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https://issues.apache.org/jira/browse/HIVE-7540?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14085539#comment-14085539
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Brock Noland commented on HIVE-7540:
------------------------------------
Hi [~lirui],
It seems this related to serializing a closure as opposed to data. I talked
with [~sandyr] and it seems that using Writable serialization is probably
difficult/impossible. It looks like the Spark folks have also tried using Kryo
to [serialize
closures|http://mail-archives.apache.org/mod_mbox/spark-dev/201405.mbox/%3CCAPh_B=Z3mNZp4A=B3M9TnQqe6n+foB6fQSmLEkVwB+mUbb=a...@mail.gmail.com%3E].
Can you try creating a class HiveBytesWritable which extends from BytesWritable
and implements Serializable and then transform the objects into that class
before the soryByKey?
> NotSerializableException encountered when using sortByKey transformation
> ------------------------------------------------------------------------
>
> Key: HIVE-7540
> URL: https://issues.apache.org/jira/browse/HIVE-7540
> Project: Hive
> Issue Type: Bug
> Components: Spark
> Environment: Spark-1.0.1
> Reporter: Rui Li
>
> This exception is thrown when sortByKey is used as the shuffle transformation
> between MapWork and ReduceWork:
> {quote}
> org.apache.spark.SparkException: Job aborted due to stage failure: Task not
> serializable: java.io.NotSerializableException:
> org.apache.hadoop.io.BytesWritable
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1049)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1033)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1031)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1031)
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:772)
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:715)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$submitStage$4.apply(DAGScheduler.scala:719)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$submitStage$4.apply(DAGScheduler.scala:718)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:718)
> at
> org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:699)
> …
> {quote}
> The root cause is that the RangePartitioner used by sortByKey contains
> rangeBounds: Array[BytesWritable], which is considered not serializable in
> spark.
> A workaround to this issue is to set the number of partitions to 1 when
> calling sortByKey, in which case the rangeBounds will be just an empty array.
> NO PRECOMMIT TESTS. This is for spark branch only.
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