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https://issues.apache.org/jira/browse/TEZ-2646?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Bikas Saha updated TEZ-2646:
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Comment: was deleted
(was: {color:green}+1 overall{color}. Here are the results of testing the
latest attachment
http://issues.apache.org/jira/secure/attachment/12748206/TEZ-2646.1.patch
against master revision 4f66cb4.
{color:green}+1 @author{color}. The patch does not contain any @author
tags.
{color:green}+1 tests included{color}. The patch appears to include 7 new
or modified test files.
{color:green}+1 javac{color}. The applied patch does not increase the
total number of javac compiler warnings.
{color:green}+1 javadoc{color}. There were no new javadoc warning messages.
{color:green}+1 findbugs{color}. The patch does not introduce any new
Findbugs (version 3.0.1) warnings.
{color:green}+1 release audit{color}. The applied patch does not increase
the total number of release audit warnings.
{color:green}+1 core tests{color}. The patch passed unit tests in .
Test results: https://builds.apache.org/job/PreCommit-TEZ-Build/946//testReport/
Console output: https://builds.apache.org/job/PreCommit-TEZ-Build/946//console
This message is automatically generated.)
> Add scheduling casual dependency for attempts
> ---------------------------------------------
>
> Key: TEZ-2646
> URL: https://issues.apache.org/jira/browse/TEZ-2646
> Project: Apache Tez
> Issue Type: Sub-task
> Reporter: Bikas Saha
> Assignee: Bikas Saha
> Attachments: TEZ-2646.1.patch
>
>
> When a task gets scheduled then we dont know what caused it. Some
> possibilities are
> 1) initial scheduling by the vertex manager - causality determined by VM.
> E.g. dynamic partition pruning VM in Hive can point causality to the attempt
> that sent it the stats needed to complete the partition pruning logic.
> 2) re-scheduling due to own previous version failure - causality points to
> the previous version that just failed
> 3) re-scheduling because read error reported by consumer - causality points
> to the consumer attempt that reported the error and caused the scheduling.
> This causality relationship can be used to stitch together scheduling
> dependencies in the execution timeline of the DAG.
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