Answer: a five-minute Tumbling window

## Analysis of Windowing Functions for Unique Tweet Counting ### Requirements: - Count tweets every 5 minutes - Each tweet must be counted only once - Output represents the count of tweets during the last 5 minutes ### Evaluation of Options: **A: Five-minute Sliding window** ❌ - Sliding windows output results whenever an event enters or exits the window - This would produce overlapping counts and potentially count the same tweet multiple times across different output intervals - Does not guarantee each tweet is counted only once **B: Five-minute Session window** ❌ - Session windows group events that occur close together in time, separated by gaps - Designed for analyzing user sessions, not for fixed-interval counting - Would not reliably produce counts every 5 minutes and may group tweets unpredictably **C: Five-minute Hopping window with one-minute hop** ❌ - Hopping windows produce overlapping results - With a 1-minute hop and 5-minute size, each tweet would appear in 5 consecutive outputs - Violates the requirement that each tweet must be counted only once **D: Five-minute Tumbling window** ✅ - Tumbling windows are non-overlapping, fixed-size intervals - Each tweet falls into exactly one 5-minute window - Guarantees each tweet is counted only once - Produces output every 5 minutes as required - Perfectly matches the requirement for counting unique tweets in discrete 5-minute intervals ### Conclusion: The tumbling window is the optimal choice because it creates discrete, non-overlapping time intervals where each event (tweet) is assigned to exactly one window. This ensures that tweets are never double-counted across different output periods, while still providing the required 5-minute aggregation intervals.

Author: LeetQuiz Editorial Team