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Posted to issues@spark.apache.org by "Richard Marscher (JIRA)" <ji...@apache.org> on 2015/09/29 20:45:04 UTC

[jira] [Commented] (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=14935614#comment-14935614 ] 

Richard Marscher commented on SPARK-2243:
-----------------------------------------

To add another potential use case. We run several driver applications that programmatically submit work to a Spark Standalone cluster. We are able to allocate and share a single SparkContext decently enough so far. However we have seen an optimization in our code to separate our job DAG to have a first step that doesn't really need all the resources of the cluster. We are trying to support as many concurrent jobs as we can so it is important we don't block cluster resources on a phase that is not necessary. It would be great if we could create a separate SparkContext in the "local" mode on the driver to execute these smaller parts of the DAG up front without taking cluster resources. We could write this outside Spark, but it would be much nicer to maintain the DAG we already wrote and leverage code sharing and flexibility.

> 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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