Thank you for Dian's explaination. I thought pyflink suported non-keyed stream cause I saw "If key_by(...) is not called, your stream is not keyed." in the document lol. Sorry for the confusion to Ramana.
On Thu, 18 Aug 2022 at 9:36 AM, Dian Fu <dian0511...@gmail.com> wrote: > Hey Ramana, > > Non-keyed window will be supported in the coming Flink 1.16. See > https://issues.apache.org/jira/browse/FLINK-26480 for more details. In > releases prior to 1.16, you could work around it as following: > > ``` > data_stream = xxx > data_stream.key_by(lambda x: 'key').xxx().force_non_parallel() > ``` > > Regards, > Dian > > On Wed, Aug 17, 2022 at 11:13 AM Ramana <ramana...@gmail.com> wrote: > >> Hi Yuan - Thanks for your response. Wondering if the window api supports >> non-keyed streams? >> >> On Wed, Aug 17, 2022, 06:43 yu'an huang <h.yuan...@gmail.com> wrote: >> >>> Hi, >>> >>> >>> Pyflink should support window api. You can read this document. >>> >>> https://nightlies.apache.org/flink/flink-docs-release-1.15/docs/dev/python/datastream/operators/windows/ >>> >>> Hope this helps. >>> >>> Best, >>> Yuan >>> >>> On Tue, 16 Aug 2022 at 3:11 PM, Ramana <ramana...@gmail.com> wrote: >>> >>>> Hi All - >>>> >>>> Trying to achieve the following - >>>> >>>> 1. Ingest the data from RMQ >>>> 2. Decompress the data read from RMQ >>>> 3. Window it for 5 mins and process the data >>>> 4. Sink the processed data. >>>> >>>> Was able to achieve step1 and step 2, however realized that Pyflink >>>> *DataStream >>>> *doesn't have window support. Given the option that we can use >>>> TableAPI for windowing, I am trying to convert DataStream into >>>> *TableAPI*, but I have been facing issues with conversion. >>>> >>>> Could anybody help me find the right way of conversion? *DataStream *has >>>> data of type *Pandas DataFrame*. >>>> >>>> Appreciate any help here. >>>> >>>> Thanks >>>> >>>> -- >>>> DREAM IT, DO IT >>>> >>>
