Andrew Palumbo created MAHOUT-1837:
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Summary: Sparse/Dense Matrix analysis for Matrix Multiplication
Key: MAHOUT-1837
URL: https://issues.apache.org/jira/browse/MAHOUT-1837
Project: Mahout
Issue Type: Improvement
Components: Math
Affects Versions: 0.12.0
Reporter: Andrew Palumbo
Fix For: 0.12.1
In matrix multiplication, Sparse Matrices can easily turn dense and bloat
memory, one fully dense column and one fully dense row can cause a sparse %*%
sparse operation have a dense result.
There are two issues here one with a quick Fix and one a bit more involved:
# in {{ABt.Scala}} use check the `MatrixFlavor` of the combiner and use the
flavor of the Block as the resulting Sparse or Dense matrix type:
{code}
val comb = if (block.getFlavor == MatrixFlavor.SPARSELIKE) {
new SparseMatrix(prodNCol, block.nrow).t
} else {
new DenseMatrix(prodNCol, block.nrow).t
}
{code}
a simlar check needs to be made in the {{blockify}} transformation.
# More importantly, and more involved is to do an actual analysis of the
resulting matrix data in the in-core {{mmul}} class and use a matrix of the
appropriate Structure as a result.
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