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
