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https://issues.apache.org/jira/browse/HIVE-10673?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14610272#comment-14610272
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Hive QA commented on HIVE-10673:
--------------------------------
{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/12743035/HIVE-10673.7.patch
{color:red}ERROR:{color} -1 due to 1 failed/errored test(s), 9137 tests executed
*Failed tests:*
{noformat}
org.apache.hadoop.hive.cli.TestMiniTezCliDriver.testCliDriver_tez_smb_1
{noformat}
Test results:
http://ec2-174-129-184-35.compute-1.amazonaws.com/jenkins/job/PreCommit-HIVE-TRUNK-Build/4460/testReport
Console output:
http://ec2-174-129-184-35.compute-1.amazonaws.com/jenkins/job/PreCommit-HIVE-TRUNK-Build/4460/console
Test logs:
http://ec2-174-129-184-35.compute-1.amazonaws.com/logs/PreCommit-HIVE-TRUNK-Build-4460/
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: 12743035 - PreCommit-HIVE-TRUNK-Build
> Dynamically partitioned hash join for Tez
> -----------------------------------------
>
> Key: HIVE-10673
> URL: https://issues.apache.org/jira/browse/HIVE-10673
> Project: Hive
> Issue Type: New Feature
> Components: Query Planning, Query Processor
> Reporter: Jason Dere
> Assignee: Jason Dere
> Attachments: HIVE-10673.1.patch, HIVE-10673.2.patch,
> HIVE-10673.3.patch, HIVE-10673.4.patch, HIVE-10673.5.patch,
> HIVE-10673.6.patch, HIVE-10673.7.patch
>
>
> Some analysis of shuffle join queries by [~mmokhtar]/[~gopalv] found about
> 2/3 of the CPU was spent during sorting/merging.
> While this does not work for MR, for other execution engines (such as Tez),
> it is possible to create a reduce-side join that uses unsorted inputs in
> order to eliminate the sorting, which may be faster than a shuffle join. To
> join on unsorted inputs, we can use the hash join algorithm to perform the
> join in the reducer. This will require the small tables in the join to fit in
> the reducer/hash table for this to work.
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