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
