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https://issues.apache.org/jira/browse/SPARK-10733?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Andrew Or resolved SPARK-10733.
-------------------------------
Resolution: Duplicate
Looks like this is a duplicate of SPARK-10474 after all. I'm closing this...
> TungstenAggregation cannot acquire page after switching to sort-based
> ---------------------------------------------------------------------
>
> Key: SPARK-10733
> URL: https://issues.apache.org/jira/browse/SPARK-10733
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.5.0
> Reporter: Andrew Or
> Assignee: Andrew Or
> Priority: Blocker
>
> This is uncovered after fixing SPARK-10474. Stack trace:
> {code}
> 15/09/21 12:51:46 WARN scheduler.TaskSetManager: Lost task 115.0 in stage
> 152.0 (TID 1736, bb-node2): java.io.IOException: Unable to acquire 16777216
> bytes of memory
> at
> org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.acquireNewPage(UnsafeExternalSorter.java:378)
> at
> org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.acquireNewPageIfNecessary(UnsafeExternalSorter.java:359)
> at
> org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.insertKVRecord(UnsafeExternalSorter.java:488)
> at
> org.apache.spark.sql.execution.UnsafeKVExternalSorter.insertKV(UnsafeKVExternalSorter.java:144)
> at
> org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.switchToSortBasedAggregation(TungstenAggregationIterator.scala:465)
> at
> org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.processInputs(TungstenAggregationIterator.scala:379)
> at
> org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.start(TungstenAggregationIterator.scala:622)
> at
> org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1.org$apache$spark$sql$execution$aggregate$TungstenAggregate$$anonfun$$executePartition$1(TungstenAggregate.scala:110)
> at
> org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:119)
> at
> org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:119)
> at
> org.apache.spark.rdd.MapPartitionsWithPreparationRDD.compute(MapPartitionsWithPreparationRDD.scala:64)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:88)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
> {code}
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