[SPARK-6844][SQL] Clean up accumulators used in InMemoryRelation when it is uncached

JIRA: https://issues.apache.org/jira/browse/SPARK-6844

Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #5475 from viirya/cache_memory_leak and squashes the following commits:

0b41235 [Liang-Chi Hsieh] fix style.
dc1d5d5 [Liang-Chi Hsieh] For comments.
78af229 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into cache_memory_leak
26c9bb6 [Liang-Chi Hsieh] Add configuration to enable in-memory table scan accumulators.
1c3b06e [Liang-Chi Hsieh] Clean up accumulators used in InMemoryRelation when it is uncached.

2 files changed, 35 insertions, 14 deletions

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/CacheManager.scala b/sql/core/src/main/scala/org/apache/spark/sql/CacheManager.scala
index ca4a127120..18584c2dcf 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/CacheManager.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/CacheManager.scala
@@ -112,7 +112,7 @@ private[sql] class CacheManager(sqlContext: SQLContext) extends Logging {
     val planToCache = query.queryExecution.analyzed
     val dataIndex = cachedData.indexWhere(cd => planToCache.sameResult(cd.plan))
     require(dataIndex >= 0, s"Table $query is not cached.")
-    cachedData(dataIndex).cachedRepresentation.cachedColumnBuffers.unpersist(blocking)
+    cachedData(dataIndex).cachedRepresentation.uncache(blocking)
     cachedData.remove(dataIndex)
   }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala
index 6eee0c86d6..d9b6fb43ab 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala
@@ -19,13 +19,15 @@ package org.apache.spark.sql.columnar
 
 import java.nio.ByteBuffer
 
-import org.apache.spark.Accumulator
+import org.apache.spark.{Accumulable, Accumulator, Accumulators}
 import org.apache.spark.sql.catalyst.expressions
 
 import scala.collection.mutable.ArrayBuffer
+import scala.collection.mutable.HashMap
 
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.Row
+import org.apache.spark.SparkContext
 import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation
 import org.apache.spark.sql.catalyst.dsl.expressions._
 import org.apache.spark.sql.catalyst.expressions._
@@ -53,11 +55,16 @@ private[sql] case class InMemoryRelation(
     child: SparkPlan,
     tableName: Option[String])(
     private var _cachedColumnBuffers: RDD[CachedBatch] = null,
-    private var _statistics: Statistics = null)
+    private var _statistics: Statistics = null,
+    private var _batchStats: Accumulable[ArrayBuffer[Row], Row] = null)
   extends LogicalPlan with MultiInstanceRelation {
 
-  private val batchStats =
-    child.sqlContext.sparkContext.accumulableCollection(ArrayBuffer.empty[Row])
+  private val batchStats: Accumulable[ArrayBuffer[Row], Row] =
+    if (_batchStats == null) {
+      child.sqlContext.sparkContext.accumulableCollection(ArrayBuffer.empty[Row])
+    } else {
+      _batchStats
+    }
 
   val partitionStatistics = new PartitionStatistics(output)
 
@@ -161,7 +168,7 @@ private[sql] case class InMemoryRelation(
   def withOutput(newOutput: Seq[Attribute]): InMemoryRelation = {
     InMemoryRelation(
       newOutput, useCompression, batchSize, storageLevel, child, tableName)(
-      _cachedColumnBuffers, statisticsToBePropagated)
+      _cachedColumnBuffers, statisticsToBePropagated, batchStats)
   }
 
   override def children: Seq[LogicalPlan] = Seq.empty
@@ -175,13 +182,20 @@ private[sql] case class InMemoryRelation(
       child,
       tableName)(
       _cachedColumnBuffers,
-      statisticsToBePropagated).asInstanceOf[this.type]
+      statisticsToBePropagated,
+      batchStats).asInstanceOf[this.type]
   }
 
   def cachedColumnBuffers: RDD[CachedBatch] = _cachedColumnBuffers
 
   override protected def otherCopyArgs: Seq[AnyRef] =
-    Seq(_cachedColumnBuffers, statisticsToBePropagated)
+    Seq(_cachedColumnBuffers, statisticsToBePropagated, batchStats)
+
+  private[sql] def uncache(blocking: Boolean): Unit = {
+    Accumulators.remove(batchStats.id)
+    cachedColumnBuffers.unpersist(blocking)
+    _cachedColumnBuffers = null
+  }
 }
 
 private[sql] case class InMemoryColumnarTableScan(
@@ -244,15 +258,20 @@ private[sql] case class InMemoryColumnarTableScan(
     }
   }
 
+  lazy val enableAccumulators: Boolean =
+    sqlContext.getConf("spark.sql.inMemoryTableScanStatistics.enable", "false").toBoolean
+
   // Accumulators used for testing purposes
-  val readPartitions: Accumulator[Int] = sparkContext.accumulator(0)
-  val readBatches: Accumulator[Int] = sparkContext.accumulator(0)
+  lazy val readPartitions: Accumulator[Int] = sparkContext.accumulator(0)
+  lazy val readBatches: Accumulator[Int] = sparkContext.accumulator(0)
 
   private val inMemoryPartitionPruningEnabled = sqlContext.conf.inMemoryPartitionPruning
 
   override def execute(): RDD[Row] = {
-    readPartitions.setValue(0)
-    readBatches.setValue(0)
+    if (enableAccumulators) {
+      readPartitions.setValue(0)
+      readBatches.setValue(0)
+    }
 
     relation.cachedColumnBuffers.mapPartitions { cachedBatchIterator =>
       val partitionFilter = newPredicate(
@@ -302,7 +321,7 @@ private[sql] case class InMemoryColumnarTableScan(
           }
         }
 
-        if (rows.hasNext) {
+        if (rows.hasNext && enableAccumulators) {
           readPartitions += 1
         }
 
@@ -321,7 +340,9 @@ private[sql] case class InMemoryColumnarTableScan(
               logInfo(s"Skipping partition based on stats $statsString")
               false
             } else {
-              readBatches += 1
+              if (enableAccumulators) {
+                readBatches += 1
+              }
               true
             }
           }