Spent the first few minutes just listing entities out loud: customers, orders, pizzas, toppings, delivery addresses.
Start by clarifying the scope and requirements of the pizza ordering system, such as whether it's for a single restaurant or a marketplace, and what features are needed. Then, design a normalized schema that captures core entities like customers, orders, pizzas, and toppings, while considering scalability and performance. Finally, discuss trade-offs and potential optimizations, such as denormalization for read-heavy workloads.
Pro tip: Demonstrate awareness of Amazon's leadership principles by emphasizing customer obsession (e.g., ensuring the schema supports a smooth ordering experience) and diving deep into edge cases like order modifications or refunds.
Ask questions to understand the system's scope, expected scale, and key features (e.g., custom pizzas, multiple locations, delivery). This ensures the schema meets actual needs.
List the main entities such as Customer, Order, Pizza, Topping, and Store. Define their attributes and relationships to form the basis of the schema.
Create normalized tables with primary and foreign keys, using junction tables for many-to-many relationships (e.g., OrderItems, PizzaToppings). Consider using surrogate keys for simplicity.
Discuss indexing strategies, partitioning, and potential denormalization for read-heavy operations. Consider how the schema supports high throughput and low latency.
Talk about trade-offs between normalization and performance, and how the schema can evolve to support new features like promotions or ratings.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.