yuhao yang created SPARK-5406:
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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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