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https://issues.apache.org/jira/browse/FLINK-37375?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jufang He updated FLINK-37375:
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Description:
In some Flink task operators, slow operations such as file uploads or data
flushing may be performed during the synchronous phase of Checkpoint. Due to
performance issues with external storage components, the synchronous phase may
take too long to execute, significantly impacting the job's throughput. For
example, during our internal use of Paimon, we observed that uploading files to
HDFS during the Checkpoint synchronous phase could encounter random HDFS slow
node issues, leading to a substantial negative impact on task throughput.
To address this issue, I propose supporting a generic operator custom
asynchronous operation feature, allowing users to move time-consuming logic to
the asynchronous phase of Checkpoint, thereby minimizing the blocking of the
main thread and improving task throughput. For instance, the Paimon writer
operator could write data locally during the Checkpoint synchronous phase and
upload files to remote storage during the asynchronous phase. Beyond the Paimon
data upload scenario, other operator logic may also experience slow execution
during the synchronous phase. This approach aims to uniformly optimize such
issues.
I drafted a flip for this issue:
[https://docs.google.com/document/d/1lwxLEQjD6jVhZUBMRGhzQNWKSvdbPbYNQsV265gR4kw]
was:
In some Flink task operators, slow operations such as file uploads or data
flushing may be performed during the synchronous phase of Checkpoint. Due to
performance issues with external storage components, the synchronous phase may
take too long to execute, significantly impacting the job's throughput. For
example, during our internal use of Paimon, we observed that uploading files to
HDFS during the Checkpoint synchronous phase could encounter random HDFS slow
node issues, leading to a substantial negative impact on task throughput.
To address this issue, I propose supporting a generic operator custom
asynchronous snapshot feature, allowing users to move time-consuming logic to
the asynchronous phase of Checkpoint, thereby minimizing the blocking of the
main thread and improving task throughput. For instance, the Paimon writer
operator could write data locally during the Checkpoint synchronous phase and
upload files to remote storage during the asynchronous phase. Beyond the Paimon
data upload scenario, other operator logic may also experience slow execution
during the synchronous phase. This approach aims to uniformly optimize such
issues.
I drafted a flip for this issue:
[https://docs.google.com/document/d/1lwxLEQjD6jVhZUBMRGhzQNWKSvdbPbYNQsV265gR4kw]
> Checkpoint supports the Operator to customize asynchronous operation
> --------------------------------------------------------------------
>
> Key: FLINK-37375
> URL: https://issues.apache.org/jira/browse/FLINK-37375
> Project: Flink
> Issue Type: New Feature
> Components: Runtime / Checkpointing
> Affects Versions: 1.20.1
> Reporter: Jufang He
> Priority: Major
> Labels: pull-request-available
>
> In some Flink task operators, slow operations such as file uploads or data
> flushing may be performed during the synchronous phase of Checkpoint. Due to
> performance issues with external storage components, the synchronous phase
> may take too long to execute, significantly impacting the job's throughput.
> For example, during our internal use of Paimon, we observed that uploading
> files to HDFS during the Checkpoint synchronous phase could encounter random
> HDFS slow node issues, leading to a substantial negative impact on task
> throughput.
> To address this issue, I propose supporting a generic operator custom
> asynchronous operation feature, allowing users to move time-consuming logic
> to the asynchronous phase of Checkpoint, thereby minimizing the blocking of
> the main thread and improving task throughput. For instance, the Paimon
> writer operator could write data locally during the Checkpoint synchronous
> phase and upload files to remote storage during the asynchronous phase.
> Beyond the Paimon data upload scenario, other operator logic may also
> experience slow execution during the synchronous phase. This approach aims to
> uniformly optimize such issues.
> I drafted a flip for this issue:
> [https://docs.google.com/document/d/1lwxLEQjD6jVhZUBMRGhzQNWKSvdbPbYNQsV265gR4kw]
>
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