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Posted to issues@flink.apache.org by "牛一凡 (Jira)" <ji...@apache.org> on 2026/07/01 10:39:00 UTC
[jira] [Commented] (FLINK-40038) [mysql][pipeline] Incremental sync throughput is low in hotspot UPDATE workloads due to deserialization overhead
[ https://issues.apache.org/jira/browse/FLINK-40038?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18092921#comment-18092921 ]
牛一凡 commented on FLINK-40038:
-----------------------------
I would like to work on this issue. Please assign it to me.
> [mysql][pipeline] Incremental sync throughput is low in hotspot UPDATE workloads due to deserialization overhead
> ----------------------------------------------------------------------------------------------------------------
>
> Key: FLINK-40038
> URL: https://issues.apache.org/jira/browse/FLINK-40038
> Project: Flink
> Issue Type: Improvement
> Components: Flink CDC
> Affects Versions: cdc-3.7.0
> Reporter: 牛一凡
> Priority: Minor
> Attachments: image-2026-07-01-18-11-43-636.png
>
>
> *Motivation*
> We observed low incremental sync throughput on a MySQL-to-Doris pipeline when using Flink CDC in a large-table hotspot UPDATE workload. In this scenario, upstream and downstream started to lag behind and the job showed an obvious backlog during incremental synchronization.
> After collecting and analyzing the job flame graph, we found that a significant portion of the CPU time was spent in the MySQL pipeline deserialization path, especially around repeated schema/data type inference during row deserialization. This overhead becomes more noticeable when a table receives frequent UPDATE events.
> A related performance concern was mentioned in FLINK-35715, but in our workload this bottleneck still exists and is still impactful enough to cause chasing-lag behavior in production-like environments.
> It would be great to further investigate and optimize this issue.
> *Flame Graph*
> !image-2026-07-01-18-11-43-636.png!
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