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From Ru-Xiang <...@git.apache.org>
Subject [GitHub] spark pull request #16033: SPARK-18607 get a result on a percent of the task...
Date Mon, 28 Nov 2016 11:16:40 GMT
GitHub user Ru-Xiang opened a pull request:

    https://github.com/apache/spark/pull/16033

    SPARK-18607 get a result on a percent of the tasks succeed

    ## What changes were proposed in this pull request?
    
    In this patch, we modify the codes corresponding to runApproximateJob so that we can get
a result when the specified percent of tasks succeed.
    In a production environment, 'long tail' is a common urgent problem. In practice, as long
as we can get a specified percent of tasks' results, we can guarantee the final results. And
this is a common requirement in the practice of machine learning algorithms.
    ## How was this patch tested?
    
    We compile the codes by dev/make-distribution.sh, and deploy it on a cluster. and run
a test codes reduce on the cluster, and we get the desired results.
    


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

    $ git pull https://github.com/Ru-Xiang/spark my_change

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

    https://github.com/apache/spark/pull/16033.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 #16033
    
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