[jira] [Created] (SPARK-17400) MinMaxScaler.transform() outputs DenseVector by default, which causes poor performance

["Frank Dai (JIRA)" <ji...@apache.org>]

Frank Dai created SPARK-17400:
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             Summary: MinMaxScaler.transform() outputs DenseVector by default, which causes poor performance
                 Key: SPARK-17400
                 URL: https://issues.apache.org/jira/browse/SPARK-17400
             Project: Spark
          Issue Type: Improvement
          Components: ML, MLlib
    Affects Versions: 2.0.0, 1.6.2, 1.6.1
            Reporter: Frank Dai


MinMaxScaler.transform() outputs DenseVector by default, which will cause poor performance and consume a lot of memory.

The most important line of code is the following:

https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/feature/MinMaxScaler.scala#L195

I suggest that the code should calculate the number of non-zero elements in advance, if the number of non-zero elements is less than half of the total elements in the matrix, use SparseVector, otherwise use DenseVector



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