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From Jeremy Lee <unorthodox.engine...@gmail.com>
Subject Re: Spark on EC2
Date Sun, 01 Jun 2014 07:12:02 GMT
Hmm.. you've gotten further than me. Which AMI's are you using?


On Sun, Jun 1, 2014 at 2:21 PM, superback <andrew.matrix.chen@gmail.com>
wrote:

> Hi,
>         I am trying to run an example on AMAZON EC2 and have successfully
> set up one cluster with two nodes on EC2. However, when I was testing an
> example using the following command,
>
> *
> ./run-example org.apache.spark.examples.GroupByTest
> spark://`hostname`:7077*
>
> I got the following warnings and errors. Can anyone help one solve this
> problem? Thanks very much!
>
> 46781 [Timer-0] WARN org.apache.spark.scheduler.TaskSchedulerImpl - Initial
> job has not accepted any resources; check your cluster UI to ensure that
> workers are registered and have sufficient memory
> 61544 [spark-akka.actor.default-dispatcher-3] ERROR
> org.apache.spark.deploy.client.AppClient$ClientActor - All masters are
> unresponsive! Giving up.
> 61544 [spark-akka.actor.default-dispatcher-3] ERROR
> org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend - Spark
> cluster looks dead, giving up.
> 61546 [spark-akka.actor.default-dispatcher-3] INFO
> org.apache.spark.scheduler.TaskSchedulerImpl - Remove TaskSet 0.0 from pool
> 61549 [main] INFO org.apache.spark.scheduler.DAGScheduler - Failed to run
> count at GroupByTest.scala:50
> Exception in thread "main" org.apache.spark.SparkException: Job aborted:
> Spark cluster looks down
>         at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1028)
>         at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1026)
>         at
>
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>         at
> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>         at
> org.apache.spark.scheduler.DAGScheduler.org
> $apache$spark$scheduler$DAGScheduler$$abortStage(DAGScheduler.scala:1026)
>         at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:619)
>         at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:619)
>         at scala.Option.foreach(Option.scala:236)
>         at
>
> org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:619)
>         at
>
> org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:207)
>         at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
>         at akka.actor.ActorCell.invoke(ActorCell.scala:456)
>         at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
>         at akka.dispatch.Mailbox.run(Mailbox.scala:219)
>         at
>
> akka.dispatch.ForkJoinExecutorConfigurator$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)
>
>
>
>
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/Spark-on-EC2-tp6638.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>



-- 
Jeremy Lee  BCompSci(Hons)
  The Unorthodox Engineers

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