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Time and Watermarks in Flink

Explore how Flink uses processing time and event time to manage unbounded streams. Learn about watermarks as a mechanism to track event time progress and handle late data in distributed stream processing.

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As explained in the previous lesson, time is a crucial element that is commonly used to define boundaries on unbounded streams.

Like other stream processing systems, such as MillWheelT. Akidau et al., “MillWheel: Fault-tolerant Stream Processing at Internet Scale,” Proceedings of the VLDB Endowment, Volume 6 Issue 11, August 2013, 2013. and The Dataflow ModelT. Akidau et al., “The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-scale, Unbounded, Out-of-order Data Processing,” Proceedings of the 41st International Conference on Very Large Data Bases, Volume 8 Issue 12, August 2015, 2015., Flink supports two main notions of time: processing time and event ...