[GitHub] spark pull request #18798: [WIP] [SPARK-19634][ML] Multivariate summarizer -...

[WeichenXu123 <gi...@git.apache.org>]

Github user WeichenXu123 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/18798#discussion_r131735748
  
    --- Diff: mllib/src/main/scala/org/apache/spark/ml/stat/Summarizer.scala ---
    @@ -547,35 +533,11 @@ object SummaryBuilderImpl extends Logging {
           // val features = udt.deserialize(featuresExpr.eval(row))
           val featuresDatum = featuresExpr.eval(row).asInstanceOf[InternalRow]
     
    -      val isDense = featuresDatum.getByte(0) == 1
    -
    -      val indices: ArrayData = if (isDense) null else featuresDatum.getArray(2)
    -      val values: ArrayData = featuresDatum.getArray(3)
    -      val _size = if (isDense) values.numElements() else featuresDatum.getInt(1)
    -
    -      val features = new TraversableIndexedSeq {
    -
    -        override def foreachActive(f: (Int, Double) => Unit): Unit = {
    -          var i = 0
    -          if (isDense) {
    -            while (i < _size) {
    -              f(i, values.getDouble(i))
    -              i += 1
    -            }
    -          } else {
    -            while (i < indices.numElements()) {
    -              f(indices.getInt(i), values.getDouble(i))
    -              i += 1
    -            }
    -          }
    -        }
    -
    -        override def size: Int = _size
    -      }
    +      val features = udt.deserialize(featuresDatum)
    --- End diff --
    
    Change to use `VectorUDT.deserialize` (Because last version code here won't improve performance markedly but increase code complexity.


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