Can you file a JIRA? https://issues.apache.org/jira/browse/SPARK
On Wed, Jul 8, 2015 at 12:47 AM, nizang <[email protected]> wrote: > hi, > > I'm running spark standalone cluster (1.4.0). I have some applications > running with scheduler every hour. I found that on one of the executions, > the job got to be FINISHED after very few seconds (instead of ~5 minutes), > and in the logs on the master, I can see the following exception: > > org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 > in > stage 1.0 failed 4 times, most recent failure: Lost task 1.3 in stage 1.0 > (TID 20, 172.31.6.203): java.io.IOException: > java.lang.reflect.InvocationTargetException > at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1257) > at > > org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:165) > at > > org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:64) > at > > org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:64) > at > > org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:88) > at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70) > at > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:59) > at org.apache.spark.scheduler.Task.run(Task.scala:70) > at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) > at > > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) > at > > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) > at java.lang.Thread.run(Thread.java:745) > Caused by: java.lang.reflect.InvocationTargetException > at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native > Method) > at > > sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57) > at > > sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) > at java.lang.reflect.Constructor.newInstance(Constructor.java:526) > at > > org.apache.spark.io.CompressionCodec$.createCodec(CompressionCodec.scala:68) > at > > org.apache.spark.io.CompressionCodec$.createCodec(CompressionCodec.scala:60) > at > org.apache.spark.broadcast.TorrentBroadcast.org > $apache$spark$broadcast$TorrentBroadcast$$setConf(TorrentBroadcast.scala:73) > at > > org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1.apply(TorrentBroadcast.scala:167) > at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1254) > ... 11 more > Caused by: java.lang.IllegalArgumentException > at > > org.apache.spark.io.SnappyCompressionCodec.<init>(CompressionCodec.scala:152) > ... 20 more > > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.org > $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1266) > at > > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1257) > at > > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1256) > at > > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at > scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1256) > at > > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730) > at > > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730) > at scala.Option.foreach(Option.scala:236) > at > > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:730) > at > > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1450) > at > > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1411) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > > This job was successful many times before and after this run, and other > jobs > were successful in that time > > Any idea what can cause that? > > thanks, nizan > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/SnappyCompressionCodec-on-the-master-tp23711.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [email protected] > For additional commands, e-mail: [email protected] > >
