Kundan Kumarr takes us through an example of the count window type in Apache Flink:
In the blog, we learned about Tumbling and Sliding windows which is based on time. In this blog, we are going to learn to define Flink’s windows on other properties i.e Count window. As the name suggests, count window is evaluated when the number of records received, hits the threshold.
Count window set the window size based on how many entities exist within that window. For example, if we fixed the count as 4, every window will have exactly 4 entities. It doesn’t matter whats the size of the window in terms of time. Window size will be different but the number of entities in that window will always be the same. Count windows can have overlapping windows or non-overlapping, both are possible. The count window in Flink is applied to keyed streams means there is already a logical grouping of the stream based on all values associated with a certain key. So the entity count will apply on a per-key basis.
I’m curious if there’s a combination of count + time, triggering when you hit X elements or Y seconds, whichever comes first.