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https://issues.apache.org/jira/browse/SPARK-17086?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15426259#comment-15426259
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Sean Owen commented on SPARK-17086:
-----------------------------------

You are right, some buckets will get no values. If the input has so few 
distinct (integer) values, 10 buckets is too many and there's no way 3 distinct 
values can ever fall into more than 3 distinct buckets. That much is actually 
fine IMHO.

But yes it's ambiguous because 2 can logically go into [2,2) or [2,3). If it 
were consistently mapped into one of them, like the first matching bucket, I 
think it would still be valid output. If there's no easy way to make this 
mapping consistently then I agree it should probably be an error to end up with 
splits like this.

(I'm also not sure why 8 splits are output in the example but 10 buckets were 
requested. It just defines 7 buckets.)

> QuantileDiscretizer throws InvalidArgumentException (parameter splits given 
> invalid value) on valid data
> --------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-17086
>                 URL: https://issues.apache.org/jira/browse/SPARK-17086
>             Project: Spark
>          Issue Type: Bug
>          Components: ML
>    Affects Versions: 2.1.0
>            Reporter: Barry Becker
>
> I discovered this bug when working with a build from the master branch (which 
> I believe is 2.1.0). This used to work fine when running spark 1.6.2.
> I have a dataframe with an "intData" column that has values like 
> {code}
> 1 3 2 1 1 2 3 2 2 2 1 3
> {code}
> I have a stage in my pipeline that uses the QuantileDiscretizer to produce 
> equal weight splits like this
> {code}
> new QuantileDiscretizer()
>         .setInputCol("intData")
>         .setOutputCol("intData_bin")
>         .setNumBuckets(10)
>         .fit(df)
> {code}
> But when that gets run it (incorrectly) throws this error:
> {code}
> parameter splits given invalid value [-Infinity, 1.0, 1.0, 2.0, 2.0, 3.0, 
> 3.0, Infinity]
> {code}
> I don't think that there should be duplicate splits generated should there be?



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