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https://issues.apache.org/jira/browse/FLINK-1873?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15274177#comment-15274177
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Simone Robutti commented on FLINK-1873:
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I began working right away on this issue.
For now I'm focusing on an indexed row matrix format but I will probably
implement a partitioned format with the same operations to perform some
operations in a more straightforward way. I will write conversions from one
format to the other.
For now I'm just initializing the distributed data structure and writing
conversions to local formats (COO, Sparse, Dense). I'm doing everything with
the standards of the local linear algebra package (indices as Int, values as
Doubles, same names for methods and so on). Also I'm working with Flink's
implementations of all these classes. Is it ok or should I go directly to
Breeze's implementations?
Then I will start thinking about common operations (multiplication, dot
product, svd (?), ATA and so on).
> Distributed matrix implementation
> ---------------------------------
>
> Key: FLINK-1873
> URL: https://issues.apache.org/jira/browse/FLINK-1873
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: liaoyuxi
> Assignee: Simone Robutti
> Labels: ML
>
> It would help to implement machine learning algorithm more quickly and
> concise if Flink would provide support for storing data and computation in
> distributed matrix. The design of the implementation is attached.
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