[GitHub] spark issue #17419: [SPARK-19634][ML] Multivariate summarizer - dataframes A...

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

Github user WeichenXu123 commented on the issue:

    https://github.com/apache/spark/pull/17419
  
    As the dataframe version is much slower than RDD version (currently test against vector of size 1)
    I also guess there is some performance issue in `ObjectAggregationIterator.processInput()`
    in the following code block:
    ```
      private def processInputs(): Unit = {
        // ...
        if (groupingExpressions.isEmpty) {
          // If there is no grouping expressions, we can just reuse the same buffer over and over again.
          val groupingKey = groupingProjection.apply(null)
          val buffer: InternalRow = getAggregationBufferByKey(hashMap, groupingKey)
          while (inputRows.hasNext) {
            val newInput = safeProjection(inputRows.next()) 
            processRow(buffer, newInput)
          }
        }
        ...
    ```
    This statement `val newInput = safeProjection(inputRows.next())` maybe do some redundant data copy (for walk-around some bugs?)
    
    cc @cloud-fan @liancheng 


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