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https://issues.apache.org/jira/browse/SPARK-2353?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Josh Rosen reassigned SPARK-2353:
---------------------------------
Assignee: Josh Rosen
> ArrayIndexOutOfBoundsException in scheduler
> -------------------------------------------
>
> Key: SPARK-2353
> URL: https://issues.apache.org/jira/browse/SPARK-2353
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.1.0
> Reporter: Mridul Muralidharan
> Assignee: Josh Rosen
> Priority: Blocker
> Fix For: 1.1.0
>
>
> I suspect the recent changes from SPARK-1937 to compute valid locality levels
> (and ignoring ones which are not applicable) has resulted in this issue.
> Specifically, some of the code using currentLocalityIndex (and lastLaunchTime
> actually) seems to be assuming
> a) constant population of locality levels.
> b) probably also immutablility/repeatibility of locality levels
> These do not hold any longer.
> I do not have the exact values for which this failure was observed (since
> this is from the logs of a failed job) - but the code path is suspect.
> Also note that the line numbers/classes might not exactly match master since
> we are in the middle of a merge. But the issue should hopefully be evident.
> java.lang.ArrayIndexOutOfBoundsException: 2
> at
> org.apache.spark.scheduler.TaskSetManager.getAllowedLocalityLevel(TaskSetManager.scala:439)
> at
> org.apache.spark.scheduler.TaskSetManager.resourceOffer(TaskSetManager.scala:388)
> at
> org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$3$$anonfun$apply$5$$anonfun$apply$2.apply$mcVI$sp(TaskSchedulerImpl.scala:248)
> at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:141)
> at
> org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$3$$anonfun$apply$5.apply(TaskSchedulerImpl.scala:244)
> at
> org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$3$$anonfun$apply$5.apply(TaskSchedulerImpl.scala:241)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
> at
> org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$3.apply(TaskSchedulerImpl.scala:241)
> at
> org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$3.apply(TaskSchedulerImpl.scala:241)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.TaskSchedulerImpl.resourceOffers(TaskSchedulerImpl.scala:241)
> at
> org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor.makeOffers(CoarseGrainedSchedulerBackend.scala:133)
> at
> org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor$$anonfun$receive$1.applyOrElse(CoarseGrainedSchedulerBackend.scala:86)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
> at
> akka.dispatch.ForkJoinExecutorConfigurator$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)
> Unfortunately, we do not have the bandwidth to tackle this issue - would be
> great if someone could take a look at it ! Thanks.
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