Understanding Flink SQL changelogs is essential for anyone looking to optimize performance in streaming data pipelines. In this session, we’ll demystify how changelog modes affect everything from state size and latency to network usage and compute requirements—and why even small SQL changes can have a big impact.
You’ll learn:
- What changelog modes are and how they shape Flink SQL execution
- How operators transform data as it flows from source to sink
- The role of primary keys and upsert keys in determining changelog behavior
- Practical examples of how to choose the right mode for efficiency and accuracy
By the end of this talk, you’ll know how to interpret and optimize changelog behavior in your Flink SQL pipelines to achieve better performance and resource utilization.
Perfect for: Data engineers, stream processing developers, and anyone using Flink SQL to build or tune real-time data systems.
