[FLINK-37627][BugFix][Connectors/Kinesis] Restarting from a checkpoint/savepoint which coincides with shard split causes data loss

[arunlakshman]

Purpose of the change

[FLINK-37627][BugFix][Connectors/Kinesis] Restarting from a checkpoint/savepoint which coincides with shard split causes data loss

Today Flink does not support distributed consistency of events from subtask (Task Manager) to coordinator (Job Manager) - https://issues.apache.org/jira/browse/FLINK-28639. As a result we have a race condition that can lead to a shard and it's children shards stopped being processed after a job restart.

• A checkpoint started
• Enumerator took a checkpoint (shard was assigned here)
• Enumerator sent checkpoint event to reader
• Before taking reader checkpoint, a SplitFinishedEvent came up in reader
• Reader took checkpoint
• Now, just after checkpoint complete, job restarted

This can lead to a shard lineage getting lost because of a shard being in ASSIGNED state in enumerator and not being part of any task manager state.
This PR changes the behaviour by also checkpointing the finished splits events received in between two checkpoints and on restore, those events again getting replayed.

Verifying this change

Please make sure both new and modified tests in this PR follows the conventions defined in our code quality guide: https://flink.apache.org/contributing/code-style-and-quality-common.html#testing

(Please pick either of the following options)

• Added UTs and this is almost a cherry pick of [FLINK-37416][BugFix][Connectors/DynamoDB] Fix state inconsistency issue in DDB connector when sending split finished event from reader -> enumerator #193 into the kinesis connector
• I manually verified this by running the connector in a local flink cluster which was getting restarted every 10 minutes. No checkpoint inconsistency was observed

Significant changes

(Please check any boxes [x] if the answer is "yes". You can first publish the PR and check them afterwards, for convenience.)

• Dependencies have been added or upgraded
• Public API has been changed (Public API is any class annotated with @Public(Evolving))
• Serializers have been changed
• New feature has been introduced
  • If yes, how is this documented? (not applicable / docs / JavaDocs / not documented)

[boring-cyborg]

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