GitHub user brkyvz opened a pull request:
https://github.com/apache/spark/pull/3200
[SPARK-3974][MLlib] Distributed Block Matrix Abstractions
This pull request includes the abstractions for the distributed BlockMatrix
representation.
`BlockMatrix` will allow users to store very large matrices in small blocks
of local matrices. Specific partitioners, such as `RowBasedPartitioner` and
`ColumnBasedPartitioner`, are implemented in order to optimize addition and
multiplication operations that will be added in a following PR.
This work is based on the ml-matrix repo developed at the AMPLab at UC
Berkeley, CA.
https://github.com/amplab/ml-matrix
Additional thanks to @rezazadeh, @shivaram, and @mengxr for guidance on the
design.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/brkyvz/spark SPARK-3974
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/3200.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 #3200
----
commit b693209c7f51ba15b8d68a35755edf0a9a2cb522
Author: Burak Yavuz <[email protected]>
Date: 2014-11-11T03:58:52Z
Ready for Pull request
commit f378e163b04dad88f6e4fe309e45a5a632aa4101
Author: Burak Yavuz <[email protected]>
Date: 2014-11-11T05:26:34Z
[SPARK-3974] Block Matrix Abstractions ready
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