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From "Hive QA (JIRA)" <>
Subject [jira] [Commented] (HIVE-8054) Disable hive.optimize.union.remove when hive.execution.engine=spark [Spark Branch]
Date Mon, 15 Sep 2014 20:02:34 GMT


Hive QA commented on HIVE-8054:

{color:red}Overall{color}: -1 at least one tests failed

Here are the results of testing the latest attachment:

{color:red}ERROR:{color} -1 due to 5 failed/errored test(s), 6343 tests executed
*Failed tests:*

Test results:
Console output:
Test logs:

Executing org.apache.hive.ptest.execution.PrepPhase
Executing org.apache.hive.ptest.execution.ExecutionPhase
Executing org.apache.hive.ptest.execution.ReportingPhase
Tests exited with: TestsFailedException: 5 tests failed

This message is automatically generated.


> Disable hive.optimize.union.remove when hive.execution.engine=spark [Spark Branch]
> ----------------------------------------------------------------------------------
>                 Key: HIVE-8054
>                 URL:
>             Project: Hive
>          Issue Type: Improvement
>          Components: Spark
>            Reporter: Xuefu Zhang
>            Assignee: Na Yang
>              Labels: Spark-M1
>         Attachments: HIVE-8054-spark.patch, HIVE-8054.2-spark.patch
> Option hive.optimize.union.remove introduced in HIVE-3276 removes union operators from
the operator graph in certain cases as an optimization reduce the number of MR jobs. While
making sense in MR, this optimization is actually harmful to an execution engine such as Spark,
which natives supports union without requiring additional jobs. This is because removing union
operator creates disjointed operator graphs, each graph generating a job, and thus this optimization
requires more jobs to run the query. Not to mention the additional complexity handling linked
FS descriptors.
> I propose that we disable such optimization when the execution engine is Spark.

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