In Google Dataflow, what does the term "windowing" refer to?
- Dividing the data stream into finite time intervals for analysis.
- Scaling the computing resources dynamically based on the workload.
- Distributing data across multiple geographic regions for fault tolerance.
- Converting unstructured data into structured formats for processing.
Understanding windowing in Google Dataflow is crucial for performing time-based analysis and computations on streaming data. It allows developers to define windows over data streams and apply transformations or aggregations within those windows, facilitating various use cases such as real-time analytics and event processing.
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