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https://issues.apache.org/jira/browse/HIVE-15054?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15608577#comment-15608577
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Rui Li commented on HIVE-15054:
-------------------------------
Thanks for the explanations Aihua.
I'm not sure which format is better: {{partitionId_attemptNumber}}, or just
{{taskAttemptId}}. Does hive rely on the attemptNumber to identify the multiple
outputs for the same task/partition?
> Hive insertion query execution fails on Hive on Spark
> -----------------------------------------------------
>
> Key: HIVE-15054
> URL: https://issues.apache.org/jira/browse/HIVE-15054
> Project: Hive
> Issue Type: Bug
> Components: Spark
> Affects Versions: 2.0.0
> Reporter: Aihua Xu
> Assignee: Aihua Xu
> Attachments: HIVE-15054.1.patch
>
>
> The query of {{insert overwrite table tbl1}} sometimes will fail with the
> following errors. Seems we are constructing taskAttemptId with partitionId
> which is not unique if there are multiple attempts.
> {noformat}
> ava.lang.IllegalStateException: Hit error while closing operators - failing
> tree: org.apache.hadoop.hive.ql.metadata.HiveException: Unable to rename
> output from:
> hdfs://table1/.hive-staging_hive_2016-06-14_01-53-17_386_3231646810118049146-9/_task_tmp.-ext-10002/_tmp.002148_0
> to:
> hdfs://table1/.hive-staging_hive_2016-06-14_01-53-17_386_3231646810118049146-9/_tmp.-ext-10002/002148_0
> at
> org.apache.hadoop.hive.ql.exec.spark.SparkMapRecordHandler.close(SparkMapRecordHandler.java:202)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.closeRecordProcessor(HiveMapFunctionResultList.java:58)
> at
> org.apache.hadoop.hive.ql.exec.spark.HiveBaseFunctionResultList$ResultIterator.hasNext(HiveBaseFunctionResultList.java:106)
> at
> scala.collection.convert.Wrappers$JIteratorWrapper.hasNext(Wrappers.scala:41)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at
> org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$1$$anonfun$apply$15.apply(AsyncRDDActions.scala:120)
> {noformat}
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