[jira] [Updated] (SPARK-2931) getAllowedLocalityLevel() throws ArrayIndexOutOfBoundsException

["Josh Rosen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-2931?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Josh Rosen updated SPARK-2931:
------------------------------

    Attachment: scala-sort-by-key.err

@ [~kayousterhout]: I can see how that code in {{executorLost()}} could be problematic, but I don't think that's what's triggering this bug since I don't see any "Re-queueing tasks for ..." messages in my log.

I've attached a full log from a failing test run.  If it helps, I can re-run at DEBUG logging or add extra logging statements.

> getAllowedLocalityLevel() throws ArrayIndexOutOfBoundsException
> ---------------------------------------------------------------
>
>                 Key: SPARK-2931
>                 URL: https://issues.apache.org/jira/browse/SPARK-2931
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.1.0
>         Environment: Spark EC2, spark-1.1.0-snapshot1, sort-by-key spark-perf benchmark
>            Reporter: Josh Rosen
>            Priority: Blocker
>             Fix For: 1.1.0
>
>         Attachments: scala-sort-by-key.err
>
>
> When running Spark Perf's sort-by-key benchmark on EC2 with v1.1.0-snapshot, I get the following errors (one per task):
> {code}
> 14/08/08 18:54:22 INFO scheduler.TaskSetManager: Starting task 39.0 in stage 0.0 (TID 39, ip-172-31-14-30.us-west-2.compute.internal, PROCESS_LOCAL, 1003 bytes)
> 14/08/08 18:54:22 INFO cluster.SparkDeploySchedulerBackend: Registered executor: Actor[akka.tcp://sparkExecutor@ip-172-31-9-213.us-west-2.compute.internal:58901/user/Executor#1436065036] with ID 0
> 14/08/08 18:54:22 ERROR actor.OneForOneStrategy: 1
> java.lang.ArrayIndexOutOfBoundsException: 1
>   at org.apache.spark.scheduler.TaskSetManager.getAllowedLocalityLevel(TaskSetManager.scala:475)
>   at org.apache.spark.scheduler.TaskSetManager.resourceOffer(TaskSetManager.scala:409)
>   at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$3$$anonfun$apply$7$$anonfun$apply$2.apply$mcVI$sp(TaskSchedulerImpl.scala:261)
>   at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:141)
>   at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$3$$anonfun$apply$7.apply(TaskSchedulerImpl.scala:257)
>   at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$3$$anonfun$apply$7.apply(TaskSchedulerImpl.scala:254)
>   at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
>   at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
>   at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$3.apply(TaskSchedulerImpl.scala:254)
>   at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$3.apply(TaskSchedulerImpl.scala:254)
>   at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>   at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>   at org.apache.spark.scheduler.TaskSchedulerImpl.resourceOffers(TaskSchedulerImpl.scala:254)
>   at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor.makeOffers(CoarseGrainedSchedulerBackend.scala:153)
>   at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor$$anonfun$receive$1.applyOrElse(CoarseGrainedSchedulerBackend.scala:103)
>   at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
>   at akka.actor.ActorCell.invoke(ActorCell.scala:456)
>   at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
>   at akka.dispatch.Mailbox.run(Mailbox.scala:219)
>   at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
>   at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
>   at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
>   at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
>   at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
> {code}
> This causes the job to hang.
> I can deterministically reproduce this by re-running the test, either in isolation or as part of the full performance testing suite.



--
This message was sent by Atlassian JIRA
(v6.2#6252)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org