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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-1297) Add support for tracking statistics of intermediate results
Date Fri, 17 Apr 2015 13:10:58 GMT

    [ https://issues.apache.org/jira/browse/FLINK-1297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14499790#comment-14499790

ASF GitHub Bot commented on FLINK-1297:

Github user StephanEwen commented on a diff in the pull request:

    --- Diff: flink-core/pom.xml ---
    @@ -63,6 +63,19 @@ under the License.
    +        <dependency>
    +            <groupId>com.clearspring.analytics</groupId>
    +            <artifactId>stream</artifactId>
    +            <version>2.7.0</version>
    +            <exclusions>
    +                <exclusion>
    +                    <groupId>it.unimi.dsi</groupId>
    +                    <artifactId>fastutil</artifactId>
    --- End diff --
    We have so far refrained from including fastutil, as it is a huge dependency, and one
usually needs only a minimal subset of the functionality. Can you elaborate what this is needed

> 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
> 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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