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https://issues.apache.org/jira/browse/SPARK-12212?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley resolved SPARK-12212.
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Resolution: Fixed
Fix Version/s: 1.6.1
2.0.0
Issue resolved by pull request 10234
[https://github.com/apache/spark/pull/10234]
> Clarify the distinction between spark.mllib and spark.ml
> --------------------------------------------------------
>
> Key: SPARK-12212
> URL: https://issues.apache.org/jira/browse/SPARK-12212
> Project: Spark
> Issue Type: Sub-task
> Components: Documentation
> Affects Versions: 1.5.2
> Reporter: Timothy Hunter
> Assignee: Timothy Hunter
> Fix For: 2.0.0, 1.6.1
>
>
> There is a confusion in the documentation of MLLib as to what exactly MLlib:
> is it the package, or is it the whole effort of ML on spark, and how it
> differs from spark.ml? Is MLLib going to be deprecated?
> We should do the following:
> - refer to the mllib the code package as spark.mllib across all the
> documentation. Alternative name is "RDD API of MLlib".
> - refer to MLlib the project that encompasses spark.ml + spark.mllib as
> MLlib (it should be the default)
> - replaces reference to "Pipeline API" by spark.ml or the "Dataframe API of
> MLlib". I would deemphasize that this API is for building pipelines. Some
> users are lead to believe from the documentation that spark.ml can only be
> used for building pipelines and that using a single algorithm can only be
> done with spark.mllib.
> Most relevant places:
> - {{mllib-guide.md}}
> - {{mllib-linear-methods.md}}
> - {{mllib-dimensionality-reduction.md}}
> - {{mllib-pmml-model-export.md}}
> - {{mllib-statistics.md}}
> In these files, most references to {{MLlib}} are meant to refer to
> {{spark.mllib}} instead.
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