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https://issues.apache.org/jira/browse/SPARK-13944?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15233142#comment-15233142
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DB Tsai commented on SPARK-13944:
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There will be no converting back and forth in 2.0. Basically, `ml` package will
be using its own `blas` and `vector` types. The reason why we don't want to
break `mllib` is that there are people using it in production, and we don't
want to break their production code. However, the adoption of `ml` is still
young, and this is an experimental package; as a result, it's more reasonable
to change the api there.
Type alias can be an option. [~mengxr] what do you think?
Thanks.
> Separate out local linear algebra as a standalone module without Spark
> dependency
> ---------------------------------------------------------------------------------
>
> Key: SPARK-13944
> URL: https://issues.apache.org/jira/browse/SPARK-13944
> Project: Spark
> Issue Type: New Feature
> Components: Build, ML
> Affects Versions: 2.0.0
> Reporter: Xiangrui Meng
> Assignee: DB Tsai
> Priority: Blocker
>
> Separate out linear algebra as a standalone module without Spark dependency
> to simplify production deployment. We can call the new module
> spark-mllib-local, which might contain local models in the future.
> The major issue is to remove dependencies on user-defined types.
> The package name will be changed from mllib to ml. For example, Vector will
> be changed from `org.apache.spark.mllib.linalg.Vector` to
> `org.apache.spark.ml.linalg.Vector`. The return vector type in the new ML
> pipeline will be the one in ML package; however, the existing mllib code will
> not be touched. As a result, this will potentially break the API. Also, when
> the vector is loaded from mllib vector by Spark SQL, the vector will
> automatically converted into the one in ml package.
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