Random Thoughts on Coding

In the third installment of this windowing blog series, you’ll learn about cumulating and session windows. In previous posts, we’ve covered hopping and tumbling windows and sliding windows and the Flink SQL equivalent - OVER aggregations. The cumulate window is unique to Flink SQL. The session window has been available...

In the third installment of this windowing blog series, you’ll learn about sliding windows and a bit of SQL. In the previous post, we covered hopping and tumbling windows, both of which Kafka Streams and Flink SQL provide. In this installment, we will discuss sliding windows, supported by Kafka Streams...

In the first post of this series, we discussed what event streaming windowing is, and we examined in detail the structure of a windowed aggregate in Kafka Streams and Flink SQL. In this post, we’ll dive into two specific windowing implementations: hopping and tumbling windows. Hopping windows A hopping window...

Stream processing is the best way to work with event data. While batch processing still has its use cases, and probably always will, only stream processing offers the ability to respond in real-time to events. But if we zoom in, what does it look like to respond to events? By...

Some time ago, over 2 years, I started a 3 part series on the CompletableFuture. I’m just now getting around to doing part two now. My long time delay in completing this series was due to working in my book Kafka Streams in Action. But now that’s done I can...