Social graph sharding
Design the storage and sharding for a social graph database backing a 'people you may know' / friends-of-friends feature, with 1 billion users averaging 300 connections (some celebrities have 50M), serving 80k graph traversals/sec that walk 2–3 hops. How do you store the adjacency data, shard the graph, and keep 2-hop traversals fast despite supernodes that span many shards?
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.