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[SPARK-26709][SQL] OptimizeMetadataOnlyQuery does not handle empty records correctly #23635

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[SPARK-26709][SQL] OptimizeMetadataOnlyQuery does not handle empty records correctly #23635

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6bd09b1
fix
gengliangwang Jan 24, 2019
1c81586
revert the whole rule
gengliangwang Jan 24, 2019
15cc872
Revert "revert the whole rule"
gengliangwang Jan 24, 2019
8399d77
address comments
gengliangwang Jan 24, 2019
1524205
Update SQLConf.scala
gatorsmile Jan 24, 2019
f7dac39
Update SQLConf.scala
gatorsmile Jan 24, 2019
9e99d4b
Update OptimizeMetadataOnlyQuery.scala
gatorsmile Jan 24, 2019
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12 changes: 0 additions & 12 deletions docs/sql-data-sources-parquet.md
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Expand Up @@ -295,18 +295,6 @@ Configuration of Parquet can be done using the `setConf` method on `SparkSession
</p>
</td>
</tr>
<tr>
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@gengliangwang gengliangwang Jan 24, 2019

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The configuration is not only about Parquet. Since it is disabled, and to avoid confusing users, I think we can just remove the doc here.

<td><code>spark.sql.optimizer.metadataOnly</code></td>
<td>true</td>
<td>
<p>
When true, enable the metadata-only query optimization that use the table's metadata to
produce the partition columns instead of table scans. It applies when all the columns scanned
are partition columns and the query has an aggregate operator that satisfies distinct
semantics.
</p>
</td>
</tr>
<tr>
<td><code>spark.sql.parquet.writeLegacyFormat</code></td>
<td>false</td>
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5 changes: 3 additions & 2 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
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Expand Up @@ -585,9 +585,10 @@ object SQLConf {
.doc("When true, enable the metadata-only query optimization that use the table's metadata " +
"to produce the partition columns instead of table scans. It applies when all the columns " +
"scanned are partition columns and the query has an aggregate operator that satisfies " +
"distinct semantics.")
"distinct semantics. By default the optimization is disabled, since it may return " +
"incorrect results with empty tables.")
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@gatorsmile gatorsmile Jan 24, 2019

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may return incorrect results when the files are empty.

.booleanConf
.createWithDefault(true)
.createWithDefault(false)
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@maropu maropu Jan 24, 2019

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How about making this conf. internal and always printing a warning message when this flag enabled and the rule applied?


val COLUMN_NAME_OF_CORRUPT_RECORD = buildConf("spark.sql.columnNameOfCorruptRecord")
.doc("The name of internal column for storing raw/un-parsed JSON and CSV records that fail " +
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13 changes: 12 additions & 1 deletion sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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Expand Up @@ -2422,7 +2422,7 @@ class SQLQuerySuite extends QueryTest with SharedSQLContext {
Row(s"$expected") :: Nil)
}

test("SPARK-15752 optimize metadata only query for datasource table") {
ignore("SPARK-15752 optimize metadata only query for datasource table") {
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@gengliangwang gengliangwang Jan 24, 2019

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This is kind of aggressive. I can revert this one if anyone objects.

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@hvanhovell hvanhovell Jan 24, 2019

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I object. You are removing integration testing for whomever it using the feature.

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@cloud-fan cloud-fan Jan 24, 2019

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we should either fix the rule, or remove it completely if it has fundamental issues. I don't think the Hive approach is the right thing to do: we should not leave a problematic rule that users can enable.

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@gengliangwang gengliangwang Jan 24, 2019

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@hvanhovell @cloud-fan I see.
As per the comments, the most appropriate solution is to delete the whole rule/configuration. I will update this PR.

withSQLConf(SQLConf.OPTIMIZER_METADATA_ONLY.key -> "true") {
withTable("srcpart_15752") {
val data = (1 to 10).map(i => (i, s"data-$i", i % 2, if ((i % 2) == 0) "a" else "b"))
Expand Down Expand Up @@ -2966,6 +2966,17 @@ class SQLQuerySuite extends QueryTest with SharedSQLContext {
}
}
}

test("SPARK-26709: OptimizeMetadataOnlyQuery does not handle empty records correctly") {
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@hvanhovell hvanhovell Jan 24, 2019

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Also add a case that illustrates that OptimizeMetadataOnlyQuery can produce wrong results.

withSQLConf(SQLConf.OPTIMIZER_METADATA_ONLY.key -> "false") {
withTable("t") {
sql("CREATE TABLE t (col1 INT, p1 INT) USING PARQUET PARTITIONED BY (p1)")
sql("INSERT INTO TABLE t PARTITION (p1 = 5) SELECT ID FROM range(1, 1)")
checkAnswer(sql("SELECT MAX(p1) FROM t"), Row(null))
checkAnswer(sql("SELECT MAX(col1) FROM t"), Row(null))
}
}
}
}

case class Foo(bar: Option[String])
4 changes: 2 additions & 2 deletions sql/core/src/test/scala/org/apache/spark/sql/execution/OptimizeMetadataOnlyQuerySuite.scala
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Expand Up @@ -58,7 +58,7 @@ class OptimizeMetadataOnlyQuerySuite extends QueryTest with SharedSQLContext {
}

private def testMetadataOnly(name: String, sqls: String*): Unit = {
test(name) {
ignore(name) {
withSQLConf(SQLConf.OPTIMIZER_METADATA_ONLY.key -> "true") {
sqls.foreach { case q => assertMetadataOnlyQuery(sql(q)) }
}
Expand All @@ -69,7 +69,7 @@ class OptimizeMetadataOnlyQuerySuite extends QueryTest with SharedSQLContext {
}

private def testNotMetadataOnly(name: String, sqls: String*): Unit = {
test(name) {
ignore(name) {
withSQLConf(SQLConf.OPTIMIZER_METADATA_ONLY.key -> "true") {
sqls.foreach { case q => assertNotMetadataOnlyQuery(sql(q)) }
}
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13 changes: 12 additions & 1 deletion sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
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Expand Up @@ -86,6 +86,17 @@ class SQLQuerySuite extends QueryTest with SQLTestUtils with TestHiveSingleton {
assert(message.contains("Table or view not found"))
}

test("SPARK-26709: OptimizeMetadataOnlyQuery does not handle empty records correctly") {
withSQLConf(SQLConf.OPTIMIZER_METADATA_ONLY.key -> "false") {
withTable("t") {
sql("CREATE TABLE t (col1 INT, p1 INT) USING PARQUET PARTITIONED BY (p1)")
sql("INSERT INTO TABLE t PARTITION (p1 = 5) SELECT ID FROM range(1, 1)")
checkAnswer(sql("SELECT MAX(p1) FROM t"), Row(null))
checkAnswer(sql("SELECT MAX(col1) FROM t"), Row(null))
}
}
}

test("script") {
assume(TestUtils.testCommandAvailable("/bin/bash"))
assume(TestUtils.testCommandAvailable("echo | sed"))
Expand Down Expand Up @@ -1770,7 +1781,7 @@ class SQLQuerySuite extends QueryTest with SQLTestUtils with TestHiveSingleton {
}
}

test("SPARK-15752 optimize metadata only query for hive table") {
ignore("SPARK-15752 optimize metadata only query for hive table") {
withSQLConf(SQLConf.OPTIMIZER_METADATA_ONLY.key -> "true") {
withTable("data_15752", "srcpart_15752", "srctext_15752") {
val df = Seq((1, "2"), (3, "4")).toDF("key", "value")
Expand Down