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
