Use 'hive' for ORC

Author: dongjoon-hyun

docs/sql-programming-guide.md

@@ -1784,7 +1784,7 @@ working with timestamps in `pandas_udf`s to get the best performance, see
       <tr><th><b>Property Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th></tr>
       <tr>
         <td><code>spark.sql.orc.impl</code></td>
-        <td><code>native</code></td>
+        <td><code>hive</code></td>
         <td>The name of ORC implementation. It can be one of <code>native</code> and <code>hive</code>. <code>native</code> means the native ORC support that is built on Apache ORC 1.4.1. `hive` means the ORC library in Hive 1.2.1 which is used prior to Spark 2.3.</td>
       </tr>
       <tr>

sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala

@@ -399,11 +399,11 @@ object SQLConf {
 
   val ORC_IMPLEMENTATION = buildConf("spark.sql.orc.impl")
     .doc("When native, use the native version of ORC support instead of the ORC library in Hive " +
-      "1.2.1. It is 'hive' by default prior to Spark 2.3.")
+      "1.2.1. It is 'hive' by default.")
     .internal()
     .stringConf
     .checkValues(Set("hive", "native"))
-    .createWithDefault("native")
+    .createWithDefault("hive")
 
   val ORC_VECTORIZED_READER_ENABLED = buildConf("spark.sql.orc.enableVectorizedReader")
     .doc("Enables vectorized orc decoding.")