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https://issues.apache.org/jira/browse/SPARK-6442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14629320#comment-14629320
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Sean Owen commented on SPARK-6442:
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[~mengxr] for Commons Math, and point #2: actually they decided to un-deprecate
the sparse implementations in 3.3 onwards, and keep supporting them:
http://commons.apache.org/proper/commons-math/changes-report.html I think it's
a good option.
But I also am not sure why *Spark* has to decide this for users. Spark can do
whatever it likes internally; apps can do whatever they like externally; both
can and should use a library. From an API perspective, all that's needed is a
representation of the data that thunks easily into other libraries, rather than
provide a library of functions again.
> MLlib Local Linear Algebra Package
> ----------------------------------
>
> Key: SPARK-6442
> URL: https://issues.apache.org/jira/browse/SPARK-6442
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Burak Yavuz
> Priority: Critical
>
> MLlib's local linear algebra package doesn't have any support for any type of
> matrix operations. With 1.5, we wish to add support to a complete package of
> optimized linear algebra operations for Scala/Java users.
> The main goal is to support lazy operations so that element-wise can be
> implemented in a single for-loop, and complex operations can be interfaced
> through BLAS.
> The design doc: http://goo.gl/sf5LCE
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