If the partition count or kafka IO size is large, then skip committin…

[kishorepola]

…g offsets that are not changed. Reduce kafka commit load

Please add a meaningful description for your change here

While committing offsets back to Kafka, Beam commits offsets back to all the topics and partitions in the KafkaIO. If some topic-partitions are idle, even then the same old offset is committed back. This causes lot of metadata pressure on the brokers if the kafka cluster has lot of idle partitions or cluster size is decently big.
Added in memory tracking for offsets.
Commit back only those offsets that are modified.

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[gemini-code-assist]

Summary of Changes

Hello @kishorepola, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request optimizes the Kafka offset commitment process within Apache Beam's KafkaIO connector. Previously, the system would commit offsets for all topic-partitions, even if some were idle and their offsets hadn't changed. This behavior could lead to excessive metadata load on Kafka brokers. The implemented solution introduces in-memory tracking of the last committed offsets and ensures that only partitions with advanced offsets are committed, thereby reducing the commit load and improving overall system efficiency.

Highlights

• Optimized Kafka Offset Commits: Introduced a mechanism to track the last successfully committed offsets for each topic-partition, preventing redundant commits for idle partitions.
• Reduced Kafka Broker Load: Modified the commitCheckpointMark method to only commit offsets that have advanced, significantly reducing metadata pressure on Kafka brokers, especially in large-scale deployments.
• Improved Efficiency: The change avoids unnecessary consumer.commitSync() calls when no offsets have changed, leading to more efficient resource utilization.

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Changelog

• sdks/java/io/kafka/src/main/java/org/apache/beam/sdk/io/kafka/KafkaUnboundedReader.java
  • Added java.util.HashMap import to support the new offset tracking mechanism.
  • Introduced a new private field lastCommittedOffsets (a Map<TopicPartition, Long>) to store the last known committed offset for each topic-partition.
  • Refactored the commitCheckpointMark method to: 1) Filter out partitions with uninitialized offsets. 2) Compare the current nextOffset with the lastCommittedOffsets to identify only those partitions whose offsets have genuinely advanced. 3) Construct a map (toCommit) containing only the advanced offsets. 4) Skip the consumer.commitSync() call if toCommit is empty, avoiding unnecessary operations. 5) Update lastCommittedOffsets only after a successful consumer.commitSync() operation.

Activity

• The pull request was created by kishorepola to address high Kafka commit load due to redundant offset commits for idle partitions.

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[github-actions]

Assigning reviewers:

R: @ahmedabu98 for label java.
R: @sjvanrossum for label kafka.

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[github-actions]

Reminder, please take a look at this pr: @ahmedabu98 @sjvanrossum

[gauravmishraitbhu]

Hi @tomstepp , can you help review this.

[tomstepp]

Thanks for contributing this!

[tomstepp]

@kishorepola - please let us know if you need any help with the feedback, thanks!

[kishorepola]

@tomstepp @johnjcasey Thank you for the thorough review! I've addressed all the feedback:

✅ Refactored commitCheckpointMark to use Java streams for better consistency
✅ Added debug logging to track idle partition counts
✅ Implemented time-based periodic commits (10-minute interval) for idle partitions to support time lag monitoring
✅ Added unit test KafkaUnboundedReaderIdlePartitionTest to verify the optimization behavior

All changes maintain backward compatibility and follow spotless formatting standards. Ready for another review!

[tomstepp]

@Abacn and/or @johnjcasey can you help approve/submit please?