[jira] [Commented] (SPARK-3637) NPE in ShuffleMapTask

["Steven Lewis (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-3637?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14162600#comment-14162600 ] 

Steven Lewis commented on SPARK-3637:
-------------------------------------

I see the same thing running a Java Map reduce program locally and it is a blocking issue for my development especially since I have no clue as to how to address it

> NPE in ShuffleMapTask
> ---------------------
>
>                 Key: SPARK-3637
>                 URL: https://issues.apache.org/jira/browse/SPARK-3637
>             Project: Spark
>          Issue Type: Bug
>    Affects Versions: 1.1.0
>            Reporter: Przemyslaw Pastuszka
>
> When trying to execute spark.jobserver.WordCountExample using spark-jobserver (https://github.com/ooyala/spark-jobserver) we observed that often it fails with NullPointerException in ShuffleMapTask.scala. Here are full details:
> {code}
> Job aborted due to stage failure: Task 0 in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1.0 (TID 6, hadoop-simple-768-worker-with-zookeeper-0): java.lang.NullPointerException: \n        java.nio.ByteBuffer.wrap(ByteBuffer.java:392)\n        org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:61)\n        org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)\n        org.apache.spark.scheduler.Task.run(Task.scala:54)\n        org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:199)\n        java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)\n        java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)\n        java.lang.Thread.run(Thread.java:745)\nDriver stacktrace:",
>     "errorClass": "org.apache.spark.SparkException",
>     "stack": ["org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1153)", "org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1142)", "org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1141)", "scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)", "scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)", "org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1141)", "org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:682)", "org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:682)", "scala.Option.foreach(Option.scala:236)", "org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:682)", "org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1359)", "akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)", "akka.actor.ActorCell.invoke(ActorCell.scala:456)", "akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)", "akka.dispatch.Mailbox.run(Mailbox.scala:219)", "akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)", "scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)", "scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)", "scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)", "scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)"
> {code}
> I am aware, that this failure may be due to the job being ill-defined by spark-jobserver (I don't know if that's the case), but if so, then it should be handled more gratefully on spark side.
> What's also important, that this issue doesn't happen always, which may indicate some type of race condition in the code.



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