Github user viirya commented on a diff in the pull request:

    https://github.com/apache/spark/pull/20594#discussion_r168057330
  
    --- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/Bucketizer.scala 
---
    @@ -290,6 +293,27 @@ object Bucketizer extends 
DefaultParamsReadable[Bucketizer] {
         }
       }
     
    +
    +  private[Bucketizer] class BucketizerWriter(instance: Bucketizer) extends 
MLWriter {
    +
    +    override protected def saveImpl(path: String): Unit = {
    +      // SPARK-23377: The default params will be saved and loaded as 
user-supplied params.
    +      // Once `inputCols` is set, the default value of `outputCol` param 
causes the error
    +      // when checking exclusive params. As a temporary to fix it, we 
remove the default
    +      // value of `outputCol` if `inputCols` is set before saving.
    +      // TODO: If we modify the persistence mechanism later to better 
handle default params,
    +      // we can get rid of this.
    +      var removedOutputCol: Option[String] = None
    +      if (instance.isSet(instance.inputCols)) {
    --- End diff --
    
    Why? I think they are orthogonal and this shouldn't cause the issue in 
Python side. Besides, as the PySpark multi-column support is not added yet 
(it's reverted), I think we don't hit the Python API issue. This is a quick fix 
to deal with the persistence bug. I'm not sure we should be blocked.


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