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https://issues.apache.org/jira/browse/SPARK-2243?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15103419#comment-15103419
]
Jason Hubbard commented on SPARK-2243:
--------------------------------------
There is a limit to how small you can make the heap before causing OOM and
causing gc issue and poor performance making it too big. You got it exactly
right, jobs have different task profiles.
Having multiple jvms and multiple yarn resource requests will take longer
and have more overhead than a single jvm and a single application master.
It may be a non goal to you but that doesn't make it generally undesirable.
> 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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