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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2020/09/13 21:30:00 UTC
[jira] [Assigned] (SPARK-32872) BytesToBytesMap exceeds growth
threshold when close to MAX_CAPACITY
[ https://issues.apache.org/jira/browse/SPARK-32872?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-32872:
------------------------------------
Assignee: Apache Spark (was: Ankur Dave)
> BytesToBytesMap exceeds growth threshold when close to MAX_CAPACITY
> -------------------------------------------------------------------
>
> Key: SPARK-32872
> URL: https://issues.apache.org/jira/browse/SPARK-32872
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.4.7, 3.0.1
> Reporter: Ankur Dave
> Assignee: Apache Spark
> Priority: Major
>
> When BytesToBytesMap is close to {{MAX_CAPACITY}} and needs to grow, {{numKeys >= growthThreshold}} is true but {{longArray.size() / 2 < MAX_CAPACITY}} is false. This correctly prevents the map from growing, but {{canGrowArray}} incorrectly remains true. Therefore the map keeps accepting new keys and exceeds its growth threshold. If we attempt to spill the map in this state, the UnsafeKVExternalSorter will not be able to reuse the long array for sorting, causing grouping aggregations to fail with the following error:
> {{2020-09-13 18:33:48,765 ERROR Executor - Exception in task 0.0 in stage 7.0 (TID 69)
> org.apache.spark.memory.SparkOutOfMemoryError: Unable to acquire 12982025696 bytes of memory, got 0
> at org.apache.spark.memory.MemoryConsumer.throwOom(MemoryConsumer.java:160)
> at org.apache.spark.memory.MemoryConsumer.allocateArray(MemoryConsumer.java:100)
> at org.apache.spark.sql.execution.UnsafeKVExternalSorter.<init>(UnsafeKVExternalSorter.java:118)
> at org.apache.spark.sql.execution.UnsafeFixedWidthAggregationMap.destructAndCreateExternalSorter(UnsafeFixedWidthAggregationMap.java:253)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.agg_doConsume_0$(Unknown Source)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.agg_doAggregateWithKeys_0$(Unknown Source)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.agg_doAggregateWithoutKey_0$(Unknown Source)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:733)
> at org.apache.spark.sql.execution.collect.UnsafeRowBatchUtils$.encodeUnsafeRows(UnsafeRowBatchUtils.scala:80)
> at org.apache.spark.sql.execution.collect.Collector.$anonfun$processFunc$1(Collector.scala:187)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.doRunTask(Task.scala:144)
> at org.apache.spark.scheduler.Task.run(Task.scala:117)
> at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$9(Executor.scala:660)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1581)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:663)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)}}
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