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From "Xuefu Zhang (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-7540) NotSerializableException encountered when using sortByKey transformation
Date Tue, 05 Aug 2014 02:34:14 GMT

    [ https://issues.apache.org/jira/browse/HIVE-7540?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14085695#comment-14085695
] 

Xuefu Zhang commented on HIVE-7540:
-----------------------------------

It's good to try this out. However, I still think the right solution is in Spark. Any additional
processing at per row level will make performance suffer. If there is absolutely impossible
in Spark, it's helpful to provide a clear reason for that. 

> 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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