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https://issues.apache.org/jira/browse/FLINK-1297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14653421#comment-14653421
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ASF GitHub Bot commented on FLINK-1297:
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Github user aalexandrov commented on the pull request:
https://github.com/apache/flink/pull/605#issuecomment-127558961
@StephanEwen To be honest I'm kind of puzzled and somewhat annoyed that a
PR that
1) adds a feature that has been on the list for at least 2 years,
2) has been tested and evaluated thoroughly, and
3) has been lying around since April and was rebased at least three times
is still open.
I was also not aware that there is a strict maintainer policy for
`flink-contrib` commits. IMHO this is a good place to expose non-critical /
exploratory / unstable features that might be of benefit for multiple users to
the project. If these turn out the be useful for enough people, I'm sure there
will be incentive to maintain them. Otherwise there is always the option to
deprecate and cleanup recent additions to the contrib prior to the next release
if nobody picked up on them.
> Add support for tracking statistics of intermediate results
> -----------------------------------------------------------
>
> Key: FLINK-1297
> URL: https://issues.apache.org/jira/browse/FLINK-1297
> Project: Flink
> Issue Type: Improvement
> Components: Distributed Runtime
> Reporter: Alexander Alexandrov
> Assignee: Alexander Alexandrov
> Fix For: 0.9
>
> Original Estimate: 1,008h
> Remaining Estimate: 1,008h
>
> One of the major problems related to the optimizer at the moment is the lack
> of proper statistics.
> With the introduction of staged execution, it is possible to instrument the
> runtime code with a statistics facility that collects the required
> information for optimizing the next execution stage.
> I would therefore like to contribute code that can be used to gather basic
> statistics for the (intermediate) result of dataflows (e.g. min, max, count,
> count distinct) and make them available to the job manager.
> Before I start, I would like to hear some feedback form the other users.
> In particular, to handle skew (e.g. on grouping) it might be good to have
> some sort of detailed sketch about the key distribution of an intermediate
> result. I am not sure whether a simple histogram is the most effective way to
> go. Maybe somebody would propose another lightweight sketch that provides
> better accuracy.
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