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Posted to issues@spark.apache.org by "Jason Hubbard (JIRA)" <ji...@apache.org> on 2015/04/02 01:40:54 UTC
[jira] [Comment Edited] (SPARK-2243) Support multiple SparkContexts
in the same JVM
[ https://issues.apache.org/jira/browse/SPARK-2243?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14391770#comment-14391770 ]
Jason Hubbard edited comment on SPARK-2243 at 4/1/15 11:40 PM:
---------------------------------------------------------------
Apologizing for being flippant is a bit of an oxymoron isn't it?
The answer you proprose is the only one available, but it isn't a real solution, it's a workaround. Obviously running in separate JVMs causes other issues with overhead of starting multiple JVMs and the complexity of having to serialize data so they can communicate. Having multiple workloads in the same SparkContext is what I have chosen, but sometimes you would like different settings for the different workloads which this would now not allow.
was (Author: jahubba):
Apologizing for being flippant is a bit of an oxymoron isn't it?
The answer you purpose is the only one available, but it isn't a real solution, it's a workaround. Obviously running in separate JVMs causes other issues with overhead of starting multiple JVMs and the complexity of having to serialize data so they can communicate. Having multiple workloads in the same SparkContext is what I have chosen, but sometimes you would like different settings for the different workloads which this would now not allow.
> Support multiple SparkContexts in the same JVM
> ----------------------------------------------
>
> Key: SPARK-2243
> URL: https://issues.apache.org/jira/browse/SPARK-2243
> Project: Spark
> Issue Type: New Feature
> Components: Block Manager, Spark Core
> Affects Versions: 0.7.0, 1.0.0, 1.1.0
> Reporter: Miguel Angel Fernandez Diaz
>
> We're developing a platform where we create several Spark contexts for carrying out different calculations. Is there any restriction when using several Spark contexts? We have two contexts, one for Spark calculations and another one for Spark Streaming jobs. The next error arises when we first execute a Spark calculation and, once the execution is finished, a Spark Streaming job is launched:
> {code}
> 14/06/23 16:40:08 ERROR executor.Executor: Exception in task ID 0
> java.io.FileNotFoundException: http://172.19.0.215:47530/broadcast_0
> at sun.net.www.protocol.http.HttpURLConnection.getInputStream(HttpURLConnection.java:1624)
> at org.apache.spark.broadcast.HttpBroadcast$.read(HttpBroadcast.scala:156)
> at org.apache.spark.broadcast.HttpBroadcast.readObject(HttpBroadcast.scala:56)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1017)
> at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1893)
> at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
> at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)
> at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)
> at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
> at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:40)
> at org.apache.spark.scheduler.ResultTask$.deserializeInfo(ResultTask.scala:63)
> at org.apache.spark.scheduler.ResultTask.readExternal(ResultTask.scala:139)
> at java.io.ObjectInputStream.readExternalData(ObjectInputStream.java:1837)
> at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1796)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
> at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:40)
> at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:62)
> at org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:193)
> at org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:45)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:176)
> 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)
> 14/06/23 16:40:08 WARN scheduler.TaskSetManager: Lost TID 0 (task 0.0:0)
> 14/06/23 16:40:08 WARN scheduler.TaskSetManager: Loss was due to java.io.FileNotFoundException
> java.io.FileNotFoundException: http://172.19.0.215:47530/broadcast_0
> at sun.net.www.protocol.http.HttpURLConnection.getInputStream(HttpURLConnection.java:1624)
> at org.apache.spark.broadcast.HttpBroadcast$.read(HttpBroadcast.scala:156)
> at org.apache.spark.broadcast.HttpBroadcast.readObject(HttpBroadcast.scala:56)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1017)
> at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1893)
> at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
> at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)
> at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)
> at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
> at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:40)
> at org.apache.spark.scheduler.ResultTask$.deserializeInfo(ResultTask.scala:63)
> at org.apache.spark.scheduler.ResultTask.readExternal(ResultTask.scala:139)
> at java.io.ObjectInputStream.readExternalData(ObjectInputStream.java:1837)
> at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1796)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
> at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:40)
> at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:62)
> at org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:193)
> at org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:45)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:176)
> 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)
> 14/06/23 16:40:08 ERROR scheduler.TaskSetManager: Task 0.0:0 failed 1 times; aborting job
> 14/06/23 16:40:08 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
> 14/06/23 16:40:08 INFO scheduler.DAGScheduler: Failed to run runJob at NetworkInputTracker.scala:182
> [WARNING]
> org.apache.spark.SparkException: Job aborted: Task 0.0:0 failed 1 times (most recent failure: Exception failure: java.io.FileNotFoundException: http://172.19.0.215:47530/broadcast_0)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1020)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1018)
> at scala.collection.mutable.ResizableArray$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$$abortStage(DAGScheduler.scala:1018)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:604)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:604)
> at scala.Option.foreach(Option.scala:236)
> at org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:604)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:190)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
> at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:385)
> 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)
> 14/06/23 16:40:09 INFO dstream.ForEachDStream: metadataCleanupDelay = 3600
> {code}
> So far, we are working on localhost. Any clue about where this error is coming from? Any workaround to solve the issue?
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