call. = FALSE)
   } else
-    if (any(grepl("org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException: ",
-                  stacktrace, fixed = TRUE))) {
+    if (any(grep("org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException: ",
+                 stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException: ",
                     fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(rmsg, "no such database - ", first, call. = FALSE)
+    stop(paste0(rmsg, "no such database - ", first), call. = FALSE)
   } else
-    if (any(grepl("org.apache.spark.sql.catalyst.analysis.NoSuchTableException: ",
-                  stacktrace, fixed = TRUE))) {
+    if (any(grep("org.apache.spark.sql.catalyst.analysis.NoSuchTableException: ",
+                 stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "org.apache.spark.sql.catalyst.analysis.NoSuchTableException: ",
                     fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(rmsg, "no such table - ", first, call. = FALSE)
-  } else if (any(grepl("org.apache.spark.sql.catalyst.parser.ParseException: ",
-                       stacktrace, fixed = TRUE))) {
+    stop(paste0(rmsg, "no such table - ", first), call. = FALSE)
+  } else if (any(grep("org.apache.spark.sql.catalyst.parser.ParseException: ",
+                      stacktrace, fixed = TRUE))) {
     msg <- strsplit(stacktrace, "org.apache.spark.sql.catalyst.parser.ParseException: ",
                     fixed = TRUE)[[1]]
     # Extract "Error in ..." message.
     rmsg <- msg[1]
     # Extract the first message of JVM exception.
     first <- strsplit(msg[2], "\r?\n\tat")[[1]][1]
-    stop(rmsg, "parse error - ", first, call. = FALSE)
+    stop(paste0(rmsg, "parse error - ", first), call. = FALSE)
   } else {
     stop(stacktrace, call. = FALSE)
   }
diff --git a/R/pkg/tests/fulltests/test_sparkSQL.R b/R/pkg/tests/fulltests/test_sparkSQL.R
index 611d9057c0f13..b7172b2ae0774 100644
--- a/R/pkg/tests/fulltests/test_sparkSQL.R
+++ b/R/pkg/tests/fulltests/test_sparkSQL.R
@@ -2558,7 +2558,7 @@ test_that("join(), crossJoin() and merge() on a DataFrame", {
   error_msg <- paste("joinType must be one of the following types:",
                  "'inner', 'cross', 'outer', 'full', 'fullouter', 'full_outer',",
                  "'left', 'leftouter', 'left_outer', 'right', 'rightouter', 'right_outer',",
-                 "'semi', 'leftsemi', 'left_semi', 'anti', 'leftanti', 'left_anti'")
+                 "'semi', 'leftsemi', 'left_semi', 'anti', 'leftanti' or 'left_anti'.")
   expect_error(join(df2, df, df2$name == df$name, "invalid"), error_msg)
 
   merged <- merge(df, df2, by.x = "name", by.y = "name", all.x = TRUE, all.y = TRUE)