Design and scale a Yelp-like platform

Q: Design and scale a Yelp-like platform

This question evaluates system design and engineering skills including data modeling, indexing, geospatial and full-text search, caching, replication and sharding for a high-scale reviews platform, together with key generation, storage layout, redirects, rate limiting and analytics for a URL-shortening service, probing the ability to balance scalability, consistency, availability, and operational complexity. It falls under the System Design / Distributed Systems / Databases domain and is commonly asked to assess architectural reasoning and trade-off analysis, testing both conceptual high-level design and practical implementation considerations such as performance, fault tolerance, and operational constraints.

Q: How do I approach System Design interview questions?

System Design questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master system design interviews.

Q: What difficulty level is this interview question?

This is a hard difficulty System Design question, commonly asked during Onsite rounds at Apple.

Q: What role is this question designed for?

This question is commonly asked for Software Engineer candidates at Apple during technical interviews.

Question

System Design: Yelp-like Local-Business Reviews Platform + URL Shortener

You are designing two systems:

A Yelp-like local-business reviews platform that supports millions of users, businesses with geocoordinates, categories, reviews, ratings, photos, and check-ins.
A high-scale URL-shortening service.

Part A — Yelp-like Reviews Platform

Define and discuss:

Core data model
- Entities: users, businesses (with geocoordinates), categories, reviews, ratings, photos, check-ins.
- Indexes for common queries.
Scaling reads
- Replication, caches, CDN, search indexes.
Scaling writes
- Sharding, queues, consistency (read-your-writes), backfills/migrations.
Search and geospatial queries
- Full-text, category filters, distance/radius queries, sorting.
Cache invalidation and performance
- What to cache, when/how to invalidate, pagination, hot keys, tail latency.

Part B — URL-Shortening Service

Outline a design covering:

Key/ID generation and collision handling (sequential vs random, length analysis).
Storage layout and data model.
Redirects, HTTP status codes, and CDN usage.
Rate limiting and abuse prevention.
Analytics and aggregation.
TTL/expiration, deletion, and alias reuse policy.
Custom aliases and namespace management.
Strategies to scale high read/write traffic (multi-region, cache, sharding).

Design and scale a Yelp-like platform

Quick Overview

Design and scale a Yelp-like platform

System Design: Yelp-like Local-Business Reviews Platform + URL Shortener

Part A — Yelp-like Reviews Platform

Part B — URL-Shortening Service

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