Hi Hequn, Thanks for bringing up the discussion. +1 to this feature. The design LGTM. It's great that the Python ML users could use both the Java Pipeline Transformer/Estimator/Model classes and the Python Pipeline Transformer/Estimator/Model in the same job.
Regards, Dian On Mon, Feb 10, 2020 at 11:08 AM jincheng sun <sunjincheng...@gmail.com> wrote: > Hi Hequn, > > Thanks for bring up this discussion. > > +1 for add Python ML Pipeline API, even though the Java pipeline API may > change. > > I would like to suggest create a FLIP for this API changes. :) > > Best, > Jincheng > > > Hequn Cheng <he...@apache.org> 于2020年2月5日周三 下午5:24写道： > > > Hi everyone, > > > > FLIP-39[1] rebuilds the Flink ML pipeline on top of TableAPI and > introduces > > a new set of Java APIs. As Python is widely used in ML areas, providing > > Python ML Pipeline APIs for Flink can not only make it easier to write ML > > jobs for Python users but also broaden the adoption of Flink ML. > > > > Given this, Jincheng and I discussed offline about the support of Python > ML > > Pipeline API and drafted a design doc[2]. We'd like to achieve three > goals > > for supporting Python Pipeline API: > > - Add Python pipeline API according to Java pipeline API(we will adapt > the > > Python pipeline API if Java pipeline API changes). > > - Support native Python Transformer/Estimator/Model, i.e., users can > write > > not only Python Transformer/Estimator/Model wrappers for calling Java > ones > > but also can write native Python Transformer/Estimator/Models. > > - Ease of use. Support keyword arguments when defining parameters. > > > > More details can be found in the design doc and we are looking forward to > > your feedback. > > > > Best, > > Hequn > > > > [1] > > > > > https://cwiki.apache.org/confluence/display/FLINK/FLIP-39+Flink+ML+pipeline+and+ML+libs > > [2] > > > > > https://docs.google.com/document/d/1fwSO5sRNWMoYuvNgfQJUV6N2n2q5UEVA4sezCljKcVQ/edit?usp=sharing > > >
