Windowing with Table-Valued Functions | Apache Flink® SQL
Get started: https://cnfl.io/apache-flink-sql-modu... | Apache Flink® SQL makes it easy to implement analytics that summarize important attributes of real-time data streams.
There are four different types of time-based windows in Flink SQL: tumbling, hopping, cumulating, and session. Learn how these various window types behave, and how to work with the table-valued functions that are at the heart of Flink SQL’s support for windowing.
For more information, check out the Apache Flink SQL course on Confluent Developer: https://cnfl.io/apache-flink-sql-modu...
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► OVER aggregations - https://cnfl.io/4fz5Um7
► Exercise: Streaming analytics - https://cnfl.io/4eUkuVf
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CHAPTERS
00:00 - Intro
00:41 - Tumbling windows
01:59 - Window table-valued functions
02:40 - What is window_time?
03:02 - Avoid this pitfall!
03:49 - Hopping windows
04:20 - Cumulating windows
05:02 - Session windows
05:36 - Conclusion
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