I upped the ulimit to 128k files on all nodes. Job crashed again with "DAGScheduler: Failed to run runJob at ReceiverTracker.scala:275". Couldn't get the logs because I killed the job and looks like yarn wipe the container logs (not sure why it wipes the logs under /var/log/hadoop-yarn/container). Next time, I will grab the logs while the job is still active/zombie.
So is there a limit on how many times a receiver is re-spawned? Thanks, Tim On Thu, Aug 28, 2014 at 10:06 PM, Tathagata Das <tathagata.das1...@gmail.com> wrote: > It did. It got failed and respawned 4 times. > In this case, the too many open files is a sign that you need increase the > system-wide limit of open files. > Try adding ulimit -n 16000 to your conf/spark-env.sh. > > TD > > > On Thu, Aug 28, 2014 at 5:29 PM, Tim Smith <secs...@gmail.com> wrote: >> >> Appeared after running for a while. I re-ran the job and this time, it >> crashed with: >> 14/08/29 00:18:50 WARN ReceiverTracker: Error reported by receiver for >> stream 0: Error in block pushing thread - java.net.SocketException: Too many >> open files >> >> Shouldn't the failed receiver get re-spawned on a different worker? >> >> >> >> On Thu, Aug 28, 2014 at 4:12 PM, Tathagata Das >> <tathagata.das1...@gmail.com> wrote: >>> >>> Do you see this error right in the beginning or after running for >>> sometime? >>> >>> The root cause seems to be that somehow your Spark executors got killed, >>> which killed receivers and caused further errors. Please try to take a look >>> at the executor logs of the lost executor to find what is the root cause >>> that caused the executor to fail. >>> >>> TD >>> >>> >>> On Thu, Aug 28, 2014 at 3:54 PM, Tim Smith <secs...@gmail.com> wrote: >>>> >>>> Hi, >>>> >>>> Have a Spark-1.0.0 (CDH5) streaming job reading from kafka that died >>>> with: >>>> >>>> 14/08/28 22:28:15 INFO DAGScheduler: Failed to run runJob at >>>> ReceiverTracker.scala:275 >>>> Exception in thread "Thread-59" 14/08/28 22:28:15 INFO >>>> YarnClientClusterScheduler: Cancelling stage 2 >>>> 14/08/28 22:28:15 INFO DAGScheduler: Executor lost: 5 (epoch 4) >>>> 14/08/28 22:28:15 INFO BlockManagerMasterActor: Trying to remove >>>> executor 5 from BlockManagerMaster. >>>> 14/08/28 22:28:15 INFO BlockManagerMaster: Removed 5 successfully in >>>> removeExecutor >>>> org.apache.spark.SparkException: Job aborted due to stage failure: Task >>>> 2.0:0 failed 4 times, most recent failure: TID 6481 on host >>>> node-dn1-1.ops.sfdc.net failed for unknown reason >>>> Driver stacktrace: >>>> at >>>> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1033) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1017) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1015) >>>> at >>>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) >>>> at >>>> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1015) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633) >>>> at scala.Option.foreach(Option.scala:236) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:633) >>>> at >>>> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1207) >>>> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498) >>>> at akka.actor.ActorCell.invoke(ActorCell.scala:456) >>>> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237) >>>> at akka.dispatch.Mailbox.run(Mailbox.scala:219) >>>> at >>>> akka.dispatch.ForkJoinExecutorConfigurator$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) >>>> >>>> >>>> Any insights into this error? >>>> >>>> Thanks, >>>> >>>> Tim >>>> >>> >> > --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
