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Implement a rate-limiter to control API requests per user.

General/Otherhard0.4 min readPremium

Rate limit = restrict requests per user per window. ALGORITHMS: (1) Token bucket—refill rate, consume per request; smooths bursts. (2) Sliding window—exact count in window; more accurate, more state. (3) Fixed window—simple but burst at boundaries. WHY: Protect backends, ensure...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
243
questions in General/Other
Difficulty Split
151E|43M|49H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Disney+ Hotstar
Key Concepts Tested
partitionwindow

Why This Question Matters

This hard-level General/Other question appears frequently in data engineering interviews at companies like Disney+ Hotstar. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (partition, window) will help you answer variations of this question confidently.

How to Approach This

This is a senior-level question that tests architectural thinking. Lead with the high-level design, then drill into specifics. Discuss trade-offs explicitly - there is rarely one correct answer. Show awareness of scale, fault tolerance, and operational complexity.

Expert Answer
83 words

Rate limit = restrict requests per user per window. ALGORITHMS: (1) Token bucket—refill rate, consume per request; smooths bursts. (2) Sliding window—exact count in window; more accurate, more state. (3) Fixed window—simple but burst at boundaries. WHY: Protect backends, ensure fair usage, cost control. IMPLEMENTATION: Redis for distributed state—INCR + EXPIRE (fixed); Lua script (sliding). SCALABILITY: Redis cluster for high throughput; per-user keys can cause hot partitions—shard by user_id hash. COST: Redis memory scales with users × window; consider in-memory for single-node APIs.

The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations covering performance optimization and real-world examples.

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According to DataEngPrep.tech, this is one of the most frequently asked General/Other interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.

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