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As always, we bring you news, updates and recommended content from the hectic world of Apache Kafka® and stream processing.
Sometimes it seems that in Apache Kafka every improvement is preceded by an involved KIP process. This month we’ve merged a great patch that improved the 99% latency of Kafka without requiring user visible changes: https://issues.apache.org/jira/browse/KAFKA-4614. Not only does it make a fast system even faster, the JIRA itself is worthy of study. I wish all JIRAs included this level of research.
Some important improvements do require KIPs. Here is what we’ve seen in active discussions this month:
Notable Blogs and Presentations:
This blog post demonstrates using Tableflow to easily transform Kafka topics into queryable Iceberg tables. It uses UK Environment Agency sensor data as a data source, and shows how to use Tableflow with standard SQL to explore and understand the data.
The guide covers Kafka consumer offsets, the challenges with manual control, and the improvements introduced by KIP-1094. Key enhancements include tracking the next offset and leader epoch accurately. This ensures consistent data processing, better reliability, and performance.