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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-1718) Add sparse vector and sparse matrix types to machine learning library
Date Thu, 26 Mar 2015 16:59:53 GMT

    [ https://issues.apache.org/jira/browse/FLINK-1718?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14382220#comment-14382220

ASF GitHub Bot commented on FLINK-1718:

GitHub user tillrohrmann opened a pull request:


    [FLINK-1718] Adds sparse matrix and sparse vector

    Adds a sparse matrix abstraction using CSC data representation. Adds a sparse vector abstraction
using CSC data representation.
    Adds convenience functions to cast a Flink matrix/vector into a Breeze matrix/vector and
vice versa.

You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/tillrohrmann/flink sparseMatrix

Alternatively you can review and apply these changes as the patch at:


To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #539
commit 4c18940bf14f376cdb339d908324e5f2cd4593ad
Author: Till Rohrmann <trohrmann@apache.org>
Date:   2015-03-25T14:27:58Z

    [FLINK-1718] [ml] Adds sparse matrix and sparse vector types

commit 756b2a64643ec888ff9a45ae1a8565e642971996
Author: Till Rohrmann <trohrmann@apache.org>
Date:   2015-03-26T16:44:17Z

    [ml] Adds convenience functions for Breeze matrix/vector conversion
    [ml] Adds breeze to flink-dist LICENSE file


> Add sparse vector and sparse matrix types to machine learning library
> ---------------------------------------------------------------------
>                 Key: FLINK-1718
>                 URL: https://issues.apache.org/jira/browse/FLINK-1718
>             Project: Flink
>          Issue Type: New Feature
>          Components: Machine Learning Library
>            Reporter: Till Rohrmann
>            Assignee: Till Rohrmann
>              Labels: ML
> Currently, the machine learning library only supports dense matrix and dense vectors.
For future algorithms it would be beneficial to also support sparse vectors and matrices.
> I'd propose to use the compressed sparse column (CSC) representation, because it allows
rather efficient operations compared to a map backed sparse matrix/vector implementation.
Furthermore, this is also the format the Breeze library expects for sparse matrices/vectors.
Thus, it is easy to convert to a sparse breeze data structure which provides us with many
linear algebra operations.
> BIDMat [1] uses the same data representation.
> Resources:
> [1] [https://github.com/BIDData/BIDMat]

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