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Posted to issues@flink.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2015/10/06 18:04:26 UTC

[jira] [Commented] (FLINK-2819) Add Windowed Join/CoGroup Operator Based on Tagged Union

    [ https://issues.apache.org/jira/browse/FLINK-2819?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14945257#comment-14945257 ] 

ASF GitHub Bot commented on FLINK-2819:
---------------------------------------

GitHub user aljoscha opened a pull request:

    https://github.com/apache/flink/pull/1232

    [FLINK-2819] Add Windowed Join/CoGroup Operator Based on Tagged Union

    Right now, this does everything in memory, so the JVM will blow if data
    for one key becomes too large.

You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/aljoscha/flink stream-join

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/flink/pull/1232.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 #1232
    
----
commit b7a50549c16dbac790268004341ee1a8b66232d3
Author: Aljoscha Krettek <al...@gmail.com>
Date:   2015-10-06T14:33:04Z

    [FLINK-2819] Add Windowed Join/CoGroup Operator Based on Tagged Union
    
    Right now, this does everything in memory, so the JVM will blow if data
    for one key becomes too large.

----


> Add Windowed Join/CoGroup Operator Based on Tagged Union
> --------------------------------------------------------
>
>                 Key: FLINK-2819
>                 URL: https://issues.apache.org/jira/browse/FLINK-2819
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Streaming
>            Reporter: Aljoscha Krettek
>            Assignee: Aljoscha Krettek
>             Fix For: 0.10
>
>
> This will add a Join/CoGroup operation that reuses the new windowing code. The implementation should be similar to how a join can be implemented on MapReduce using tags for the two input side and then pulling them apart again in the reduce operation.



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