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https://issues.apache.org/jira/browse/FLINK-33734?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17818255#comment-17818255
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Zakelly Lan commented on FLINK-33734:
-------------------------------------
[~Feifan Wang] Sorry for the late reply as I was on vacation for a few weeks.
Overall it makes sense to offload file creation from JM to TM, especially in
conjunction with the file merging mechanism in TM side introduced by FLIP-306.
I thought it is better to show some detailed analysis about the performance
enhancement and some explanation about the implementation as well as the test
setup. I'm curious about why the checkpoint time reduced by 36s (from 66s to
30s) when serializing in TM side while the metadata time is only 12s. And how
the long-tail of async duration happened, is it due to massive file creation
requests and hotspot issue in NN node of HDFS?
> Merge unaligned checkpoint state handle
> ---------------------------------------
>
> Key: FLINK-33734
> URL: https://issues.apache.org/jira/browse/FLINK-33734
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / Checkpointing
> Reporter: Feifan Wang
> Assignee: Feifan Wang
> Priority: Major
> Labels: pull-request-available
> Attachments: image-2024-02-18-15-12-20-665.png
>
>
> h3. Background
> Unaligned checkpoint will write the inflight-data of all InputChannel and
> ResultSubpartition of the same subtask to the same file during checkpoint.
> The InputChannelStateHandle and ResultSubpartitionStateHandle organize the
> metadata of inflight-data at the channel granularity, which causes the file
> name to be repeated many times. When a job is under backpressure and task
> parallelism is high, the metadata of unaligned checkpoints will bloat. This
> will result in:
> # The amount of data reported by taskmanager to jobmanager increases, and
> jobmanager takes longer to process these RPC requests.
> # The metadata of the entire checkpoint becomes very large, and it takes
> longer to serialize and write it to dfs.
> Both of the above points ultimately lead to longer checkpoint duration.
> h3. A Production example
> Take our production job with a parallelism of 4800 as an example:
> # When there is no back pressure, checkpoint end-to-end duration is within 7
> seconds.
> # When under pressure: checkpoint end-to-end duration often exceeds 1
> minute. We found that jobmanager took more than 40 seconds to process rpc
> requests, and serialized metadata took more than 20 seconds.Some checkpoint
> statistics:
> |metadata file size|950 MB|
> |channel state count|12,229,854|
> |channel file count|5536|
> Of the 950MB in the metadata file, 68% are redundant file paths.
> We enabled log-based checkpoint on this job and hoped that the checkpoint
> could be completed within 30 seconds. This problem made it difficult to
> achieve this goal.
> h3. Propose changes
> I suggest introducing MergedInputChannelStateHandle and
> MergedResultSubpartitionStateHandle to eliminate redundant file paths.
> The taskmanager merges all InputChannelStateHandles with the same delegated
> StreamStateHandle in the same subtask into one MergedInputChannelStateHandle
> before reporting. When recovering from checkpoint, jobmangager converts
> MergedInputChannelStateHandle to InputChannelStateHandle collection before
> assigning state handle, and the rest of the process does not need to be
> changed.
> Structure of MergedInputChannelStateHandle :
>
> {code:java}
> { // MergedInputChannelStateHandle
> "delegate": {
> "filePath":
> "viewfs://hadoop-meituan/flink-yg15/checkpoints/retained/1234567/ab8d0c2f02a47586490b15e7a2c30555/chk-31/ffe54c0a-9b6e-4724-aae7-61b96bf8b1cf",
> "stateSize": 123456
> },
> "size": 2000,
> "subtaskIndex":0,
> "channels": [ // One InputChannel per element
> {
> "info": {
> "gateIdx": 0,
> "inputChannelIdx": 0
> },
> "offsets": [
> 100,200,300,400
> ],
> "size": 1400
> },
> {
> "info": {
> "gateIdx": 0,
> "inputChannelIdx": 1
> },
> "offsets": [
> 500,600
> ],
> "size": 600
> }
> ]
> }
> {code}
> MergedResultSubpartitionStateHandle is similar.
>
>
> WDYT [~roman] , [~pnowojski] , [~fanrui] ?
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