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Posted to issues@spark.apache.org by "DB Tsai (JIRA)" <ji...@apache.org> on 2016/03/21 09:10:25 UTC
[jira] [Updated] (SPARK-13944) Separate out local linear algebra as
a standalone module without Spark dependency
[ https://issues.apache.org/jira/browse/SPARK-13944?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
DB Tsai updated SPARK-13944:
----------------------------
Description:
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.
was:
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.
> 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: Critical
>
> 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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