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https://issues.apache.org/jira/browse/HIVE-7613?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14120697#comment-14120697
]
Suhas Satish commented on HIVE-7613:
------------------------------------
as a part of this work, we should also enable auto_sortmerge_join_1.q which
currently fails with
{code:title=auto_sortmerge_join_1.stackTrace|borderStyle=solid}
2014-09-03 16:12:59,607 ERROR [main]: spark.SparkClient
(SparkClient.java:execute(166)) - Error executing Spark Plan
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID
1, localhost): java.lang.RuntimeException:
org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime Error while
processing row {"key":"0","value":"val_0","ds":"2008-04-08"}
org.apache.hadoop.hive.ql.exec.spark.SparkMapRecordHandler.processRow(SparkMapRecordHandler.java:151)
org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.processNextRecord(HiveMapFunctionResultList.java:47)
org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.processNextRecord(HiveMapFunctionResultList.java:28)
org.apache.hadoop.hive.ql.exec.spark.HiveBaseFunctionResultList$ResultIterator.hasNext(HiveBaseFunctionResultList.java:99)
scala.collection.convert.Wrappers$JIteratorWrapper.hasNext(Wrappers.scala:41)
scala.collection.Iterator$class.foreach(Iterator.scala:727)
scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
org.apache.spark.shuffle.hash.HashShuffleWriter.write(HashShuffleWriter.scala:65)
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
org.apache.spark.scheduler.Task.run(Task.scala:54)
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1177)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1166)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1165)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1165)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
at scala.Option.foreach(Option.scala:236)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:688)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1383)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at
akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
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}
> Research optimization of auto convert join to map join [Spark branch]
> ---------------------------------------------------------------------
>
> Key: HIVE-7613
> URL: https://issues.apache.org/jira/browse/HIVE-7613
> Project: Hive
> Issue Type: Sub-task
> Components: Spark
> Reporter: Chengxiang Li
> Assignee: Szehon Ho
> Priority: Minor
> Attachments: HIve on Spark Map join background.docx
>
>
> ConvertJoinMapJoin is an optimization the replaces a common join(aka shuffle
> join) with a map join(aka broadcast or fragment replicate join) when
> possible. we need to research how to make it workable with Hive on Spark.
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