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From "Stephen Boesch (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-2243) Support multiple SparkContexts in the same JVM
Date Sun, 14 Aug 2016 19:58:20 GMT

    [ https://issues.apache.org/jira/browse/SPARK-2243?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15420467#comment-15420467
] 

Stephen Boesch commented on SPARK-2243:
---------------------------------------

Given this were not going to be fixed: please update documentation and fix the following warning:

WARN SparkContext: Multiple running SparkContexts detected 
in the same JVM!
org.apache.spark.SparkException: Only one SparkContext may be running in
this JVM (see SPARK-2243). To ignore this error, 
set spark.driver.allowMultipleContexts = true



> 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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