Apache Kafka - Real-time Stream Processing (Master Class) - Table Caching and Emit Rates

The lecture explains the caching mechanism in Kafka's K Table, highlighting its role in optimizing data processing by reducing the number of operations. It discusses how caching affects performance and data correctness, and provides configuration options for tuning caching in Kafka Streams. Advanced techniques like rate limiting using the suppress operator are also covered, emphasizing the importance of buffer memory management. The lecture concludes by encouraging experimentation with configurations to understand their impact on application behavior.

Discuss the implications of disabling caching in K Tables.

What is the significance of the K Table suppress operator in Kafka Streams?

What happens if the buffer fills up in the context of Kafka Streams?