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Posted to dev@apex.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2016/02/19 01:50:18 UTC
[jira] [Commented] (APEXCORE-201) Reported latency is wrong when a
downstream operator is behind more than 1000 windows
[ https://issues.apache.org/jira/browse/APEXCORE-201?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15153454#comment-15153454 ]
ASF GitHub Bot commented on APEXCORE-201:
-----------------------------------------
GitHub user davidyan74 opened a pull request:
https://github.com/apache/incubator-apex-core/pull/230
APEXCORE-201
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/davidyan74/incubator-apex-core APEXCORE-201-PR
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/incubator-apex-core/pull/230.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #230
----
commit d67d7711fa16b76d068e4f1e9c2d46d8668fc7a4
Author: David Yan <da...@datatorrent.com>
Date: 2015-12-30T01:35:04Z
APEXCORE-201 changed the way latency is calculated and fixed the problem when latency is stalled when an operator falls behind too many windows
commit dcb47f22b7f9e3a0462487f55322eb42b550ff2d
Author: David Yan <da...@datatorrent.com>
Date: 2016-02-19T00:43:17Z
APEXCORE-201 optimization of finding critical path
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> Reported latency is wrong when a downstream operator is behind more than 1000 windows
> -------------------------------------------------------------------------------------
>
> Key: APEXCORE-201
> URL: https://issues.apache.org/jira/browse/APEXCORE-201
> Project: Apache Apex Core
> Issue Type: Bug
> Reporter: David Yan
> Assignee: David Yan
>
> We should probably estimate this by reporting the latency using the number of windows behind when that happens. Right now it reports a stale latency.
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