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https://issues.apache.org/jira/browse/HIVE-15054?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15616426#comment-15616426
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Aihua Xu commented on HIVE-15054:
---------------------------------
[~lirui] You are right that hive needs to use the same id to figure out it's
the same task. Spark has different taskId for different task attempt. Seems
partitionId is the closest choice.
> 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, HIVE-15054.2.patch,
> HIVE-15054.3.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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