You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@spark.apache.org by ma...@apache.org on 2014/01/22 23:02:33 UTC
[50/50] git commit: Merge pull request #315 from rezazadeh/sparsesvd
Merge pull request #315 from rezazadeh/sparsesvd
Sparse SVD
# Singular Value Decomposition
Given an *m x n* matrix *A*, compute matrices *U, S, V* such that
*A = U * S * V^T*
There is no restriction on m, but we require n^2 doubles to fit in memory.
Further, n should be less than m.
The decomposition is computed by first computing *A^TA = V S^2 V^T*,
computing svd locally on that (since n x n is small),
from which we recover S and V.
Then we compute U via easy matrix multiplication
as *U = A * V * S^-1*
Only singular vectors associated with the largest k singular values
If there are k such values, then the dimensions of the return will be:
* *S* is *k x k* and diagonal, holding the singular values on diagonal.
* *U* is *m x k* and satisfies U^T*U = eye(k).
* *V* is *n x k* and satisfies V^TV = eye(k).
All input and output is expected in sparse matrix format, 0-indexed
as tuples of the form ((i,j),value) all in RDDs.
# Testing
Tests included. They test:
- Decomposition promise (A = USV^T)
- For small matrices, output is compared to that of jblas
- Rank 1 matrix test included
- Full Rank matrix test included
- Middle-rank matrix forced via k included
# Example Usage
import org.apache.spark.SparkContext
import org.apache.spark.mllib.linalg.SVD
import org.apache.spark.mllib.linalg.SparseMatrix
import org.apache.spark.mllib.linalg.MatrixyEntry
// Load and parse the data file
val data = sc.textFile("mllib/data/als/test.data").map { line =>
val parts = line.split(',')
MatrixEntry(parts(0).toInt, parts(1).toInt, parts(2).toDouble)
}
val m = 4
val n = 4
// recover top 1 singular vector
val decomposed = SVD.sparseSVD(SparseMatrix(data, m, n), 1)
println("singular values = " + decomposed.S.data.toArray.mkString)
# Documentation
Added to docs/mllib-guide.md
Project: http://git-wip-us.apache.org/repos/asf/incubator-spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-spark/commit/d009b17d
Tree: http://git-wip-us.apache.org/repos/asf/incubator-spark/tree/d009b17d
Diff: http://git-wip-us.apache.org/repos/asf/incubator-spark/diff/d009b17d
Branch: refs/heads/master
Commit: d009b17d137edf2f1b9da04254e55fb7455faa3d
Parents: 749f842 85b95d0
Author: Matei Zaharia <ma...@databricks.com>
Authored: Wed Jan 22 14:01:30 2014 -0800
Committer: Matei Zaharia <ma...@databricks.com>
Committed: Wed Jan 22 14:01:30 2014 -0800
----------------------------------------------------------------------
docs/mllib-guide.md | 51 +++++
.../apache/spark/examples/mllib/SparkSVD.scala | 59 ++++++
.../apache/spark/mllib/linalg/MatrixEntry.scala | 27 +++
.../apache/spark/mllib/linalg/MatrixSVD.scala | 29 +++
.../org/apache/spark/mllib/linalg/SVD.scala | 189 +++++++++++++++++++
.../spark/mllib/linalg/SparseMatrix.scala | 30 +++
.../apache/spark/mllib/linalg/SVDSuite.scala | 158 ++++++++++++++++
7 files changed, 543 insertions(+)
----------------------------------------------------------------------