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Matias Rotenberg commented on SPARK-17086:
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I seem to be running into this exact issue in 2.2.0
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Barry Becker commented on SPARK-17086:
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Thanks.
BTW, I hope there are some test cases where the
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Barry Becker commented on SPARK-17086:
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Is it possible to get this fix into 2.0.1? Maybe it would be
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Apache Spark commented on SPARK-17086:
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User 'VinceShieh' has created a pull request for this issue:
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Yanbo Liang commented on SPARK-17086:
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We should not throw exception in this case. If the number of
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Qian Huang commented on SPARK-17086:
I also agree on that it does not make sense if we put the same
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Sean Owen commented on SPARK-17086:
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Yeah sounds good -- feel free to make a PR.
> QuantileDiscretizer
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Barry Becker commented on SPARK-17086:
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I think I agree with the discussion. Here is a summary of
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Vincent commented on SPARK-17086:
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Agree! [~srowen]
> QuantileDiscretizer throws
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Sean Owen commented on SPARK-17086:
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I suppose it depends on the desired semantics of
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Vincent commented on SPARK-17086:
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[~srowen] in the example you just took, yes, it will return
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Sean Owen commented on SPARK-17086:
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You are right, some buckets will get no values. If the input has
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Yanbo Liang commented on SPARK-17086:
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[~sowen]
The bucket defined by [1.0, 1.0) will only receive
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Sean Owen commented on SPARK-17086:
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Yes, I know it generates an error. I think it should accept
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Vincent commented on SPARK-17086:
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[~yanboliang] yes, actually that case was handled on spark-1.6.2
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Sean Owen commented on SPARK-17086:
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The issue is that approxQuantile may return quantiles where
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Yanbo Liang commented on SPARK-17086:
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If the number of distinct input data is less than
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Vincent commented on SPARK-17086:
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confirmed issue doesnt exist on Spark-1.6.2.
I will work on this
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