Hi Weihua， Thanks for bring up this discuss! I quickly read the google doc，and I fully agree that ML can be well supported on TableAPI (at some stage in the future). In fact, Xiaowei and I have already brought up a discussion on enhancing the Table API. In the first phase, we will add support for map/flatmap/agg/flatagg in TableAPI. So I am very happy to be involved in this discussion and will leave a comment in the good doc later.
I think It's grateful if you can add a phased implementation plan in google doc. What to do you think? Thanks, Jincheng Weihua Jiang <weihua.ji...@gmail.com> 于2018年11月20日周二 下午8:53写道： > ML Pipeline is the idea brought by Scikit-learn > <https://arxiv.org/abs/1309.0238>. Both Spark and Flink has borrowed this > idea and made their own implementations [Spark ML Pipeline > <https://spark.apache.org/docs/latest/ml-pipeline.html>, Flink ML Pipeline > < > https://ci.apache.org/projects/flink/flink-docs-release-1.6/dev/libs/ml/pipelines.html > >]. > > > > NOTE: though I am using the term "ML", ML Pipeline shall apply to both ML > and DL pipelines. > > > ML Pipeline is quite helpful for model composition (i.e. using model(s) for > feature engineering) . And it enables logic reuse in train and inference > phases (via pipeline persistence and load), which is essential for AI > engineering. ML Pipeline can also be a good base for Flink based AI > engineering platform if we can make ML Pipeline have good tooling support > (i.e. meta data human readable). > > > As the Table API will be the unified high level API for both stream and > batch processing, I want to initiate the design discussion of new Table > based Flink ML Pipeline. > > > I drafted a design document [1] for this discussion. This design tries to > create a new ML Pipeline implementation so that concrete ML/DL algorithms > can fit to this new API to achieve interoperability. > > > Any feedback is highly appreciated. > > > Thanks > > Weihua > > > [1] > > https://docs.google.com/document/d/1PLddLEMP_wn4xHwi6069f3vZL7LzkaP0MN9nAB63X90/edit?usp=sharing >
