How does Apache Flink handle event time processing?
- Implements sequential processing
- Relies on batch processing techniques
- Uses synchronized clocks for event ordering
- Utilizes watermarks and windowing
Apache Flink handles event time processing by utilizing watermarks and windowing techniques. Watermarks are markers that signify the progress of event time within the stream and are used to trigger computations based on the completeness of the data. Windowing enables the grouping of events into time-based or count-based windows for aggregation and analysis. By combining watermarks and windowing, Flink ensures accurate and efficient event time processing, even in the presence of out-of-order events or delayed data arrival.
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