Github user VinceShieh commented on a diff in the pull request:
https://github.com/apache/spark/pull/14858#discussion_r78513514
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/QuantileDiscretizer.scala ---
@@ -109,7 +114,7 @@ final class QuantileDiscretizer @Since("1.6.0")
(@Since("1.6.0") override val ui
@Since("2.0.0")
override def fit(dataset: Dataset[_]): Bucketizer = {
transformSchema(dataset.schema, logging = true)
- val splits = dataset.stat.approxQuantile($(inputCol),
+ val splits =
dataset.select($(inputCol)).na.drop().stat.approxQuantile($(inputCol),
--- End diff --
@srowen I have one question here. The reason why we dont move this NaN
filter into approxiQuantile or multipleApproxQuantiles is that, those apis are
shared with sparkSQL? Becoz, personally I think it would look better if we put
this filter inside multipleApproxQuantiles, though it would introduce more
changes and, should make sure it doesnt impact other components other than
mllib.
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