[jira] [Created] (SPARK-5406) LocalLAPACK mode in RowMatrix.computeSVD should have much smaller upper bound

["yuhao yang (JIRA)" <ji...@apache.org>]

yuhao yang created SPARK-5406:
---------------------------------

             Summary: LocalLAPACK mode in RowMatrix.computeSVD should have much smaller upper bound
                 Key: SPARK-5406
                 URL: https://issues.apache.org/jira/browse/SPARK-5406
             Project: Spark
          Issue Type: Bug
          Components: MLlib
    Affects Versions: 1.2.0
         Environment: centos, others should be similar
            Reporter: yuhao yang
            Priority: Minor


In RowMatrix.computeSVD, under LocalLAPACK mode, the code would invoke brzSvd. Yet breeze svd for dense matrix has latent constraint. In it's implementation:

      val workSize = ( 3
        * scala.math.min(m, n)
        * scala.math.min(m, n)
        + scala.math.max(scala.math.max(m, n), 4 * scala.math.min(m, n)
          * scala.math.min(m, n) + 4 * scala.math.min(m, n))
      )
      val work = new Array[Double](workSize)

as a result, column num must satisfy 7 * n * n + 4 * n < Int.MaxValue
thus, n < 17515.

This jira is only the first step. If possbile, I hope spark can handle matrix computation up to 80K * 80K.




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