[
https://issues.apache.org/jira/browse/FLINK-1297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14502547#comment-14502547
]
ASF GitHub Bot commented on FLINK-1297:
---------------------------------------
Github user tammymendt commented on the pull request:
https://github.com/apache/flink/pull/605#issuecomment-94401122
Hey, thanks for the quick feedback. I agree with separating the
contribution as a library, however I have a question. The reason I have used a
specialized method in the RuntimeEnvironment, is that for the
OperatorStatsAccumulator, we do not want to only track the accumulated
statistics per job, but also keep an array of the statistics collected at each
task. The subtaskIndex which part of the RuntimeEnvironment is passed as a
parameter to the constructor of the accumulator so that we can track which
subtask is associated to which stats. Any ideas as to how I could use the same
accumulator infrastructure but be able to associate an accumulated value with a
given subtask?
> 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
