Design a scalable search service with sharding
Quick Overview
This question evaluates understanding of search system architecture, including indexing, querying, and sharding strategies, and measures competency in designing scalable, low-latency data pipelines; it falls under system design and distributed systems and emphasizes practical application-level architecture rather than purely conceptual theory.
Airtable
Jan 22, 2026, 12:00 AM
Software Engineer
Onsite
System Design
13
0
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Technical Design: Search + Sharding Trade-offs
Design a search service that lets users query documents/products with keywords.
Functional requirements
-
GET /search?q=...returns top results ranked by relevance. - Support basic filtering (e.g., category, language, tenant/app id).
- P95 latency target (e.g., < 200 ms) and ability to scale to large corpora.
Non-functional requirements
- Data size grows to billions of docs.
- Frequent reads, continuous ingestion/updates.
- High availability.
Prompt
- Describe how you would implement the core search algorithm at a high level (indexing + querying).
- Propose a sharding strategy for the index.
- Discuss trade-offs: latency, cost, rebalancing, hot keys, consistency, and operational complexity.
No need to write production code, but be concrete about components and data flows.
Solution
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