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Posted to issues@spark.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2017/10/10 02:54:01 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=16198062#comment-16198062 ]
ASF GitHub Bot commented on SPARK-2243:
---------------------------------------
GitHub user 561152 opened a pull request:
https://github.com/apache/incubator-predictionio/pull/441
pio batchpredict error
pio batchpredict --input /tmp/pio/batchpredict-input.json --output /tmp/pio/batchpredict-output.json
[WARN] [ALSModel] Product factor is not cached. Prediction could be slow.
Exception in thread "main" 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. The currently running SparkContext was created at:
org.apache.spark.SparkContext.<init>(SparkContext.scala:76)
org.apache.predictionio.workflow.WorkflowContext$.apply(WorkflowContext.scala:45)
org.apache.predictionio.workflow.BatchPredict$.run(BatchPredict.scala:160)
org.apache.predictionio.workflow.BatchPredict$$anonfun$main$1$$anonfun$apply$2.apply(BatchPredict.scala:121)
org.apache.predictionio.workflow.BatchPredict$$anonfun$main$1$$anonfun$apply$2.apply(BatchPredict.scala:117)
scala.Option.map(Option.scala:146)
org.apache.predictionio.workflow.BatchPredict$$anonfun$main$1.apply(BatchPredict.scala:117)
org.apache.predictionio.workflow.BatchPredict$$anonfun$main$1.apply(BatchPredict.scala:115)
scala.Option.map(Option.scala:146)
org.apache.predictionio.workflow.BatchPredict$.main(BatchPredict.scala:115)
org.apache.predictionio.workflow.BatchPredict.main(BatchPredict.scala)
sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
java.lang.reflect.Method.invoke(Method.java:498)
org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:738)
org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
at org.apache.spark.SparkContext$$anonfun$assertNoOtherContextIsRunning$2.apply(SparkContext.scala:2278)
at org.apache.spark.SparkContext$$anonfun$assertNoOtherContextIsRunning$2.apply(SparkContext.scala:2274)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.SparkContext$.assertNoOtherContextIsRunning(SparkContext.scala:2274)
at org.apache.spark.SparkContext$.markPartiallyConstructed(SparkContext.scala:2353)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:85)
at org.apache.predictionio.workflow.WorkflowContext$.apply(WorkflowContext.scala:45)
at org.apache.predictionio.workflow.BatchPredict$.run(BatchPredict.scala:183)
at org.apache.predictionio.workflow.BatchPredict$$anonfun$main$1$$anonfun$apply$2.apply(BatchPredict.scala:121)
at org.apache.predictionio.workflow.BatchPredict$$anonfun$main$1$$anonfun$apply$2.apply(BatchPredict.scala:117)
at scala.Option.map(Option.scala:146)
at org.apache.predictionio.workflow.BatchPredict$$anonfun$main$1.apply(BatchPredict.scala:117)
at org.apache.predictionio.workflow.BatchPredict$$anonfun$main$1.apply(BatchPredict.scala:115)
at scala.Option.map(Option.scala:146)
at org.apache.predictionio.workflow.BatchPredict$.main(BatchPredict.scala:115)
at org.apache.predictionio.workflow.BatchPredict.main(BatchPredict.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:738)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/apache/incubator-predictionio develop
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/incubator-predictionio/pull/441.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #441
----
commit a87b7a6d90e071f0c92455b1a157681bae8bdf2a
Author: Chan Lee <ch...@gmail.com>
Date: 2017-09-28T03:16:57Z
Bump version to 0.13.0-SNAPSHOT
commit 7339a16fd0fedeb2ab9a9fce79e13a561e5198f9
Author: Shinsuke Sugaya <sh...@apache.org>
Date: 2017-10-06T04:43:03Z
[PIO-125] Spark 2.2 support
Closes #436
commit 9017d7fae4a77246b63688508c3d56dedad177e0
Author: Donald Szeto <do...@apache.org>
Date: 2017-10-07T06:16:30Z
[PIO-133] Add DOAP
----
> 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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