Too Long; Didn't Read
The text discusses two types of windowing implementations in event stream processing: hopping and tumbling windows. Hopping windows have a fixed time length and move forward at intervals smaller than their length, which can result in overlapping results. Tumbling windows, a specialized case of hopping windows, have equal size and advance intervals, and hence do not overlap. The text further provides examples of how these windows can be implemented in Kafka Streams and Flink SQL and discusses suitable use cases for each windowing type. It concludes by providing resource links for further reading.
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Bill Bejeck
Curious about a lot of things in life, technology is one of them.
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