Design a Search Autocomplete System at TikTok Scale
Last updated: March 3, 2025
Quick Overview
Build typeahead suggestions with prefix matching, personalization, trending detection, and sub-100ms latency for billions of daily queries.
ByteDance
System Design
Software Engineer
ByteDance
March 3, 2025Software Engineer
System Design Round
System Design
Medium
9
3
4,297 solved
Build typeahead suggestions with prefix matching, personalization, trending detection, and sub-100ms latency for billions of daily queries.
Standard but scaled to ByteDance's volume. Tests data structure choice and ranking under tight latency constraints.
What the Interviewer Expects
- Design efficient prefix matching with tries or inverted indexes
- Implement trending query detection
- Add personalization based on user history
- Meet sub-100ms P99 latency
- Handle offensive query filtering
Key Topics to Cover
Trie data structures
Prefix matching
Trending detection
Personalization
Low-latency serving
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 do you handle multi-language autocomplete?
- How do you detect and suppress dangerous search suggestions?
- What is your cold-start strategy for new users?
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Practice System Design ProblemsSample Answer
Requirements
- Functional Requirements:
- Provide typeahead suggestions for user queries using prefix matching.
- Implement personalization based on user search history and preferences.
- Detect and s...
Capacity Estimation
- User Base: Assume TikTok has 1 billion active users.
- Queries per User: Let's estimate an average of 10 search queries per user per day.
- Total Queries: 1 billion users * 10 queries/us...
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