+1. I'd say this is almost a must-have for machine learning. Thanks,
Jiangjie (Becket) Qin On Thu, Feb 13, 2020 at 10:03 AM Rong Rong <walter...@gmail.com> wrote: > Thanks for driving this initiative @Hequn Cheng <he...@apache.org>. > > Moving towards python based ML is definitely a huge win consider how large > the python-ML community is. a big +1 on my side! > Regarding the doc, I only left a few comments on the specific APIs. overall > the architecture looks very good! > > Looking forward to it! > -- > Rong > > On Sun, Feb 9, 2020 at 10:28 PM Hequn Cheng <he...@apache.org> wrote: > > > Hi everyone, > > > > Thanks a lot for your feedback. I have created the FLIP[1]. > > > > Best, > > Hequn > > > > [1] > > > > > https://cwiki.apache.org/confluence/display/FLINK/FLIP+96%3A+Support+Python+ML+Pipeline+API > > > > On Mon, Feb 10, 2020 at 12:29 PM Dian Fu <dian0511...@gmail.com> wrote: > > > > > 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 > > > > > > > > > > > > > > >
