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Posted to issues@spark.apache.org by "Reynold Xin (JIRA)" <ji...@apache.org> on 2015/01/25 02:04:07 UTC

[jira] [Comment Edited] (SPARK-5235) Determine serializability of SQLContext

    [ https://issues.apache.org/jira/browse/SPARK-5235?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14290905#comment-14290905 ] 

Reynold Xin edited comment on SPARK-5235 at 1/25/15 1:00 AM:
-------------------------------------------------------------

Sean - this was not done. We merged a patch to make it serializable again, but for 1.3 we should decide whether we want it to be serializable for real.


was (Author: rxin):
Sean - this was not done. We merged a patch to make it serializable again, but for 1.3 we should decide whether we wanted to be serializable for real.

> Determine serializability of SQLContext
> ---------------------------------------
>
>                 Key: SPARK-5235
>                 URL: https://issues.apache.org/jira/browse/SPARK-5235
>             Project: Spark
>          Issue Type: Sub-task
>            Reporter: Alex Baretta
>             Fix For: 1.3.0
>
>
> The SQLConf field in SQLContext is neither Serializable nor transient. Here's the stack trace I get when running SQL queries against a Parquet file.
> {code}
> Exception in thread "Thread-43" org.apache.spark.SparkException: Job aborted due to stage failure: Task not serializable: java.io.NotSerializableException: org.apache.spark.sql.SQLConf
>         at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1195)
>         at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1184)
>         at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1183)
>         at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>         at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>         at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1183)
>         at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:843)
>         at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:779)
>         at org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:763)
>         at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1364)
>         at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
>         at org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1356)
>         at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
>         at akka.actor.ActorCell.invoke(ActorCell.scala:487)
>         at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
>         at akka.dispatch.Mailbox.run(Mailbox.scala:220)
>         at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
>         at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
>         at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
>         at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
>         at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
> {code}



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