Github user imatiach-msft commented on a diff in the pull request:

    https://github.com/apache/spark/pull/16722#discussion_r101339952
  
    --- Diff: 
mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala 
---
    @@ -99,16 +105,31 @@ class DecisionTreeRegressor @Since("1.4.0") 
(@Since("1.4.0") override val uid: S
       @Since("2.0.0")
       def setVarianceCol(value: String): this.type = set(varianceCol, value)
     
    +  /**
    +   * Sets the value of param [[weightCol]].
    +   * If this is not set or empty, we treat all instance weights as 1.0.
    +   * Default is not set, so all instances have weight one.
    +   *
    +   * @group setParam
    +   */
    +  @Since("2.2.0")
    +  def setWeightCol(value: String): this.type = set(weightCol, value)
    +
       override protected def train(dataset: Dataset[_]): 
DecisionTreeRegressionModel = {
         val categoricalFeatures: Map[Int, Int] =
           MetadataUtils.getCategoricalFeatures(dataset.schema($(featuresCol)))
    -    val oldDataset: RDD[LabeledPoint] = extractLabeledPoints(dataset)
    +    val w = if (!isDefined(weightCol) || $(weightCol).isEmpty) lit(1.0) 
else col($(weightCol))
    +    val instances =
    +      dataset.select(col($(labelCol)).cast(DoubleType), w, 
col($(featuresCol))).rdd.map {
    +        case Row(label: Double, weight: Double, features: Vector) =>
    +          Instance(label, weight, features)
    +      }
    --- End diff --
    
    it sounds like you are going to create a separate JIRA for refactoring this 
code, that is reasonable to me.


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