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https://issues.apache.org/jira/browse/SPARK-1764?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13995484#comment-13995484
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Bernardo Gomez Palacio commented on SPARK-1764:
-----------------------------------------------
We just ran `sc.parallelize(range(100)).map(lambda n: n * 2).collect()` on a
Mesos 0.18.1 cluster with the latest spark and it worked. Could you confirm the
Spark & Mesos version you are using (if using master please include the
sha/commit hash).
> EOF reached before Python server acknowledged
> ---------------------------------------------
>
> Key: SPARK-1764
> URL: https://issues.apache.org/jira/browse/SPARK-1764
> Project: Spark
> Issue Type: Bug
> Components: Mesos, PySpark
> Affects Versions: 1.0.0
> Reporter: Bouke van der Bijl
> Priority: Blocker
> Labels: mesos, pyspark
>
> I'm getting "EOF reached before Python server acknowledged" while using
> PySpark on Mesos. The error manifests itself in multiple ways. One is:
> 14/05/08 18:10:40 ERROR DAGSchedulerActorSupervisor: eventProcesserActor
> failed due to the error EOF reached before Python server acknowledged;
> shutting down SparkContext
> And the other has a full stacktrace:
> 14/05/08 18:03:06 ERROR OneForOneStrategy: EOF reached before Python server
> acknowledged
> org.apache.spark.SparkException: EOF reached before Python server acknowledged
> at
> org.apache.spark.api.python.PythonAccumulatorParam.addInPlace(PythonRDD.scala:416)
> at
> org.apache.spark.api.python.PythonAccumulatorParam.addInPlace(PythonRDD.scala:387)
> at org.apache.spark.Accumulable.$plus$plus$eq(Accumulators.scala:71)
> at
> org.apache.spark.Accumulators$$anonfun$add$2.apply(Accumulators.scala:279)
> at
> org.apache.spark.Accumulators$$anonfun$add$2.apply(Accumulators.scala:277)
> at
> scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
> at
> scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:98)
> at
> scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:98)
> at
> scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:226)
> at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:39)
> at scala.collection.mutable.HashMap.foreach(HashMap.scala:98)
> at
> scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
> at org.apache.spark.Accumulators$.add(Accumulators.scala:277)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:818)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1204)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
> at
> akka.dispatch.ForkJoinExecutorConfigurator$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)
> This error causes the SparkContext to shutdown. I have not been able to
> reliably reproduce this bug, it seems to happen randomly, but if you run
> enough tasks on a SparkContext it'll hapen eventually
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