Classic system design prompt but there's a lot hiding under the surface.
Start by clarifying functional and non-functional requirements, such as scale, latency, and consistency needs. Then propose a high-level design using a combination of a database for persistent storage and an in-memory data store like Redis for fast leaderboard operations. Dive into the data structures and algorithms for efficient ranking and updates, and discuss trade-offs between different approaches.
Pro tip: Emphasize the importance of choosing the right data structure (e.g., sorted sets) and partitioning strategy to handle high write throughput and low-latency reads at Google scale. Also, discuss how to handle ties and periodic updates without disrupting the user experience.
Ask questions to understand the scale (number of users, updates per second), latency requirements, consistency needs, and features like real-time updates, historical data, and leaderboard segmentation.
Outline the main components: a write path for score updates, a read path for retrieving leaderboards, and a storage layer. Consider using a combination of a persistent database (e.g., Bigtable) and an in-memory store (e.g., Redis) for performance.
Discuss using sorted sets (e.g., Redis ZSET) for efficient ranking, and algorithms for updating scores and retrieving top-K or a user's rank. Consider trade-offs between exact and approximate ranking for scalability.
Explain how to shard the leaderboard by time window or user segments, and how to handle hot keys. Discuss using consistent hashing and replication for fault tolerance.
Compare SQL vs NoSQL, in-memory vs disk-based, and push vs pull for updates. Discuss caching, batch updates, and handling ties. Mention monitoring and alerting for performance.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.