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From danielblazevski <...@git.apache.org>
Subject [GitHub] flink pull request: Flink 1745
Date Sun, 04 Oct 2015 16:31:58 GMT
Github user danielblazevski commented on the pull request:

    Thanks @chiwanpark for the very useful comments.  I have made changes to the comments,
which can be found here:
    I also changed the testing of KNN + QuadTree, which can be found here:
    Since useQuadTree is now a parameter, I did not need KNNQuadTreeSuite anymore and I removed
    I did not address comment 6 yet.  I need to have the training set before I can define
a non-user specified useQuadTree, so any main if(useQuadTree) should come within ` val crossed
= trainingSet.cross(inputSplit).mapPartition {`
    About your last "P.S" comment,  Creating the quadtree after the cross operation is likely
more efficient -- each CPU/Node will form their own quadtree, which is what is suggested for
the R-tree here:
    This will result less communication overhead than creating a more global quadtree, if
that is what you were referring to.

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