Design a low-latency search autocomplete system
Reported in Multiverse Computing European engineering loops. System design interview around indexing, ranking, and freshness.
Interview scenario
Context for Multiverse Computing candidates:
Return top query suggestions as user types, with response under 100 ms.
Model answer
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Cover trade-offs, structure, and a concrete example before revealing the baseline response.
How to frame this at Multiverse Computing: Connect your answer to measurable impact, clarity of thought, and trade-offs the team cares about. Below is a strong baseline response you can adapt with your own project examples.
Store prefix index in memory using trie or finite state structure, backed by offline-generated popularity scores from query logs. Query path is read-optimized and served from cache-heavy stateless nodes.
Ranking combines global frequency, user locale, recent trends, and typo tolerance. Apply debounce on client side and throttle server requests per session to control load.
Updates can be near-real-time with mini-batch ingestion every few minutes. Keep stale-safe fallback index so partial pipeline failures do not break core suggestions.
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