I jumped straight into the database schema and kind of forgot to clarify scope first.
Start by clarifying requirements and scale (e.g., number of users, reviews, restaurants, read/write ratio). Then propose a high-level architecture covering data modeling, storage choices, and key components like search and ranking. Finally, dive into trade-offs and scalability considerations, especially around consistency and availability.
Pro tip: Emphasize how you would handle the read-heavy nature of the platform with caching and denormalization, and discuss how to ensure data consistency for reviews across distributed systems.
Ask questions to understand functional and non-functional requirements: user base size, expected QPS, read/write ratio, latency requirements, and consistency needs.
Sketch the main components: client apps, API gateway, services (user, restaurant, review, search), databases, cache, and message queues. Explain data flow for key operations like posting a review and searching restaurants.
Design schemas for users, restaurants, reviews, and ratings. Choose appropriate databases (e.g., SQL for transactional data, NoSQL for reviews, Elasticsearch for search) and discuss indexing strategies.
Address how to scale reads with caching (e.g., Redis), CDN for static assets, and database sharding/replication. Discuss handling hot restaurants and viral reviews.
Discuss trade-offs between consistency and availability (CAP theorem), and how to handle eventual consistency for reviews and ratings. Mention techniques like optimistic locking or versioning.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.