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SPARK-1782: svd for sparse matrix using ARPACK #964

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@vrilleup vrilleup commented Jun 4, 2014

copy ARPACK dsaupd/dseupd code from latest breeze
change RowMatrix to use sparse SVD
change tests for sparse SVD

All tests passed. I will run it against some large matrices.

copy ARPACK dsaupd/dseupd code from latest breeze
change RowMatrix to use sparse SVD
change tests for sparse SVD
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Can one of the admins verify this patch?

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mateiz commented Jun 4, 2014

Jenkins, this is ok to test

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mengxr commented Jun 4, 2014

@vrilleup It didn't pass the tests. Please check the Jenkins page.

*/
private[mllib] def multiplyGramianMatrix(v: Vector): Vector = {
val bv = rows.map{
row => row.toBreeze * row.toBreeze.dot(v.toBreeze)
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This would create many temp objects. Please use RDD#aggregate and axpy. The initial vector should be a dense vector.

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You can use the code in computeGramianMatrix as an example.

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changed to use aggregrate and axpy (from breeze). There are still some boxing/unboxing overhead from/to breeze objects. I can further improve if needed.

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*
* The decomposition is computed by providing a function that multiples a vector with A'A to
* ARPACK, and iteratively invoking ARPACK-dsaupd on master node, from which we recover S and V.
* Then we compute U via easy matrix multiplication as U = A * (V * S-1).
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"S-1" -> "S^-1" or "S^{-1}"

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fixed. Somehow my intellij treated ^ as a tag and matched it with a ^ in another line. They both got deleted when I was editing the other line...

@@ -494,4 +519,4 @@ object RowMatrix {

Matrices.dense(n, n, G.data)
}
}
}
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add a newline at the end.

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* @return a dense vector of eigenvalues in descending order and a dense matrix of eigenvectors
* (columns of the matrix). The number of computed eigenvalues might be smaller than k.
*/
private[mllib] def symmetricEigs(mul: Vector => Vector, n: Int, k: Int, tol: Double)
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Is it implemented in breeze-0.8? If so, please add a TODO here so we will switch to the breeze implementation if we upgrade breeze.

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current implementation in breeze-0.8 is for svd, it computes both U and V in memory. I can refactor that part to move the code block calling ARPACK to eig so only V is computed. TODO added

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vrilleup commented Jul 9, 2014

@mengxr I tested axpy, there is no visible change in running time. Should be good to merge :)

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mengxr commented Jul 9, 2014

Jenkins, retest this please.

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mengxr commented Jul 9, 2014

@vrilleup Great! I'll merge it if Jenkins is happy. Thank you for the contribution!

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mengxr commented Jul 9, 2014

Jenkins, retest this please.

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All automated tests passed.
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Thanks @vrilleup !

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mengxr commented Jul 9, 2014

Merged. Thanks!

@asfgit asfgit closed this in 1f33e1f Jul 9, 2014
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vrilleup commented Jul 9, 2014

@mengxr @rezazadeh Thank you! Excited to see this merged :)

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All automated tests passed.
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vrilleup commented Jul 9, 2014

@mengxr I ran one of the large size jobs again, per multiplication time increased to 8 seconds from 2 seconds (the version before yesterday). I don't know which part was the cause (shouldn't be the axpy part because I already compared this). Will submit a patch after identifying the cause.

gzm55 pushed a commit to MediaV/spark that referenced this pull request Jul 18, 2014
copy ARPACK dsaupd/dseupd code from latest breeze
change RowMatrix to use sparse SVD
change tests for sparse SVD

All tests passed. I will run it against some large matrices.

Author: Li Pu <[email protected]>
Author: Xiangrui Meng <[email protected]>
Author: Li Pu <[email protected]>

Closes apache#964 from vrilleup/master and squashes the following commits:

7312ec1 [Li Pu] very minor comment fix
4c618e9 [Li Pu] Merge pull request #1 from mengxr/vrilleup-master
a461082 [Xiangrui Meng] make superscript show up correctly in doc
861ec48 [Xiangrui Meng] simplify axpy
62969fa [Xiangrui Meng] use BDV directly in symmetricEigs change the computation mode to local-svd, local-eigs, and dist-eigs update tests and docs
c273771 [Li Pu] automatically determine SVD compute mode and parameters
7148426 [Li Pu] improve RowMatrix multiply
5543cce [Li Pu] improve svd api
819824b [Li Pu] add flag for dense svd or sparse svd
eb15100 [Li Pu] fix binary compatibility
4c7aec3 [Li Pu] improve comments
e7850ed [Li Pu] use aggregate and axpy
827411b [Li Pu] fix EOF new line
9c80515 [Li Pu] use non-sparse implementation when k = n
fe983b0 [Li Pu] improve scala style
96d2ecb [Li Pu] improve eigenvalue sorting
e1db950 [Li Pu] SPARK-1782: svd for sparse matrix using ARPACK
xiliu82 pushed a commit to xiliu82/spark that referenced this pull request Sep 4, 2014
copy ARPACK dsaupd/dseupd code from latest breeze
change RowMatrix to use sparse SVD
change tests for sparse SVD

All tests passed. I will run it against some large matrices.

Author: Li Pu <[email protected]>
Author: Xiangrui Meng <[email protected]>
Author: Li Pu <[email protected]>

Closes apache#964 from vrilleup/master and squashes the following commits:

7312ec1 [Li Pu] very minor comment fix
4c618e9 [Li Pu] Merge pull request apache#1 from mengxr/vrilleup-master
a461082 [Xiangrui Meng] make superscript show up correctly in doc
861ec48 [Xiangrui Meng] simplify axpy
62969fa [Xiangrui Meng] use BDV directly in symmetricEigs change the computation mode to local-svd, local-eigs, and dist-eigs update tests and docs
c273771 [Li Pu] automatically determine SVD compute mode and parameters
7148426 [Li Pu] improve RowMatrix multiply
5543cce [Li Pu] improve svd api
819824b [Li Pu] add flag for dense svd or sparse svd
eb15100 [Li Pu] fix binary compatibility
4c7aec3 [Li Pu] improve comments
e7850ed [Li Pu] use aggregate and axpy
827411b [Li Pu] fix EOF new line
9c80515 [Li Pu] use non-sparse implementation when k = n
fe983b0 [Li Pu] improve scala style
96d2ecb [Li Pu] improve eigenvalue sorting
e1db950 [Li Pu] SPARK-1782: svd for sparse matrix using ARPACK
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