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Interviewer: How to Design a Real-Time Product Search & Personalized Recommendation Engine for High-Scale E-Commerce
8 min read4 days ago
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Today, I want to share an architectural experiences with you that was asked in an interview.
In a modern e-commerce platform, search and recommendation are the dual engines driving conversion rates. If a user searches for a product and experiences a 2-second delay, or if their home feed feels generic and unresponsive to their clicks, you lose them.
In this article, we will dissect how to combine Spring Boot 3+, Spring Cloud, Elasticsearch, Redis, and Kafka to build a high-performance, real-time product search and personalized recommendation system.
I. Business Scenarios and Technical Challenges
Core Business Requirements
- Real-Time Product Search: Millisecond-level responses across massive catalogs containing millions of SKUs.
- Personalized Recommendation: Generating dynamic, context-aware feed updates in real time based on instant user behaviors (clicks, views, adds-to-cart).
- High-Concurrency Handling: Sustaining tens of thousands of requests per second (QPS) during flash sales and peak promotional events.
- Data Consistency…
