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From chiwanpark <...@git.apache.org>
Subject [GitHub] flink pull request: Flink 1745
Date Sun, 04 Oct 2015 14:16:29 GMT
Github user chiwanpark commented on the pull request:

    https://github.com/apache/flink/pull/1220#issuecomment-145353515
  
    I just reviewed quickly. I have some comments for this pull request.
    
    1. This pull request cannot pass checking Scala code style. The Scala code should not
exceed 100 characters in each line. I also found some wrong indentations such as line 200-211
in `KNN.scala` file. Please reformat your code.
    2. The meaning of `BruteOrQuad` is ambiguous. From my understand, if `BruteOrQuad` is
true, we use quadtree implementation, right? So the other name such as `useQuadTree` would
be better.
    3. Please remove blank line after Scala doc comments.
    4. Your implementation assumes that the type of given `Vector` is `DenseVector`. But basically,
there is no guarantee of the type of `Vector`. We should generalize the implementation.
    5. We should be able to configure the use of quadtree implementation. Please add configure
parameter into `KNN` object.
    6. Currently, `predictDataSet` is too big and complex because of large code in `mapPartition`
operation. How about split the operation into `mapPartition` for raw and quadtree?
    7. Please avoid calculation of `BigDecimal`. Maybe we can check whether we use quadtree
or not without `BigDecimal` like following:
      * `(4 ^ dim) * Ntest * log(Ntrain) < Ntest * Ntrain` is same as `dim + log_4(log(Ntrain))
< log_4(Ntrain)`
    
    This is great start! If you have some question about my comments, please feel free to
reply.
    
    P.S.: How about create training quadtree before cross operation? Is there any intention
to create quadtree after cross operation?


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