Trending-detection with acceleration
Design a trending-detection system that surfaces topics whose interest is *accelerating*, not just topics that are popular. A perennially-high term (e.g. 'weather') should NOT trend; a term going from 200 to 20,000 mentions in 10 minutes SHOULD. You ingest 800k events/sec across millions of distinct terms, want updates every ~30s, and must resist a coordinated bot push of a hashtag. Define the trending score, the windowing, and the abuse defenses.
What a strong answer looks like
Clarify scale and constraints first. Propose a clean component breakdown, then go deep on the hard parts (data model, bottlenecks, consistency, failure modes) and name the trade-offs you are making.
Clarify5:00 left
Estimate5:00 planned
Design15:00 planned
Deep dive12:00 planned
Failure8:00 planned
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.
Run or narrate your approach, then ask the coach.