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https://issues.apache.org/jira/browse/SPARK-3637?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Josh Rosen resolved SPARK-3637.
-------------------------------
Resolution: Cannot Reproduce
I'm going to resolve this as "Cannot Reproduce." If you see this exception on
a newer Spark version, please re-open or file a new issue.
> NPE in ShuffleMapTask
> ---------------------
>
> Key: SPARK-3637
> URL: https://issues.apache.org/jira/browse/SPARK-3637
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> 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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