I think your *sparkUrl *points to an invalid cluster url. Just make sure you are giving the correct url (the one you see on top left in the master:8080 webUI).
Thanks Best Regards On Tue, Aug 26, 2014 at 11:07 AM, Forest D <dev24a...@gmail.com> wrote: > Hi Jonathan, > > Thanks for the reply. I ran other exercises (movie recommendation and > GraphX) on the same cluster and did not see these errors. So I think this > might not be related to the memory setting.. > > Thanks, > Forest > > On Aug 24, 2014, at 10:27 AM, Jonathan Haddad <j...@jonhaddad.com> wrote: > > > Could you be hitting this? > https://issues.apache.org/jira/browse/SPARK-3178 > > > > On Sun, Aug 24, 2014 at 10:21 AM, Forest D <dev24a...@gmail.com> wrote: > >> Hi folks, > >> > >> I have been trying to run the AMPLab’s twitter streaming example > >> ( > http://ampcamp.berkeley.edu/big-data-mini-course/realtime-processing-with-spark-streaming.html > ) > >> in the last 2 days.I have encountered the same error messages as shown > >> below: > >> > >> 14/08/24 17:14:22 ERROR client.AppClient$ClientActor: All masters are > >> unresponsive! Giving up. > >> 14/08/24 17:14:22 ERROR cluster.SparkDeploySchedulerBackend: Spark > cluster > >> looks dead, giving up. > >> [error] (Thread-39) org.apache.spark.SparkException: Job aborted: Spark > >> cluster looks down > >> 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:262) > >> at > >> > scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:975) > >> at > >> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1478) > >> at > >> > scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104) > >> [trace] Stack trace suppressed: run last compile:run for the full > output. > >> ------------------------------------------- > >> Time: 1408900463000 ms > >> ------------------------------------------- > >> > >> 14/08/24 17:14:23 WARN scheduler.TaskSchedulerImpl: Initial job has not > >> accepted any resources; check your cluster UI to ensure that workers are > >> registered and have sufficient memory > >> ------------------------------------------- > >> Time: 1408900464000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900465000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900466000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900467000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900468000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900469000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900470000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900471000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900472000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900473000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900474000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900475000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900476000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900477000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900478000 ms > >> ------------------------------------------- > >> > >> 14/08/24 17:14:38 WARN scheduler.TaskSchedulerImpl: Initial job has not > >> accepted any resources; check your cluster UI to ensure that workers are > >> registered and have sufficient memory > >> ------------------------------------------- > >> Time: 1408900479000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900480000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900481000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900482000 ms > >> ------------------------------------------- > >> > >> 14/08/24 17:14:42 ERROR client.AppClient$ClientActor: All masters are > >> unresponsive! Giving up. > >> ------------------------------------------- > >> Time: 1408900483000 ms > >> ------------------------------------------- > >> > >> ------------------------------------------- > >> Time: 1408900484000 ms > >> ------------------------------------------- > >> > >> > >> I checked my cluster status and found 0 memory is used.. > >> > >> Workers: 5 > >> Cores: 20 Total, 0 Used > >> Memory: 68.2 GB Total, 0.0 B Used > >> Applications: 0 Running, 0 Completed > >> Drivers: 0 Running, 0 Completed > >> > >> Anyone can shed some light on this issue? > >> > >> Thanks, > >> Senhua > > > > > > > > -- > > Jon Haddad > > http://www.rustyrazorblade.com > > twitter: rustyrazorblade > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > > For additional commands, e-mail: user-h...@spark.apache.org > > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >
