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 >>> >>
