Got through brute force and the optimized version pretty cleanly, tradeoffs discussion felt okay too.
Start by clarifying requirements (e.g., single-threaded vs. distributed, exact vs. approximate counts) and then present a brute-force solution using a list of timestamps with O(n) space and O(n) time per query. Then propose an optimized approach using a circular buffer of 300 buckets (one per second) with O(1) time per hit and O(1) space, discussing trade-offs like precision and memory.
Pro tip: Mention that in a real system like Uber, you'd likely use a distributed counter with sliding windows (e.g., Redis sorted sets or a ring buffer per shard) and discuss how to handle clock skew and eventual consistency.
Ask about scale (hits per second), precision (exact vs. approximate), and whether the system is single-node or distributed. This shows you think before coding.
Store all hit timestamps in a list; on query, filter out timestamps older than 5 minutes and return the count. Discuss O(n) time and space, and why it's inefficient for high throughput.
Use a circular buffer of 300 buckets (one per second) to store counts. On each hit, increment the current second's bucket; on query, sum all buckets. This gives O(1) time per hit and O(1) space (300 integers).
Compare precision (brute force exact, bucket approach approximate within 1 second), memory (O(n) vs. O(1)), and concurrency (need locks or atomic operations). Mention that bucket approach can be extended to sliding window with finer granularity.
Address thread safety, clock drift, and distributed scenarios (e.g., sharding by user ID, using Redis sorted sets). Suggest monitoring and potential optimizations like lazy deletion.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.