My first pass was a queue, just append timestamps on hit() and prune anything older than 300 seconds on getHits().
Start by clarifying requirements and constraints, then propose a solution using a circular buffer or a queue with timestamp buckets. Discuss trade-offs between time and space complexity, and address the follow-up by considering scalability and concurrency.
Pro tip: Mention that timestamps are monotonically increasing, so you can use a queue and evict old entries efficiently. Also, for the follow-up, suggest sharding or using a distributed counter to handle high throughput.
Ask about the expected scale, whether timestamps are in seconds, and if multiple hits per timestamp are allowed. Confirm that getHits should return hits in the past 300 seconds inclusive.
Propose using a queue of timestamps or a circular buffer of size 300. For each hit, add timestamp; for getHits, remove timestamps older than timestamp-300 and return the count.
If hits per second are high, use a bucket approach: an array of 300 buckets, each storing count for that second. Use modulo arithmetic to map timestamps to buckets and handle wraparound.
Discuss scaling: shard by timestamp or user, use distributed counters, or approximate counting with probabilistic data structures if exact count not required. Mention concurrency control.
Compare queue vs bucket approach: queue uses O(n) space where n is hits in 300s, bucket uses O(300) space but may have collisions if multiple hits per second. Discuss precision vs memory.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.