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
