[hotfix] [API/DataStream]: Ensure the proper triggering functionality of ContinuousProcessingTimeTrigger

[beibei-li01]

What is the purpose of the change

This pull request fixes an issue in ContinuousProcessingTimeTrigger that triggered logic failure when processingtime lasted longer than the maximum window time

Brief change log

When “time == window.maxTimestamp()”, increment the time parameter in registerNextFireTimestamp by one based on its original value, keeping it unchanged otherwise.

In registerNextFireTimestamp, when time is greater than window.maxTimestamp(), use time + interval as the next trigger value, otherwise, maintain the original logic.

For example, when processing historical data in the following way, the computation can be guaranteed to trigger every five seconds as expected, without failing to trigger or falling into a loop of continuous triggering: datastream .window(TumblingEventTimeWindows.of(Time.days(1), Time.hours(-8))) .trigger(ContinuousProcessingTimeTriggerCustomer.of(Time.seconds(5)))

Verifying this change

This change has been validated with business data and is correct.

Does this pull request potentially affect one of the following parts:

Dependencies (does it add or upgrade a dependency): no The public API, i.e., is any changed class annotated with @Public(Evolving): no The serializers: no The runtime per-record code paths (performance sensitive): no Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Kubernetes/Yarn, ZooKeeper: no The S3 file system connector: no

Documentation

Does this pull request introduce a new feature? no

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CI report:

• 39fe9fd7cc625b6cc6e808b3bbe95b5d79bae50b Azure: SUCCESS

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