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[MLnick]

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Merged to master / branch-2.3


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Thanks @mgaido91 and @jkbradley for working on this and others for review


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+1 merge this to 2.3


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[MLnick]

Github user MLnick commented on the issue:

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Well yes it would - but the method checks inputCols/inputCol first so will
always fail for that reason here, ie we aren’t actually testing the full
code path
On Mon, 22 Jan 2018 at 16:43, Marco Gaido  wrote:

> *@mgaido91* commented on this pull request.
> --
>
> In mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala
> :
>
> > -  test("Both inputCol and inputCols are set") {
> -val bucket = new Bucketizer()
> -  .setInputCol("feature1")
> -  .setOutputCol("result")
> -  .setSplits(Array(-0.5, 0.0, 0.5))
> -  .setInputCols(Array("feature1", "feature2"))
> -
> -// When both are set, we ignore `inputCols` and just map the column 
specified by `inputCol`.
> -assert(bucket.isBucketizeMultipleColumns() == false)
> +  test("assert exception is thrown if both multi-column and 
single-column params are set") {
> +val df = Seq((0.5, 0.3), (0.5, -0.4)).toDF("feature1", "feature2")
> +ParamsSuite.testExclusiveParams(new Bucketizer, df, ("inputCol", 
"feature1"),
> +  ("inputCols", Array("feature1", "feature2")))
> +ParamsSuite.testExclusiveParams(new Bucketizer, df, ("outputCol", 
"result1"),
> +  ("outputCols", Array("result1", "result2")))
> +ParamsSuite.testExclusiveParams(new Bucketizer, df, ("splits", 
Array(-0.5, 0.0, 0.5)),
>
> @MLnick  actually it will fail for both
> reasons. We can add more test cases to check each of these two cases if 
you
> think it is needed.
>
> —
> You are receiving this because you were mentioned.
> Reply to this email directly, view it on GitHub
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> 

> .
>



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Overall looks good with @jkbradley's changes. I just left a comment on the 
param test cases as I think they're not quite complete


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OK, sent: https://github.com/mgaido91/spark/pull/1


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@jkbradley sure no problem, let me know how I can help.


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Since RC1 for 2.3 failed, it'd be great to get this into 2.3.  @mgaido91 do 
you mind if I send my comments along with a PR to update this PR of yours?  I'm 
rushing because of the time pressure to get this into 2.3 (to avoid a behavior 
change between 2.3 and 2.4).  Thanks in advance!


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@jkbradley maybe you can also help reviewing this, thanks.


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@MLnick @viirya  @WeichenXu123 any further comments on this?


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thanks @hhbyyh, I removed the 2 too strict checks.


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[MLnick]

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Yes featurehasher doesn’t need inputCol and inputCols - since it is a new
multi column transformer. We may see this more in future - as I think new
transformers should be able to work on multiple columns if possible
On Thu, 21 Dec 2017 at 20:27, Yuhao Yang  wrote:

> *@hhbyyh* commented on this pull request.
>
> LGTM besides the one comment.
> --
>
> In mllib/src/main/scala/org/apache/spark/ml/param/params.scala
> :
>
> > @@ -249,6 +250,31 @@ object ParamValidators {
>def arrayLengthGt[T](lowerBound: Double): Array[T] => Boolean = { 
(value: Array[T]) =>
>  value.length > lowerBound
>}
> +
> +  /**
> +   * Checks that either inputCols and outputCols are set or inputCol and 
outputCol are set. If
> +   * this is not true, an `IllegalArgumentException` is raised.
> +   * @param model
> +   */
> +  private[spark] def checkMultiColumnParams(model: Params): Unit = {
> +model match {
> +  case m: HasInputCols with HasInputCol if m.isSet(m.inputCols) && 
m.isSet(m.inputCol) =>
> +raiseIncompatibleParamsException("inputCols", "inputCol")
> +  case m: HasOutputCols with HasInputCol if m.isSet(m.outputCols) && 
m.isSet(m.inputCol) =>
> +raiseIncompatibleParamsException("outputCols", "inputCol")
> +  case m: HasInputCols with HasOutputCol if m.isSet(m.inputCols) && 
m.isSet(m.outputCol) =>
>
> Sorry to miss it, but I just found that FeatureHasher has both InputCols
> and OutputCol.
> I think we can remove the case and the one above since they can be too
> strict.
>
> —
> You are receiving this because you were mentioned.
> Reply to this email directly, view it on GitHub
> ,
> or mute the thread
> 

> .
>



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thanks @hhbyyh, I updated the PR according to your suggestion and previous 
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[hhbyyh]

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To make it available for other classes, we need to support checking for 
both `fit` and `transform`, that means we also need a sample input Dataset, so 
we may have to add the explicit test in each of the test suite. But we can 
still create some infrastructure function for the explicit test to invoke.
E.g. we can create some function in object ParamsSuite or other places 
`checkMultiColumnParams(obj: Params, sampleData: Dataset[_])`


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@hhbyyh thanks for the comments. I already fixed all your comments, but I 
am waiting to push for the UT. Honestly I think that `checkParam` is not the 
best place. Checking the exception requires setting the parameters and invoking 
`transform`, thus I am not sure it is the best place, since it is a very 
generic one and at the moment we are setting no parameter there. What do you 
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[GitHub] spark issue #19993: [SPARK-22799][ML] Bucketizer should throw exception if s...

[mgaido91]

Github user mgaido91 commented on the issue:

https://github.com/apache/spark/pull/19993
  
@hhbyyh I created a common infrastructure. Please let me know if I have to 
modify it. Meanwhile, I'd like to discuss where to put the common UTs: do you 
have any specific idea about the right place? Thanks.


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[GitHub] spark issue #19993: [SPARK-22799][ML] Bucketizer should throw exception if s...

[hhbyyh]

Github user hhbyyh commented on the issue:

https://github.com/apache/spark/pull/19993
  
I would suggest to develop the common infrastructure and unit test first, 
then other PR can take it or we can send follow-up fix.

cc @MLnick for advice.


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[GitHub] spark issue #19993: [SPARK-22799][ML] Bucketizer should throw exception if s...

[mgaido91]

Github user mgaido91 commented on the issue:

https://github.com/apache/spark/pull/19993
  
@hhbyyh thanks for the review. I see that for some classes there are 
ongoing PRs. Thus I cannot change them now in order to have a common place and 
a common test. Should I wait for those PRs to be merged then? Or were you 
suggesting something different?
Thanks.


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[mgaido91]

Github user mgaido91 commented on the issue:

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Jenkins, retest this please


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