Introduction
In the world of Kafka message consumption, the Spring Kafka framework provides convenient abstractions and utilities. However, a bug in the SeekToCurrentErrorHandler component can cause unexpected behavior when the concurrency level is lower than the number of partitions. This blog post aims to shed light on this bug, its impact, and the version in which it is resolved.
Understanding the Bug
The bug manifests when using Spring Kafka version 2.2.7. If the concurrency level is set to a value lower than the number of partitions for a topic, the maxFailures configuration of the SeekToCurrentErrorHandler does not work as intended. Instead of stopping message consumption after reaching the specified number of failures, the consumer retries the failed message indefinitely.
Reproducing the Issue
To reproduce the issue, follow these steps:
- Create a topic with multiple partitions (e.g., 3 or 6).
- In the Spring Kafka configuration, set the concurrency level to 1.
- Configure the SeekToCurrentErrorHandler with a positive value for maxFailures (e.g., 3).
- Send a substantial number of messages to the topic.
Upon reproducing the issue, you will observe that each failed message is retried infinitely, regardless of the maxFailures configuration. Additionally, the consumer lag may increase due to the retries.
Impact and Workaround
The bug primarily affects applications with low concurrency levels and a higher number of partitions. The infinite retries can lead to message processing delays, increased resource consumption, and potential performance degradation.
Although there is no direct workaround for this bug in Spring Kafka 2.2.7, it is possible to mitigate the issue by adjusting the concurrency level to match the number of partitions. By doing so, you ensure that the maxFailures configuration functions as intended.
Bug Fix and Updated Versions
Fortunately, the bug has been addressed in the subsequent release of Spring Kafka. In version 2.2.8, the SeekToCurrentErrorHandler is updated to resolve the issue, allowing the maxFailures configuration to work correctly even with lower concurrency levels.
Conclusion
The Spring Kafka SeekToCurrentErrorHandler bug, which affects the functioning of maxFailures when the concurrency level is less than the partition number, can cause message consumption issues. It is crucial to be aware of this bug, its impact, and the version in which it is fixed.
If you encounter this bug, consider upgrading to Spring Kafka version 2.2.8 or later to ensure proper error handling and message consumption behavior. With the bug resolved, you can confidently leverage the power of Spring Kafka in your applications.
Remember to stay updated with the latest versions and bug fixes to ensure the stability and reliability of your Kafka message consumption processes.
