Thanks for bring up this DISCUSS Shuiqiang! +1 for the proposal!
Best, Jincheng Xingbo Huang <hxbks...@gmail.com> 于2020年7月9日周四 上午10:41写道： > Hi Shuiqiang, > > Thanks a lot for driving this discussion. > Big +1 for supporting Python DataStream. > In many ML scenarios, operating Object will be more natural than operating > Table. > > Best, > Xingbo > > Wei Zhong <weizhong0...@gmail.com> 于2020年7月9日周四 上午10:35写道： > > > Hi Shuiqiang, > > > > Thanks for driving this. Big +1 for supporting DataStream API in PyFlink! > > > > Best, > > Wei > > > > > > > 在 2020年7月9日，10:29，Hequn Cheng <he...@apache.org> 写道： > > > > > > +1 for adding the Python DataStream API and starting with the stateless > > > part. > > > There are already some users that expressed their wish to have the > Python > > > DataStream APIs. Once we have the APIs in PyFlink, we can cover more > use > > > cases for our users. > > > > > > Best, Hequn > > > > > > On Wed, Jul 8, 2020 at 11:45 AM Shuiqiang Chen <acqua....@gmail.com> > > wrote: > > > > > >> Sorry, the 3rd link is broken, please refer to this one: Support > Python > > >> DataStream API > > >> < > > >> > > > https://docs.google.com/document/d/1H3hz8wuk22-8cDBhQmQKNw3m1q5gDAMkwTDEwnj3FBI/edit > > >>> > > >> > > >> Shuiqiang Chen <acqua....@gmail.com> 于2020年7月8日周三 上午11:13写道： > > >> > > >>> Hi everyone, > > >>> > > >>> As we all know, Flink provides three layered APIs: the > > ProcessFunctions, > > >>> the DataStream API and the SQL & Table API. Each API offers a > different > > >>> trade-off between conciseness and expressiveness and targets > different > > >> use > > >>> cases[1]. > > >>> > > >>> Currently, the SQL & Table API has already been supported in PyFlink. > > The > > >>> API provides relational operations as well as user-defined functions > to > > >>> provide convenience for users who are familiar with python and > > relational > > >>> programming. > > >>> > > >>> Meanwhile, the DataStream API and ProcessFunctions provide more > generic > > >>> APIs to implement stream processing applications. The > ProcessFunctions > > >>> expose time and state which are the fundamental building blocks for > any > > >>> kind of streaming application. > > >>> To cover more use cases, we are planning to cover all these APIs in > > >>> PyFlink. > > >>> > > >>> In this discussion(FLIP-130), we propose to support the Python > > DataStream > > >>> API for the stateless part. For more detail, please refer to the FLIP > > >> wiki > > >>> page here[2]. If interested in the stateful part, you can also take a > > >>> look the design doc here[3] for which we are going to discuss in a > > >> separate > > >>> FLIP. > > >>> > > >>> Any comments will be highly appreciated! > > >>> > > >>> [1] https://flink.apache.org/flink-applications.html#layered-apis > > >>> [2] > > >>> > > >> > > > https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=158866298 > > >>> [3] > > >>> > > >> > > > https://docs.google.com/document/d/1H3hz8wuk228cDBhQmQKNw3m1q5gDAMkwTDEwnj3FBI/edit?usp=sharing > > >>> > > >>> Best, > > >>> Shuiqiang > > >>> > > >>> > > >>> > > >>> > > >> > > > > >
