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3. We add four APIs to PartitionWindowedStream,  including mapPartition, sortPartition, aggregate and reduce.

Proposed Changes

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Support only full window processing on non-keyed DataStream

We propose to support only support full window processing on non-keyed DataStream. There are challenges in supporting arbitrary types of windows, such as count windows, sliding windows, and session windows. These 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, we have not observed that currently no users suggests suggest to support arbitrary window processing on non-keyed DataStream.

Full window processing has unique characteristics and is primarily applicable to batch processing scenarios. As such, it can be designed to work only when RuntimeExecutionMode=BATCH and does not support checkpoint. When specifying RuntimeExecutionMode=STREAMING, the job will fail to submiton submission. Without the requirement for checkpoint, the underlying implementation can no longer rely on state and avoid the aforementioned conflict issues.Importantly, the DataSet API already offers full window processing capabilities. Integrating this existing capability of DataSet into non-keyed DataStream will enhance its functionality and better meet the needs of users. Therefore, we propose to only support full window processing on non-keyed DataStream.

Introduce the PartitionWindowedStream

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