Geospatial datastore sharding
Design the sharding and partitioning scheme for a global geospatial datastore that holds 1B moving entities and serves both point lookups by id and radius/kNN spatial queries, with hotspots in dense metros (Tokyo, NYC) and quiet rural regions. How do you partition so spatial queries stay local while avoiding hot shards, and how do you rebalance as density shifts?
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.