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Posted to dev@mahout.apache.org by "Andrew Palumbo (JIRA)" <ji...@apache.org> on 2015/03/27 13:42:53 UTC

[jira] [Resolved] (MAHOUT-1607) spark-shell:scheduler.DAGScheduler: Failed to run fold at CheckpointedDrmSpark.scala:192

     [ https://issues.apache.org/jira/browse/MAHOUT-1607?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Andrew Palumbo resolved MAHOUT-1607.
------------------------------------
    Resolution: Not a Problem

This was likely caused by mismatched spark versions.  Closing since there's no way to verify and this is currently not a problem:
{code}
mahout> val drmData = drmParallelize(dense(
     |   (2, 2, 10.5, 10, 29.509541),  // Apple Cinnamon Cheerios
     |   (1, 2, 12,   12, 18.042851),  // Cap'n'Crunch
     |   (1, 1, 12,   13, 22.736446),  // Cocoa Puffs
     |   (2, 1, 11,   13, 32.207582),  // Froot Loops
     |   (1, 2, 12,   11, 21.871292),  // Honey Graham Ohs
     |   (2, 1, 16,   8,  36.187559),  // Wheaties Honey Gold
     |   (6, 2, 17,   1,  50.764999),  // Cheerios
     |   (3, 2, 13,   7,  40.400208),  // Clusters
     |   (3, 3, 13,   4,  45.811716)), // Great Grains Pecan
     |   numPartitions = 2);
drmData: org.apache.mahout.math.drm.CheckpointedDrm[Int] = org.apache.mahout.sparkbindings.drm.CheckpointedDrmSpark@1ea2ad30
mahout> val drmX = drmData(::, 0 until 4)
drmX: org.apache.mahout.math.drm.DrmLike[Int] = org.apache.mahout.math.drm.logical.OpMapBlock@4d345c9d
 {code}

> spark-shell:scheduler.DAGScheduler: Failed to run fold at CheckpointedDrmSpark.scala:192
> ----------------------------------------------------------------------------------------
>
>                 Key: MAHOUT-1607
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-1607
>             Project: Mahout
>          Issue Type: Bug
>          Components: CLI
>    Affects Versions: 1.0, 0.9
>         Environment: ubuntu 13.x   x64
> jdk1.7.0_65
> scala 2.10.4
> spark 1.0.2
>            Reporter: hhlin
>            Assignee: Andrew Palumbo
>              Labels: DSL, scala, spark, test
>             Fix For: 0.10.0
>
>
> follow the step by http://mahout.apache.org/users/sparkbindings/play-with-shell.html, mahou spark-shell startup normally,but when  exec "val drmX = drmData(::, 0 until 4);" ,it throw  exception as bellow:
> 14/08/17 20:13:20 INFO scheduler.DAGScheduler: Failed to run fold at CheckpointedDrmSpark.scala:192
> 14/08/17 20:13:20 INFO scheduler.TaskSetManager: Loss was due to java.lang.ArrayStoreException: scala.Tuple3 [duplicate 6]
> 14/08/17 20:13:20 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0.0:1 failed 4 times, most recent failure: Exception failure in TID 6 on host iZ23qefud7nZ: java.lang.ArrayStoreException: scala.Tuple3
>         com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:338)
>         com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:293)
>         com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
>         com.twitter.chill.WrappedArraySerializer.read(WrappedArraySerializer.scala:34)
>         com.twitter.chill.WrappedArraySerializer.read(WrappedArraySerializer.scala:21)
>         com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
>         org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:118)
>         org.apache.spark.rdd.ParallelCollectionPartition$$anonfun$readObject$1.apply(ParallelCollectionRDD.scala:80)
>         org.apache.spark.rdd.ParallelCollectionPartition$$anonfun$readObject$1.apply(ParallelCollectionRDD.scala:80)
>         org.apache.spark.util.Utils$.deserializeViaNestedStream(Utils.scala:120)
>         org.apache.spark.rdd.ParallelCollectionPartition.readObject(ParallelCollectionRDD.scala:80)
>         sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>         sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>         sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>         java.lang.reflect.Method.invoke(Method.java:606)
>         java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1017)
>         java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1893)
>         java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)
>         java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
>         java.io.ObjectInputStream.skipCustomData(ObjectInputStream.java:1956)
>         java.io.ObjectInputStream.readExternalData(ObjectInputStream.java:1850)
>         java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1796)
>         java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
>         java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
>         org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:63)
>         org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:85)
>         org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:165)
>         java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>         java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>         java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> 	at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1049)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1033)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1031)
> 	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> 	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> 	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1031)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:635)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:635)
> 	at scala.Option.foreach(Option.scala:236)
> 	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:635)
> 	at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1234)
> 	at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
> 	at akka.actor.ActorCell.invoke(ActorCell.scala:456)
> 	at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
> 	at akka.dispatch.Mailbox.run(Mailbox.scala:219)
> 	at akka.dispatch.ForkJoinExecutorConfigurator$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)



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