tapomoyadhikari commented on issue #26189:
URL: https://github.com/apache/doris/issues/26189#issuecomment-1793352001
The thread dump you provided doesn't contain detailed information about the
specific Flink CDC task or your application's code. However, I can offer some
general guidance on how to approach the issue of high CPU usage on one of the
BE nodes running Flink CDC tasks:
1. Analyze the High CPU Thread:
- You'll need to identify which thread or process within your Flink CDC
task is causing the high CPU usage. This requires more detailed information
about the threads and their activity.
- Use a tool like `jstack`, `jvisualvm`, or other profiling tools to
capture thread dumps and gain insights into what the high CPU thread is doing.
This will help you pinpoint the exact issue.
2. Possible Causes of High CPU Usage:
- Inefficient code: Review the code of your Flink CDC task to ensure it's
optimized and not causing unnecessary CPU load.
- Data volume: High data volumes being processed by the task can lead to
high CPU usage.
- Resource contention: Check if there are resource contention issues,
such as locks, that are causing threads to wait and consume CPU.
3. Check Flink Configuration:
- Review the Flink configuration parameters, such as parallelism, to
ensure they are set appropriately for your task.
4. MySQL and Doris Synchronization:
- The high CPU usage may be related to the MySQL and Doris
synchronization process. Ensure that the synchronization process is configured
correctly and efficiently.
5. Monitoring:
- Set up monitoring tools like Prometheus, Grafana, or other monitoring
solutions to gain insights into the performance of your Flink CDC tasks.
6. Scale Out:
- If the high CPU usage is due to high data volumes, consider scaling out
your Flink CDC task to distribute the load across multiple BE nodes.
7. Optimization:
- Profile and optimize your code, identify bottlenecks, and make
necessary improvements.
8. Fine-Tuning:
- Fine-tune Flink's configuration settings based on your specific
workload and requirements.
9. Updates and Patches:
- Ensure that you are using the latest versions of Flink and other
components, and apply any relevant updates or patches.
10. Consult Documentation and Community:
- Refer to the documentation for Flink and your synchronization tools
for best practices and troubleshooting guidance.
- Seek help from the Flink and Doris communities or support channels for
more specific assistance.
Without more detailed information, it's challenging to pinpoint the exact
cause of the high CPU usage. You may need to investigate the application
further and monitor its behavior to identify and resolve the issue.
Additionally, consider involving your development and operations teams to
collaborate on debugging and optimizing the system.
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