[SPARK-17549][SQL] Only collect table size stat in driver for cached relation.

This reverts commit 9ac68dbc. Turns out
the original fix was correct.

Original change description:
The existing code caches all stats for all columns for each partition
in the driver; for a large relation, this causes extreme memory usage,
which leads to gc hell and application failures.

It seems that only the size in bytes of the data is actually used in the
driver, so instead just colllect that. In executors, the full stats are
still kept, but that's not a big problem; we expect the data to be distributed
and thus not really incur in too much memory pressure in each individual
executor.

There are also potential improvements on the executor side, since the data
being stored currently is very wasteful (e.g. storing boxed types vs.
primitive types for stats). But that's a separate issue.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #15304 from vanzin/SPARK-17549.2.

sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/InMemoryRelation.scala

@@ -17,8 +17,6 @@
 
 package org.apache.spark.sql.execution.columnar
 
-import scala.collection.JavaConverters._
-
 import org.apache.commons.lang3.StringUtils
 
 import org.apache.spark.network.util.JavaUtils
@@ -31,7 +29,7 @@ import org.apache.spark.sql.catalyst.plans.logical
 import org.apache.spark.sql.catalyst.plans.logical.Statistics
 import org.apache.spark.sql.execution.SparkPlan
 import org.apache.spark.storage.StorageLevel
-import org.apache.spark.util.CollectionAccumulator
+import org.apache.spark.util.LongAccumulator
 
 
 object InMemoryRelation {
@@ -63,8 +61,7 @@ case class InMemoryRelation(
     @transient child: SparkPlan,
     tableName: Option[String])(
     @transient var _cachedColumnBuffers: RDD[CachedBatch] = null,
-    val batchStats: CollectionAccumulator[InternalRow] =
-      child.sqlContext.sparkContext.collectionAccumulator[InternalRow])
+    val batchStats: LongAccumulator = child.sqlContext.sparkContext.longAccumulator)
   extends logical.LeafNode with MultiInstanceRelation {
 
   override protected def innerChildren: Seq[QueryPlan[_]] = Seq(child)
@@ -74,21 +71,12 @@ case class InMemoryRelation(
   @transient val partitionStatistics = new PartitionStatistics(output)
 
   override lazy val statistics: Statistics = {
-    if (batchStats.value.isEmpty) {
+    if (batchStats.value == 0L) {
       // Underlying columnar RDD hasn't been materialized, no useful statistics information
       // available, return the default statistics.
       Statistics(sizeInBytes = child.sqlContext.conf.defaultSizeInBytes)
     } else {
-      // Underlying columnar RDD has been materialized, required information has also been
-      // collected via the `batchStats` accumulator.
-      val sizeOfRow: Expression =
-        BindReferences.bindReference(
-          output.map(a => partitionStatistics.forAttribute(a).sizeInBytes).reduce(Add),
-          partitionStatistics.schema)
-
-      val sizeInBytes =
-        batchStats.value.asScala.map(row => sizeOfRow.eval(row).asInstanceOf[Long]).sum
-      Statistics(sizeInBytes = sizeInBytes)
+      Statistics(sizeInBytes = batchStats.value.longValue)
     }
   }
 
@@ -139,10 +127,10 @@ case class InMemoryRelation(
             rowCount += 1
           }
 
+          batchStats.add(totalSize)
+
           val stats = InternalRow.fromSeq(columnBuilders.map(_.columnStats.collectedStatistics)
             .flatMap(_.values))
-
-          batchStats.add(stats)
           CachedBatch(rowCount, columnBuilders.map { builder =>
             JavaUtils.bufferToArray(builder.build())
           }, stats)

sql/core/src/test/scala/org/apache/spark/sql/execution/columnar/InMemoryColumnarQuerySuite.scala

@@ -232,4 +232,18 @@ class InMemoryColumnarQuerySuite extends QueryTest with SharedSQLContext {
     val columnTypes2 = List.fill(length2)(IntegerType)
     val columnarIterator2 = GenerateColumnAccessor.generate(columnTypes2)
   }
+
+  test("SPARK-17549: cached table size should be correctly calculated") {
+    val data = spark.sparkContext.parallelize(1 to 10, 5).toDF()
+    val plan = spark.sessionState.executePlan(data.logicalPlan).sparkPlan
+    val cached = InMemoryRelation(true, 5, MEMORY_ONLY, plan, None)
+
+    // Materialize the data.
+    val expectedAnswer = data.collect()
+    checkAnswer(cached, expectedAnswer)
+
+    // Check that the right size was calculated.
+    assert(cached.batchStats.value === expectedAnswer.size * INT.defaultSize)
+  }
+
 }