Build a low-latency Search Pipeline
Last updated: November 29, 2025
Quick Overview
Design a low-latency search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Airbnb
November 29, 202510
7
2,351 solved
Design a low-latency search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Airbnb asks this during the Onsite to assess your understanding of the full ML lifecycle. They want to see how you translate a business problem into an ML objective, design the feature pipeline, and plan for model monitoring and retraining.
What the Interviewer Expects
- Design the full ML lifecycle from data collection to model monitoring
- Address cold start, exploration/exploitation, and model freshness
- Discuss multi-objective optimization and ranking systems
- Plan for model debugging, fairness, and bias mitigation
- Design the feature store and training pipeline for scale
- Address model versioning, canary deployments, and rollback strategies
- Discuss the data flywheel and long-term system evolution
Key Topics to Cover
How to Approach This
- Start by clarifying functional and non-functional requirements with the interviewer.
- Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
- Draw a high-level architecture first, then deep dive into 1-2 critical components.
- Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
- Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
- How would you handle the cold start problem?
- How would you ensure fairness and reduce bias in the model?
- How would you run A/B tests on different model versions?
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Requirements
Functional Requirements
- Search Functionality: Users must be able to search for listings based on various filters such as location, price range, amenities, and availability.
- **Real-Time U...
Capacity Estimation
Assuming Airbnb has approximately 6 million listings and anticipates about 1 billion searches per month:
- Daily Searches: 1 billion searches / 30 days = ~33 million searches per day.
- **Peak ...
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