[jira] [Reopened] (MAHOUT-1837) Sparse/Dense Matrix analysis for Matrix Multiplication

["Andrew Palumbo (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MAHOUT-1837?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Andrew Palumbo reopened MAHOUT-1837:
------------------------------------

Reopening- may need to use {{SparseMatrix}} as default in {{Drm.blockify()}}, Users are seeing OOM errors in when using {{DenseMatrix}} as default block:

{code:title=Drm.blockify()}
{...}
 val block = new DenseMatrix(vectors.length, blockncol)
        var row = 0
        while (row < vectors.length) {
          block(row, ::) := vectors(row)
          row += 1
        }

        // Test the density of the data. If the matrix does not meet the
        // requirements for density, convert the Vectors to a sparse Matrix.
        val resBlock = if (densityAnalysis(block)) {
          block
        } else {
          new SparseRowMatrix(vectors.length, blockncol, vectors, true, false)
        }
{code}

I proposing using {{SparseMatrix}} as default and then testing sparsity and copying into a {{DenseMatrix}} if necessary. 

> 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
>            Assignee: Andrew Palumbo
>             Fix For: 0.13.0
>
>         Attachments: compareDensityTest.ods
>
>
> 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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