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[Spark-5406][MLlib] LocalLAPACK mode in RowMatrix.computeSVD should have much smaller upper bound #4200

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[Spark-5406][MLlib] LocalLAPACK mode in RowMatrix.computeSVD should have much smaller upper bound #4200

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e48a6e4
make latent svd computation constraint clear
hhbyyh Jan 27, 2015
23860e4
fix comment style
hhbyyh Jan 27, 2015
f7864d0
update auto logic for rowMatrix svd
hhbyyh Jan 29, 2015
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8 changes: 7 additions & 1 deletion mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -220,8 +220,12 @@ class RowMatrix(

val computeMode = mode match {
case "auto" =>
if(k > 5000) {
logWarning(s"computing svd with k=$k and n=$n, please check necessity")
}

// TODO: The conditions below are not fully tested.
if (n < 100 || k > n / 2) {
if (n < 100 || (k > n / 2 && n <= 15000)) {
// If n is small or k is large compared with n, we better compute the Gramian matrix first
// and then compute its eigenvalues locally, instead of making multiple passes.
if (k < n / 3) {
Expand All @@ -246,6 +250,8 @@ class RowMatrix(
val G = computeGramianMatrix().toBreeze.asInstanceOf[BDM[Double]]
EigenValueDecomposition.symmetricEigs(v => G * v, n, k, tol, maxIter)
case SVDMode.LocalLAPACK =>
// breeze (v0.10) svd latent constraint, 7 * n * n + 4 * n < Int.MaxValue
require(n < 17515, s"$n exceeds the breeze svd capability")
val G = computeGramianMatrix().toBreeze.asInstanceOf[BDM[Double]]
val brzSvd.SVD(uFull: BDM[Double], sigmaSquaresFull: BDV[Double], _) = brzSvd(G)
(sigmaSquaresFull, uFull)
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