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Posted to issues@spark.apache.org by "Sudharma Puranik (JIRA)" <ji...@apache.org> on 2015/04/02 15:28:47 UTC

[jira] [Issue Comment Deleted] (SPARK-2243) Support multiple SparkContexts in the same JVM

     [ https://issues.apache.org/jira/browse/SPARK-2243?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sudharma Puranik updated SPARK-2243:
------------------------------------
    Comment: was deleted

(was: [~jahubba] : Running on the seperate JVMs is not a workaround but I its about sharing the SparkContext understanding your processor and memory. Nonetheless Running multiple sparkcontexts on JVM is total different aspect which they are still skeptical or whatsoever the reason. But to set the things straight, its not workaround.)

> 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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