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https://issues.apache.org/jira/browse/BEAM-2728?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16114356#comment-16114356
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ASF GitHub Bot commented on BEAM-2728:
--------------------------------------

GitHub user ArnaudFnr opened a pull request:

    https://github.com/apache/beam/pull/3686

    [BEAM-2728] Extension for sketch-based statistics

    Follow this checklist to help us incorporate your contribution quickly and 
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    ---
    
    Extension to compute approximate statistics with the use of probabilistic 
data structure, or sketches.
    
    For now, 4 sketches are supported :
    - HyperLogLog (ApproximateDistinct) for stream's cardinality
    - Count-min Sketch (SketchFrequencies) for computing frequency by element
    - Stream Summary (KMostFrequent) for computing a top k of most frequent 
elements
    - T-Digest (TDigestQuantiles) for computing quantiles in the stream
    
    The sketches are implemented as Beam Combiners, allowing a user to build 
the sketch dynamically in the Pipeline and then make some dynamic queries 
and/or store it in a database.
     

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

    $ git pull https://github.com/ArnaudFnr/beam sketching

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

    https://github.com/apache/beam/pull/3686.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 #3686
    
----
commit 6bf51fdf6afe6f389415792f335dd08adf9fa85a
Author: Arnaud Fournier <[email protected]>
Date:   2017-07-20T14:57:38Z

    [BEAM-2728] Extension for sketch-based statistics

----


> Extension for sketch-based statistics
> -------------------------------------
>
>                 Key: BEAM-2728
>                 URL: https://issues.apache.org/jira/browse/BEAM-2728
>             Project: Beam
>          Issue Type: New Feature
>          Components: sdk-java-extensions
>            Reporter: Arnaud Fournier
>            Assignee: Arnaud Fournier
>            Priority: Minor
>
> Goal : Provide an extension library to compute approximate statistics on 
> streams.
> Interest : Probabilistic data structures can create an approximation (sketch) 
> of the current state of a stream without storing every element but rather 
> processing each observation quickly to summarize its current state and find 
> useful statistical insights.
> Implementation is here : 
> https://github.com/ArnaudFnr/beam/tree/sketching/sdks/java/extensions/sketching
> More info : 
> https://docs.google.com/document/d/1Xy6g5RPBYX_HadpIr_2WrUeusiwL0Jo2ACI5PEOP1kc/edit



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