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https://issues.apache.org/jira/browse/FLINK-1718?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14382220#comment-14382220
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ASF GitHub Bot commented on FLINK-1718:
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GitHub user tillrohrmann opened a pull request:
https://github.com/apache/flink/pull/539
[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:
https://github.com/apache/flink/pull/539.patch
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
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commit 4c18940bf14f376cdb339d908324e5f2cd4593ad
Author: Till Rohrmann <[email protected]>
Date: 2015-03-25T14:27:58Z
[FLINK-1718] [ml] Adds sparse matrix and sparse vector types
commit 756b2a64643ec888ff9a45ae1a8565e642971996
Author: Till Rohrmann <[email protected]>
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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