I wonder if it’s trying to write an empty rdd to a text file. Can you give the CLI options and a snippet of data?
Also have you successfully run this on the toy data in the resource dir? There is a script to run it locally that you can adapt for running on a cluster. This will eliminate any cluster problem. On Sep 13, 2014, at 1:13 PM, Phil Wills <[email protected]> wrote: Here's the master log from the line with the stack trace to termination: 14/09/12 15:54:55 INFO scheduler.DAGScheduler: Failed to run saveAsTextFile at TextDelimitedReaderWriter.scala:288 Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 8.0:3 failed 4 times, most recent failure: TID 448 on host ip-10-105-176-77.eu-west-1.compute.internal failed for unknown reason Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1049) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1033) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1031) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1031) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:635) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:635) at scala.Option.foreach(Option.scala:236) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:635) at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1234) at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498) at akka.actor.ActorCell.invoke(ActorCell.scala:456) at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237) at akka.dispatch.Mailbox.run(Mailbox.scala:219) at akka.dispatch.ForkJoinExecutorConfigurator$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) 14/09/12 15:54:55 INFO scheduler.DAGScheduler: Executor lost: 8 (epoch 20) 14/09/12 15:54:55 INFO storage.BlockManagerMasterActor: Trying to remove executor 8 from BlockManagerMaster. 14/09/12 15:54:55 INFO storage.BlockManagerMaster: Removed 8 successfully in removeExecutor 14/09/12 15:54:55 INFO storage.BlockManagerInfo: Registering block manager ip-10-105-176-77.eu-west-1.compute.internal:58803 with 3.4 GB RAM 14/09/12 15:54:55 INFO cluster.SparkDeploySchedulerBackend: Registered executor: Actor[akka.tcp://[email protected]:56590/user/Executor#1456047585] with ID 9 On Sat, Sep 13, 2014 at 4:21 PM, Pat Ferrel <[email protected]> wrote: > It’s not an error I’ve seen but they can tend to be pretty cryptic. Could > you post more of the stack trace? > > On Sep 12, 2014, at 2:55 PM, Phil Wills <[email protected]> wrote: > > I've tried on 1.0.1 and 1.0.2, updating the pom to 1.0.2 when running on > that. I used the spark-ec2 scripts to set up the cluster. > > I might be able to share the data I'll mull it over the weekend to make > sure there's nothing sensitive, or if there's a way I can transform it to > that point. > > Phil > > > On Fri, Sep 12, 2014 at 6:30 PM, Pat Ferrel <[email protected]> wrote: > >> The mahout pom says 1.0.1 but I’m running fine on 1.0.2 >> >> >> On Sep 12, 2014, at 10:08 AM, Pat Ferrel <[email protected]> wrote: >> >> Is it a mature Spark cluster, what version of Spark? >> >> If you can share the data I can try it on mine. >> >> On Sep 12, 2014, at 9:42 AM, Phil Wills <[email protected]> wrote: >> >> I've been experimenting with the fairly new ItemSimilarityDriver, which > is >> working fine up until the point it tries to write out it's results. >> Initially I was getting an issue with the akka frameSize being too small, >> but after expanding that I'm now getting a much more cryptic error: >> >> 14/09/12 15:54:55 INFO scheduler.DAGScheduler: Failed to run > saveAsTextFile >> at TextDelimitedReaderWriter.scala:288 >> Exception in thread "main" org.apache.spark.SparkException: Job aborted > due >> to stage failure: Task 8.0:3 failed 4 times, most recent failure: TID 448 >> on host ip-10-105-176-77.eu-west-1.compute.internal failed for unknown >> reason >> >> This is from the master node, but there doesn't seem to be anything more >> intelligible in the slave node logs. >> >> I've tried writing to the local file system as well as s3n and can see > it's >> not an access problem, as I am seeing a zero length file appear. >> >> Thanks for any pointers and apologies if this would be better to ask on > the >> Spark list, >> >> Phil >> >> >> > >
