Hi Sumeet, Yes, you are right. It supports mix use of PyFlink DataStream API and PyFlink Table API. It's recommended to use PyFlink Table API for window operations for now before it's supported in PyFlink DataStream API.
Regards, Dian On Mon, Mar 22, 2021 at 4:34 PM Sumeet Malhotra <[email protected]> wrote: > Apologies. I meant `StreamTableEnvironment.to_append_stream` in my last > message. > > On Mon, Mar 22, 2021 at 2:03 PM Sumeet Malhotra <[email protected]> > wrote: > >> Thanks Dian. >> >> Another question I have is, since PyFlink Datastream API still doesn't >> have native Window support, what's the recommended way to introduce >> windows? Use PyFlink Table API for windows in conjunction with the >> Datastream APIs? For example, read input records from Kafka into a table >> and then use `StreamTableEnvironment.to_apend_table(...)` to push records >> into a data stream? >> >> Thanks, >> Sumeet >> >> >> On Mon, Mar 22, 2021 at 1:05 PM Dian Fu <[email protected]> wrote: >> >>> Hi Sumeet, >>> >>> It still doesn't support side outputs in PyFlink. >>> >>> >> Or do I have to replicate the input datastream and then apply record >>> specific filters? >>> I'm afraid that yes. >>> >>> Regards, >>> Dian >>> >>> >>> On Sun, Mar 21, 2021 at 5:20 PM Sumeet Malhotra < >>> [email protected]> wrote: >>> >>>> Hi, >>>> >>>> I have a use case where I need to process incoming records on a Kafka >>>> topic based on a certain record field that defines the record type. >>>> >>>> What I'm thinking is to split the incoming datastream into record-type >>>> specific streams and then apply record-type specific stream processing on >>>> each. What's the recommended way to achieve this in PyFlink? Are side >>>> outputs supported in PyFlink (I couldn't find any reference in the >>>> codebase)? Or do I have to replicate the input datastream and then apply >>>> record specific filters? >>>> >>>> Thanks, >>>> Sumeet >>>> >>>
