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https://issues.apache.org/jira/browse/HIVE-9342?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14276730#comment-14276730
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Hive QA commented on HIVE-9342:
-------------------------------
{color:red}Overall{color}: -1 at least one tests failed
Here are the results of testing the latest attachment:
https://issues.apache.org/jira/secure/attachment/12692178/HIVE-9342.2-spark.patch
{color:red}ERROR:{color} -1 due to 2 failed/errored test(s), 7307 tests executed
*Failed tests:*
{noformat}
org.apache.hadoop.hive.cli.TestCliDriver.testCliDriver_mapjoin_memcheck
org.apache.hadoop.hive.cli.TestSparkCliDriver.testCliDriver_optimize_nullscan
{noformat}
Test results:
http://ec2-174-129-184-35.compute-1.amazonaws.com/jenkins/job/PreCommit-HIVE-SPARK-Build/641/testReport
Console output:
http://ec2-174-129-184-35.compute-1.amazonaws.com/jenkins/job/PreCommit-HIVE-SPARK-Build/641/console
Test logs:
http://ec2-50-18-27-0.us-west-1.compute.amazonaws.com/logs/PreCommit-HIVE-SPARK-Build-641/
Messages:
{noformat}
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: 2 tests failed
{noformat}
This message is automatically generated.
ATTACHMENT ID: 12692178 - PreCommit-HIVE-SPARK-Build
> add num-executors / executor-cores / executor-memory option support for hive
> on spark in Yarn mode
> --------------------------------------------------------------------------------------------------
>
> Key: HIVE-9342
> URL: https://issues.apache.org/jira/browse/HIVE-9342
> Project: Hive
> Issue Type: Improvement
> Components: spark-branch
> Affects Versions: spark-branch
> Reporter: Pierre Yin
> Priority: Minor
> Labels: spark
> Fix For: spark-branch
>
> Attachments: HIVE-9342.1-spark.patch, HIVE-9342.2-spark.patch
>
>
> When I run hive on spark with Yarn mode, I want to control some yarn option,
> such as --num-executors, --executor-cores, --executor-memory.
> We can append these options into argv in SparkClientImpl.
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