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From "Xuefu Zhang (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (HIVE-8545) Exception when casting Text to BytesWritable [Spark Branch]
Date Thu, 23 Oct 2014 17:26:33 GMT

    [ https://issues.apache.org/jira/browse/HIVE-8545?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14181596#comment-14181596
] 

Xuefu Zhang edited comment on HIVE-8545 at 10/23/14 5:25 PM:
-------------------------------------------------------------

I think we can get this in first, and log a followup JIRA to investigate the test failure
above. [~csun], could you load up your latest patch with changes discussed above?


was (Author: xuefuz):
I think we can get this in first, and log a followup JIRA to investigate the test failure
above.

> Exception when casting Text to BytesWritable [Spark Branch]
> -----------------------------------------------------------
>
>                 Key: HIVE-8545
>                 URL: https://issues.apache.org/jira/browse/HIVE-8545
>             Project: Hive
>          Issue Type: Bug
>          Components: Spark
>            Reporter: Chao
>            Assignee: Chao
>         Attachments: HIVE-8545.1-spark.patch, HIVE-8545.2-spark.patch, HIVE-8545.3-spark.patch,
HIVE-8545.4-spark.patch, HIVE-8545.5-spark.patch
>
>
> With the current multi-insertion implementation, when caching is enabled for input RDD,
query may fail with the following exception:
> {noformat}
> 2014-10-21 13:57:34,742 WARN  [task-result-getter-0]: scheduler.TaskSetManager (Logging.scala:logWarning(71))
- Lost task 0.0 in stage 1.0 (TID 1, localhost): java.lang.ClassCastException: org.apache.hadoop.io.Text
cannot be cast to org.apache.hadoop.io.BytesWritable
>         org.apache.hadoop.hive.ql.exec.spark.MapInput$CopyFunction.call(MapInput.java:67)
>         org.apache.hadoop.hive.ql.exec.spark.MapInput$CopyFunction.call(MapInput.java:61)
>         org.apache.spark.api.java.JavaPairRDD$$anonfun$pairFunToScalaFun$1.apply(JavaPairRDD.scala:1002)
>         org.apache.spark.api.java.JavaPairRDD$$anonfun$pairFunToScalaFun$1.apply(JavaPairRDD.scala:1002)
>         scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>         org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:234)
>         org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:163)
>         org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:70)
>         org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
>         org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>         org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>         org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
>         org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
>         org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>         org.apache.spark.scheduler.Task.run(Task.scala:56)
>         org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:181)
>         java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>         java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>         java.lang.Thread.run(Thread.java:745)
> {noformat}
> The fix should be easy. However, interestingly, this error doesn't show up when the caching
is turned off. We need to find out why.



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