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https://issues.apache.org/jira/browse/HIVE-9277?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14372510#comment-14372510
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Hive QA commented on HIVE-9277:
-------------------------------
{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/12706109/HIVE-9277.15.patch
{color:red}ERROR:{color} -1 due to 1 failed/errored test(s), 7819 tests executed
*Failed tests:*
{noformat}
org.apache.hadoop.hive.cli.TestCliDriver.testCliDriver_udaf_percentile_approx_23
{noformat}
Test results:
http://ec2-174-129-184-35.compute-1.amazonaws.com/jenkins/job/PreCommit-HIVE-TRUNK-Build/3102/testReport
Console output:
http://ec2-174-129-184-35.compute-1.amazonaws.com/jenkins/job/PreCommit-HIVE-TRUNK-Build/3102/console
Test logs:
http://ec2-174-129-184-35.compute-1.amazonaws.com/logs/PreCommit-HIVE-TRUNK-Build-3102/
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: 1 tests failed
{noformat}
This message is automatically generated.
ATTACHMENT ID: 12706109 - PreCommit-HIVE-TRUNK-Build
> Hybrid Hybrid Grace Hash Join
> -----------------------------
>
> Key: HIVE-9277
> URL: https://issues.apache.org/jira/browse/HIVE-9277
> Project: Hive
> Issue Type: New Feature
> Components: Physical Optimizer
> Reporter: Wei Zheng
> Assignee: Wei Zheng
> Labels: join
> Attachments: HIVE-9277.01.patch, HIVE-9277.02.patch,
> HIVE-9277.03.patch, HIVE-9277.04.patch, HIVE-9277.05.patch,
> HIVE-9277.06.patch, HIVE-9277.07.patch, HIVE-9277.08.patch,
> HIVE-9277.13.patch, HIVE-9277.14.patch, HIVE-9277.15.patch,
> High-leveldesignforHybridHybridGraceHashJoinv1.0.pdf
>
>
> We are proposing an enhanced hash join algorithm called _“hybrid hybrid grace
> hash join”_.
> We can benefit from this feature as illustrated below:
> * The query will not fail even if the estimated memory requirement is
> slightly wrong
> * Expensive garbage collection overhead can be avoided when hash table grows
> * Join execution using a Map join operator even though the small table
> doesn't fit in memory as spilling some data from the build and probe sides
> will still be cheaper than having to shuffle the large fact table
> The design was based on Hadoop’s parallel processing capability and
> significant amount of memory available.
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