Answer-first summary for fast verification
Answer: sliding window (also called hopping windows)
Sliding windows (also known as hopping windows) are ideal for modeling a consistent time interval in a stream, making them the best choice for continuously averaging temperature over the past hour. Fixed windows (or tumbling windows) represent consistent, disjoint time intervals, while session windows accommodate gaps in duration, suitable for non-continuous data streams. Apache Beam runners, like Cloud Dataflow, do not support concurrent window functions. For more details, visit [Cloud Dataflow documentation](https://cloud.google.com/dataflow/docs/concepts/streaming-pipelines).
Author: LeetQuiz Editorial Team
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A delivery drone manufacturer utilizes an Apache Beam runner for its monitoring system. The system analyzes temperature readings from the past hour and triggers an alert if any reading deviates by more than 2 standard deviations from the mean. Which windowing function would you implement for this operation?
A
session windows
B
fixed windows (also called tumbling windows)
C
sliding window (also called hopping windows)
D
concurrent windows
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