[ 
https://issues.apache.org/jira/browse/SPARK-15390?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Davies Liu updated SPARK-15390:
-------------------------------
    Assignee: Davies Liu

> Memory management issue in complex DataFrame join and filter
> ------------------------------------------------------------
>
>                 Key: SPARK-15390
>                 URL: https://issues.apache.org/jira/browse/SPARK-15390
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0
>         Environment: branch-2.0, 16 workers
>            Reporter: Joseph K. Bradley
>            Assignee: Davies Liu
>             Fix For: 2.0.0
>
>
> See [SPARK-15389] for a description of the code which produces this bug.  I 
> am filing this as a separate JIRA since the bug in 2.0 is different.
> In 2.0, the code fails with some memory management error.  Here is the 
> stacktrace:
> {code}
> OpenJDK 64-Bit Server VM warning: ignoring option MaxPermSize=512m; support 
> was removed in 8.0
> 16/05/18 19:23:16 ERROR Uncaught throwable from user code: 
> org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree:
> Exchange SinglePartition, None
> +- WholeStageCodegen
>    :  +- TungstenAggregate(key=[], 
> functions=[(count(1),mode=Partial,isDistinct=false)], output=[count#170L])
>    :     +- Project
>    :        +- BroadcastHashJoin [id#70L], [id#110L], Inner, BuildLeft, None
>    :           :- INPUT
>    :           +- Project [id#110L]
>    :              +- Filter (degree#115 > 2000000)
>    :                 +- TungstenAggregate(key=[id#110L], 
> functions=[(count(1),mode=Final,isDistinct=false)], 
> output=[id#110L,degree#115])
>    :                    +- INPUT
>    :- BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint]))
>    :  +- WholeStageCodegen
>    :     :  +- Project [row#66.id AS id#70L]
>    :     :     +- Filter isnotnull(row#66.id)
>    :     :        +- INPUT
>    :     +- Scan ExistingRDD[row#66,uniq_id#67]
>    +- Exchange hashpartitioning(id#110L, 200), None
>       +- WholeStageCodegen
>          :  +- TungstenAggregate(key=[id#110L], 
> functions=[(count(1),mode=Partial,isDistinct=false)], 
> output=[id#110L,count#136L])
>          :     +- Filter isnotnull(id#110L)
>          :        +- INPUT
>          +- Generate explode(array(src#2L, dst#3L)), false, false, [id#110L]
>             +- WholeStageCodegen
>                :  +- Filter ((isnotnull(src#2L) && isnotnull(dst#3L)) && NOT 
> (src#2L = dst#3L))
>                :     +- INPUT
>                +- InMemoryTableScan [src#2L,dst#3L], 
> [isnotnull(src#2L),isnotnull(dst#3L),NOT (src#2L = dst#3L)], InMemoryRelation 
> [src#2L,dst#3L], true, 10000, StorageLevel(disk=true, memory=true, 
> offheap=false, deserialized=true, replication=1), WholeStageCodegen, None
>       at 
> org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:50)
>       at 
> org.apache.spark.sql.execution.exchange.ShuffleExchange.doExecute(ShuffleExchange.scala:113)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
>       at 
> org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:233)
>       at 
> org.apache.spark.sql.execution.aggregate.TungstenAggregate.inputRDDs(TungstenAggregate.scala:134)
>       at 
> org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:348)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
>       at 
> org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:240)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:287)
>       at 
> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2122)
>       at 
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
>       at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2436)
>       at 
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2121)
>       at 
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2128)
>       at 
> org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2156)
>       at 
> org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2155)
>       at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2449)
>       at org.apache.spark.sql.Dataset.count(Dataset.scala:2155)
>       at Notebook.summary$1(<console>:70)
>       at Notebook.getIndexedEdges(<console>:82)
>       at Notebook.getIndexedGraph(<console>:135)
> Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult: 
>       at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:194)
>       at 
> org.apache.spark.sql.execution.exchange.BroadcastExchangeExec.doExecuteBroadcast(BroadcastExchangeExec.scala:102)
>       at 
> org.apache.spark.sql.execution.InputAdapter.doExecuteBroadcast(WholeStageCodegenExec.scala:229)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeBroadcast$1.apply(SparkPlan.scala:125)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeBroadcast$1.apply(SparkPlan.scala:125)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeBroadcast(SparkPlan.scala:124)
>       at 
> org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.prepareBroadcast(BroadcastHashJoinExec.scala:98)
>       at 
> org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.codegenInner(BroadcastHashJoinExec.scala:197)
>       at 
> org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.doConsume(BroadcastHashJoinExec.scala:82)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:153)
>       at 
> org.apache.spark.sql.execution.ProjectExec.consume(basicPhysicalOperators.scala:30)
>       at 
> org.apache.spark.sql.execution.ProjectExec.doConsume(basicPhysicalOperators.scala:62)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:153)
>       at 
> org.apache.spark.sql.execution.FilterExec.consume(basicPhysicalOperators.scala:79)
>       at 
> org.apache.spark.sql.execution.FilterExec.doConsume(basicPhysicalOperators.scala:194)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:153)
>       at 
> org.apache.spark.sql.execution.aggregate.TungstenAggregate.consume(TungstenAggregate.scala:33)
>       at 
> org.apache.spark.sql.execution.aggregate.TungstenAggregate.generateResultCode(TungstenAggregate.scala:432)
>       at 
> org.apache.spark.sql.execution.aggregate.TungstenAggregate.doProduceWithKeys(TungstenAggregate.scala:534)
>       at 
> org.apache.spark.sql.execution.aggregate.TungstenAggregate.doProduce(TungstenAggregate.scala:141)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.aggregate.TungstenAggregate.produce(TungstenAggregate.scala:33)
>       at 
> org.apache.spark.sql.execution.FilterExec.doProduce(basicPhysicalOperators.scala:113)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.FilterExec.produce(basicPhysicalOperators.scala:79)
>       at 
> org.apache.spark.sql.execution.ProjectExec.doProduce(basicPhysicalOperators.scala:40)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.ProjectExec.produce(basicPhysicalOperators.scala:30)
>       at 
> org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.doProduce(BroadcastHashJoinExec.scala:77)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.produce(BroadcastHashJoinExec.scala:38)
>       at 
> org.apache.spark.sql.execution.ProjectExec.doProduce(basicPhysicalOperators.scala:40)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.ProjectExec.produce(basicPhysicalOperators.scala:30)
>       at 
> org.apache.spark.sql.execution.aggregate.TungstenAggregate.doProduceWithoutKeys(TungstenAggregate.scala:211)
>       at 
> org.apache.spark.sql.execution.aggregate.TungstenAggregate.doProduce(TungstenAggregate.scala:139)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at 
> org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:78)
>       at 
> org.apache.spark.sql.execution.aggregate.TungstenAggregate.produce(TungstenAggregate.scala:33)
>       at 
> org.apache.spark.sql.execution.WholeStageCodegenExec.doCodeGen(WholeStageCodegenExec.scala:304)
>       at 
> org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:343)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
>       at 
> org.apache.spark.sql.execution.exchange.ShuffleExchange.prepareShuffleDependency(ShuffleExchange.scala:86)
>       at 
> org.apache.spark.sql.execution.exchange.ShuffleExchange$$anonfun$doExecute$1.apply(ShuffleExchange.scala:122)
>       at 
> org.apache.spark.sql.execution.exchange.ShuffleExchange$$anonfun$doExecute$1.apply(ShuffleExchange.scala:113)
>       at 
> org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:49)
>       at 
> org.apache.spark.sql.execution.exchange.ShuffleExchange.doExecute(ShuffleExchange.scala:113)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
>       at 
> org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:233)
>       at 
> org.apache.spark.sql.execution.aggregate.TungstenAggregate.inputRDDs(TungstenAggregate.scala:134)
>       at 
> org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:348)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
>       at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
>       at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
>       at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
>       at 
> org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:240)
>       at 
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:287)
>       at 
> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2122)
>       at 
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
>       at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2436)
>       at 
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2121)
>       at 
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2128)
>       at 
> org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2156)
>       at 
> org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2155)
>       at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2449)
>       at org.apache.spark.sql.Dataset.count(Dataset.scala:2155)
>       at Notebook.summary$1(<console>:70)
>       at Notebook.getIndexedEdges(<console>:82)
>       at Notebook.getIndexedGraph(<console>:135)
> Caused by: java.util.concurrent.ExecutionException: Boxed Error
>       at scala.concurrent.impl.Promise$.resolver(Promise.scala:55)
>       at 
> scala.concurrent.impl.Promise$.scala$concurrent$impl$Promise$$resolveTry(Promise.scala:47)
>       at 
> scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:244)
>       at scala.concurrent.Promise$class.complete(Promise.scala:55)
>       at 
> scala.concurrent.impl.Promise$DefaultPromise.complete(Promise.scala:153)
>       at 
> scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:23)
>       at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
>       at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
>       at java.lang.Thread.run(Thread.java:745)
> Caused by: java.lang.AssertionError: assertion failed: invalid number of 
> bytes requested: -2146435072
>       at scala.Predef$.assert(Predef.scala:179)
>       at 
> org.apache.spark.memory.ExecutionMemoryPool.acquireMemory(ExecutionMemoryPool.scala:96)
>       at 
> org.apache.spark.memory.StaticMemoryManager.acquireExecutionMemory(StaticMemoryManager.scala:98)
>       at 
> org.apache.spark.memory.TaskMemoryManager.acquireExecutionMemory(TaskMemoryManager.java:145)
>       at 
> org.apache.spark.sql.execution.joins.LongToUnsafeRowMap.acquireMemory(HashedRelation.scala:403)
>       at 
> org.apache.spark.sql.execution.joins.LongToUnsafeRowMap.init(HashedRelation.scala:419)
>       at 
> org.apache.spark.sql.execution.joins.LongToUnsafeRowMap.<init>(HashedRelation.scala:426)
>       at 
> org.apache.spark.sql.execution.joins.LongHashedRelation$.apply(HashedRelation.scala:795)
>       at 
> org.apache.spark.sql.execution.joins.HashedRelation$.apply(HashedRelation.scala:105)
>       at 
> org.apache.spark.sql.execution.joins.HashedRelationBroadcastMode.transform(HashedRelation.scala:819)
>       at 
> org.apache.spark.sql.execution.joins.HashedRelationBroadcastMode.transform(HashedRelation.scala:815)
>       at 
> org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1$$anonfun$apply$1.apply(BroadcastExchangeExec.scala:80)
>       at 
> org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1$$anonfun$apply$1.apply(BroadcastExchangeExec.scala:71)
>       at 
> org.apache.spark.sql.execution.SQLExecution$.withExecutionId(SQLExecution.scala:94)
>       at 
> org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1.apply(BroadcastExchangeExec.scala:71)
>       at 
> org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1.apply(BroadcastExchangeExec.scala:71)
>       at 
> scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
>       at 
> scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
>       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}



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