[SPARK-12898] Consider having dummyCallSite for HiveTableScan

Currently, HiveTableScan runs with getCallSite which is really expensive and shows up when scanning through large table with partitions (e.g TPC-DS) which slows down the overall runtime of the job. It would be good to consider having dummyCallSite in HiveTableScan.

Author: Rajesh Balamohan <rbalamohan@apache.org>

Closes #10825 from rajeshbalamohan/SPARK-12898.

sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala

@@ -32,6 +32,7 @@ import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.execution._
 import org.apache.spark.sql.hive._
 import org.apache.spark.sql.types.{BooleanType, DataType}
+import org.apache.spark.util.Utils
 
 /**
  * The Hive table scan operator.  Column and partition pruning are both handled.
@@ -133,11 +134,17 @@ case class HiveTableScan(
   }
 
   protected override def doExecute(): RDD[InternalRow] = {
+    // Using dummyCallSite, as getCallSite can turn out to be expensive with
+    // with multiple partitions.
     val rdd = if (!relation.hiveQlTable.isPartitioned) {
-      hadoopReader.makeRDDForTable(relation.hiveQlTable)
+      Utils.withDummyCallSite(sqlContext.sparkContext) {
+        hadoopReader.makeRDDForTable(relation.hiveQlTable)
+      }
     } else {
-      hadoopReader.makeRDDForPartitionedTable(
-        prunePartitions(relation.getHiveQlPartitions(partitionPruningPred)))
+      Utils.withDummyCallSite(sqlContext.sparkContext) {
+        hadoopReader.makeRDDForPartitionedTable(
+          prunePartitions(relation.getHiveQlPartitions(partitionPruningPred)))
+      }
     }
     rdd.mapPartitionsInternal { iter =>
       val proj = UnsafeProjection.create(schema)