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We propose to only support full window processing on DataStream . It's difficult to support due to the challenges in supporting arbitrary types of windows on DataStream, including such as count windows, sliding windows, and session windows. The main reason is challenges arise from the fact that the DataStream is non-keyed and does not support keyed statebackend and keyed raw state. This issue results in two conflicts on the usage of various windows:

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Furthermore, based on community feedbacks, there is currently no demand for arbitrary window processing on DataStream.

Full window processing is a little special. Its processing semantics are has unique characteristics and is primarily applicable to batch processing scenarios. This feature could As such, it can be designed to work only when RuntimeExecutionMode=BATCHBATCH and does not support checkpoint. If user specifies When specifying RuntimeExecutionMode=STREAMING, the job will be failed fail to submit. Without the requirement for checkpoint, the underlying implementation can no longer rely on state and avoid the aforementioned conflict issues.

AdditionallyImportantly, it is worth noting that the DataSet API already offers full window processing capabilities. Integrating this existing capability of DataSet into DataStream would enhance its functionality and better meet the needs of users. Therefore, we propose to only support full window processing on DataStream.

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