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https://issues.apache.org/jira/browse/SPARK-16922?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15427241#comment-15427241
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Davies Liu edited comment on SPARK-16922 at 8/18/16 9:58 PM:
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Is this failure determistic or not? Happened on every task or some or them?
Could you also try to disable the dense mode?
was (Author: davies):
Is this failure determistic or not? Happened on every task or some or them?
> Query with Broadcast Hash join fails due to executor OOM in Spark 2.0
> ---------------------------------------------------------------------
>
> Key: SPARK-16922
> URL: https://issues.apache.org/jira/browse/SPARK-16922
> Project: Spark
> Issue Type: Bug
> Components: Shuffle
> Affects Versions: 2.0.0
> Reporter: Sital Kedia
>
> A query which used to work in Spark 1.6 fails with executor OOM in 2.0.
> Stack trace -
> {code}
> at
> org.apache.spark.unsafe.types.UTF8String.getBytes(UTF8String.java:229)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator$agg_VectorizedHashMap.hash$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator$agg_VectorizedHashMap.findOrInsert(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at
> org.apache.spark.shuffle.sort.UnsafeShuffleWriter.write(UnsafeShuffleWriter.java:161)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> {code}
> Query plan in Spark 1.6
> {code}
> == Physical Plan ==
> TungstenAggregate(key=[field1#101], functions=[(sum((field2#74 /
> 100.0)),mode=Final,isDistinct=false)], output=[field1#101,field3#3])
> +- TungstenExchange hashpartitioning(field1#101,200), None
> +- TungstenAggregate(key=[field1#101], functions=[(sum((field2#74 /
> 100.0)),mode=Partial,isDistinct=false)], output=[field1#101,sum#111])
> +- Project [field1#101,field2#74]
> +- BroadcastHashJoin [field5#63L], [cast(cast(field4#97 as
> decimal(20,0)) as bigint)], BuildRight
> :- ConvertToUnsafe
> : +- HiveTableScan [field2#74,field5#63L], MetastoreRelation
> foo, table1, Some(a), [(ds#57 >= 2013-10-01),(ds#57 <= 2013-12-31)]
> +- ConvertToUnsafe
> +- HiveTableScan [field1#101,field4#97], MetastoreRelation
> foo, table2, Some(b)
> {code}
> Query plan in 2.0
> {code}
> == Physical Plan ==
> *HashAggregate(keys=[field1#160], functions=[sum((field2#133 / 100.0))])
> +- Exchange hashpartitioning(field1#160, 200)
> +- *HashAggregate(keys=[field1#160], functions=[partial_sum((field2#133 /
> 100.0))])
> +- *Project [field2#133, field1#160]
> +- *BroadcastHashJoin [field5#122L], [cast(cast(field4#156 as
> decimal(20,0)) as bigint)], Inner, BuildRight
> :- *Filter isnotnull(field5#122L)
> : +- HiveTableScan [field5#122L, field2#133], MetastoreRelation
> foo, table1, a, [isnotnull(ds#116), (ds#116 >= 2013-10-01), (ds#116 <=
> 2013-12-31)]
> +- BroadcastExchange
> HashedRelationBroadcastMode(List(cast(cast(input[0, string, false] as
> decimal(20,0)) as bigint)))
> +- *Filter isnotnull(field4#156)
> +- HiveTableScan [field4#156, field1#160],
> MetastoreRelation foo, table2, b
> {code}
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