Design a Top-K Ranking Service
Company: LinkedIn
Role: Software Engineer
Category: System Design
Difficulty: easy
Interview Round: Onsite
Design a service that returns the top K most frequent items for a configurable time window, such as the top 10 search queries in the last hour or the top 100 products in the last day. Discuss APIs, write and read paths, data storage, exact versus approximate counting, streaming updates, sharding, caching, fault tolerance, and how you would keep results fresh under high traffic.
Quick Answer: This question evaluates a candidate's ability to design scalable, real-time Top-K ranking services, testing competencies in distributed systems, streaming analytics, data storage, caching, sharding, and fault tolerance within the System Design category.