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:
In these files, most references to MLlib are meant to refer to spark.mllib instead.