[jira] [Commented] (FLINK-1725) New Partitioner for better load balancing for skewed data

["ASF GitHub Bot (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/FLINK-1725?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16033713#comment-16033713 ] 

ASF GitHub Bot commented on FLINK-1725:
---------------------------------------

Github user coveralls commented on the issue:

    https://github.com/apache/flink/pull/1069
  
    
    [![Coverage Status](https://coveralls.io/builds/11790399/badge)](https://coveralls.io/builds/11790399)
    
    Changes Unknown when pulling **a2429551c2e498383ed61a7e3650224c12ec3933 on anisnasir:master** into ** on apache:master**.



> New Partitioner for better load balancing for skewed data
> ---------------------------------------------------------
>
>                 Key: FLINK-1725
>                 URL: https://issues.apache.org/jira/browse/FLINK-1725
>             Project: Flink
>          Issue Type: Improvement
>          Components: DataStream API
>    Affects Versions: 0.8.1
>            Reporter: Anis Nasir
>            Assignee: Anis Nasir
>              Labels: LoadBalancing, Partitioner
>   Original Estimate: 336h
>  Remaining Estimate: 336h
>
> Hi,
> We have recently studied the problem of load balancing in Storm [1].
> In particular, we focused on key distribution of the stream for skewed data.
> We developed a new stream partitioning scheme (which we call Partial Key Grouping). It achieves better load balancing than key grouping while being more scalable than shuffle grouping in terms of memory.
> In the paper we show a number of mining algorithms that are easy to implement with partial key grouping, and whose performance can benefit from it. We think that it might also be useful for a larger class of algorithms.
> Partial key grouping is very easy to implement: it requires just a few lines of code in Java when implemented as a custom grouping in Storm [2].
> For all these reasons, we believe it will be a nice addition to the standard Partitioners available in Flink. If the community thinks it's a good idea, we will be happy to offer support in the porting.
> References:
> [1]. https://melmeric.files.wordpress.com/2014/11/the-power-of-both-choices-practical-load-balancing-for-distributed-stream-processing-engines.pdf
> [2]. https://github.com/gdfm/partial-key-grouping



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