[SPARK-6575] [SQL] Adds configuration to disable schema merging while converting metastore Parquet tables

Consider a metastore Parquet table that

1. doesn't have schema evolution issue
2. has lots of data files and/or partitions

In this case, driver schema merging can be both slow and unnecessary. Would be good to have a configuration to let the use disable schema merging when converting such a metastore Parquet table.

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Author: Cheng Lian <lian@databricks.com>

Closes #5231 from liancheng/spark-6575 and squashes the following commits:

cd96159 [Cheng Lian] Adds configuration to disable schema merging while converting metastore Parquet tables

2 files changed, 15 insertions, 10 deletions

diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala
index c06c2e396b..6bb1c47dba 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala
@@ -58,6 +58,15 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) {
     getConf("spark.sql.hive.convertMetastoreParquet", "true") == "true"
 
   /**
+   * When true, also tries to merge possibly different but compatible Parquet schemas in different
+   * Parquet data files.
+   *
+   * This configuration is only effective when "spark.sql.hive.convertMetastoreParquet" is true.
+   */
+  protected[sql] def convertMetastoreParquetWithSchemaMerging: Boolean =
+    getConf("spark.sql.hive.convertMetastoreParquet.mergeSchema", "false") == "true"
+
+  /**
    * When true, a table created by a Hive CTAS statement (no USING clause) will be
    * converted to a data source table, using the data source set by spark.sql.sources.default.
    * The table in CTAS statement will be converted when it meets any of the following conditions:
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
index f20f0ad99f..2b5d031741 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala
@@ -218,6 +218,10 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with
 
   private def convertToParquetRelation(metastoreRelation: MetastoreRelation): LogicalRelation = {
     val metastoreSchema = StructType.fromAttributes(metastoreRelation.output)
+    val mergeSchema = hive.convertMetastoreParquetWithSchemaMerging
+    val parquetOptions = Map(
+      ParquetRelation2.METASTORE_SCHEMA -> metastoreSchema.json,
+      ParquetRelation2.MERGE_SCHEMA -> mergeSchema.toString)
 
     // NOTE: Instead of passing Metastore schema directly to `ParquetRelation2`, we have to
     // serialize the Metastore schema to JSON and pass it as a data source option because of the
@@ -234,18 +238,10 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with
       }
       val partitionSpec = PartitionSpec(partitionSchema, partitions)
       val paths = partitions.map(_.path)
-      LogicalRelation(
-        ParquetRelation2(
-          paths,
-          Map(ParquetRelation2.METASTORE_SCHEMA -> metastoreSchema.json),
-          None,
-          Some(partitionSpec))(hive))
+      LogicalRelation(ParquetRelation2(paths, parquetOptions, None, Some(partitionSpec))(hive))
     } else {
       val paths = Seq(metastoreRelation.hiveQlTable.getDataLocation.toString)
-      LogicalRelation(
-        ParquetRelation2(
-          paths,
-          Map(ParquetRelation2.METASTORE_SCHEMA -> metastoreSchema.json))(hive))
+      LogicalRelation(ParquetRelation2(paths, parquetOptions)(hive))
     }
   }