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From Vicky Kak <vicky....@gmail.com>
Subject Re: Programatically running of the Spark Jobs.
Date Fri, 05 Sep 2014 05:20:43 GMT
I get this error when i run it from IDE
***************************************************************************************

Exception in thread "main" org.apache.spark.SparkException: Job aborted due
to stage failure: Master removed our application: FAILED
    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)

***************************************************************************************



On Fri, Sep 5, 2014 at 7:35 AM, ericacm <ericacm@gmail.com> wrote:

> Ahh - that probably explains an issue I am seeing.  I am a brand new user
> and
> I tried running the SimpleApp class that is on the Quick Start page
> (http://spark.apache.org/docs/latest/quick-start.html).
>
> When I use conf.setMaster("local") then I can run the class directly from
> my
> IDE.  But when I try to set the master to my standalone cluster using
> conf.setMaster("spark://myhost:7077") and then run the class directly from
> the IDE I got this error in the local application (running from the IDE):
>
> 14/09/01 10:56:04 ERROR scheduler.TaskSetManager: Task 0.0:0 failed 4
> times;
> aborting job
> 14/09/01 10:56:04 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 0.0,
> whose tasks have all completed, from pool
> 14/09/01 10:56:04 INFO scheduler.TaskSchedulerImpl: Cancelling stage 0
> 14/09/01 10:56:04 INFO client.AppClient$ClientActor: Executor updated:
> app-20140901105546-0001/3 is now EXITED (Command exited with code 52)
> 14/09/01 10:56:04 INFO cluster.SparkDeploySchedulerBackend: Executor
> app-20140901105546-0001/3 removed: Command exited with code 52
> 14/09/01 10:56:04 INFO scheduler.DAGScheduler: Failed to run count at
> SimpleApp.scala:17
> Exception in thread "main" 14/09/01 10:56:04 INFO
> client.AppClient$ClientActor: Executor added: app-20140901105546-0001/4 on
> worker-20140901105055-10.0.1.5-56156 (10.0.1.5:56156) with 8 cores
> org.apache.spark.SparkException: Job aborted due to stage failure: Task
> 0.0:0 failed 4 times, most recent failure: TID 3 on host 10.0.1.5 failed
> for
> unknown reason
>
> and this error in the worker stderr:
>
> 14/09/01 10:55:54 ERROR Executor: Exception in task ID 1
> java.lang.OutOfMemoryError: Java heap space
>         at
>
> org.apache.hadoop.io.WritableUtils.readCompressedStringArray(WritableUtils.java:183)
>         at
> org.apache.hadoop.conf.Configuration.readFields(Configuration.java:2378)
>         at
> org.apache.hadoop.io.ObjectWritable.readObject(ObjectWritable.java:285)
>         at
> org.apache.hadoop.io.ObjectWritable.readFields(ObjectWritable.java:77)
>         at
>
> org.apache.spark.SerializableWritable.readObject(SerializableWritable.scala:42)
>         at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>         at
>
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>         at
>
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>         at java.lang.reflect.Method.invoke(Method.java:601)
>         at
> java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1004)
>         at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1872)
>         at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1777)
>         at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347)
>         at java.io.ObjectInputStream.readObject(ObjectInputStream.java:369)
>         at
>
> org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:63)
>
> Which made no sense because I also gave the worker 1gb of heap and it was
> trying to process a 4k README.md file.  I'm guessing it must have tried to
> deserialize a bogus object because I was not submitting the job correctly
> (via spark-submit or this spark-jobserver)?
>
> Thanks,
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/Programatically-running-of-the-Spark-Jobs-tp13426p13518.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
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