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https://issues.apache.org/jira/browse/SPARK-23377?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dongjoon Hyun updated SPARK-23377:
----------------------------------
    Fix Version/s:     (was: 2.3.1)
                   2.3.0

> Bucketizer with multiple columns persistence bug
> ------------------------------------------------
>
>                 Key: SPARK-23377
>                 URL: https://issues.apache.org/jira/browse/SPARK-23377
>             Project: Spark
>          Issue Type: Bug
>          Components: ML
>    Affects Versions: 2.3.0
>            Reporter: Bago Amirbekian
>            Assignee: Liang-Chi Hsieh
>            Priority: Blocker
>             Fix For: 2.3.0, 2.4.0
>
>
> A Bucketizer with multiple input/output columns get "inputCol" set to the 
> default value on write -> read which causes it to throw an error on 
> transform. Here's an example.
> {code:java}
> import org.apache.spark.ml.feature._
> val splits = Array(Double.NegativeInfinity, 0, 10, 100, 
> Double.PositiveInfinity)
> val bucketizer = new Bucketizer()
>   .setSplitsArray(Array(splits, splits))
>   .setInputCols(Array("foo1", "foo2"))
>   .setOutputCols(Array("bar1", "bar2"))
> val data = Seq((1.0, 2.0), (10.0, 100.0), (101.0, -1.0)).toDF("foo1", "foo2")
> bucketizer.transform(data)
> val path = "/temp/bucketrizer-persist-test"
> bucketizer.write.overwrite.save(path)
> val bucketizerAfterRead = Bucketizer.read.load(path)
> println(bucketizerAfterRead.isDefined(bucketizerAfterRead.outputCol))
> // This line throws an error because "outputCol" is set
> bucketizerAfterRead.transform(data)
> {code}
> And the trace:
> {code:java}
> java.lang.IllegalArgumentException: Bucketizer bucketizer_6f0acc3341f7 has 
> the inputCols Param set for multi-column transform. The following Params are 
> not applicable and should not be set: outputCol.
>       at 
> org.apache.spark.ml.param.ParamValidators$.checkExclusiveParams$1(params.scala:300)
>       at 
> org.apache.spark.ml.param.ParamValidators$.checkSingleVsMultiColumnParams(params.scala:314)
>       at 
> org.apache.spark.ml.feature.Bucketizer.transformSchema(Bucketizer.scala:189)
>       at 
> org.apache.spark.ml.feature.Bucketizer.transform(Bucketizer.scala:141)
>       at 
> line251821108a8a433da484ee31f166c83725.$read$$iw$$iw$$iw$$iw$$iw$$iw.<init>(command-6079631:17)
> {code}



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