Databricks·Software Engineer·Technical Phone Screen·Senior

Senior

Jun 2026

Summary

Databricks SWE interview with a system design coding question that was more nuanced than it looked on the surface. The core task was clean but the rate-tracking piece is where things get interesting.

Questions Asked (1)

Design a key-value store class with put and get methods, plus two methods that return the average number of put and get calls per second over the last 5 minutes. All four operations should run in close to O(1) time.

System DesignAlgorithms & Data StructuresTechnical Trade-offs

Author's notes

The key-value part took me maybe two minutes, then I spent the rest of the time on the rate tracking.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and assumptions, then design a hash map for O(1) put/get and a sliding window with bucketed timestamps for O(1) rate calculations. Discuss trade-offs between exact and approximate rates, and how to handle concurrency and memory.

Pro tip: Mention that using a circular buffer of per-second counters gives O(1) updates and queries, and that you can use a lock-free approach or sharding to handle high concurrency.

1. Clarify Requirements

Ask about expected throughput, concurrency, memory constraints, and whether exact rates are needed or approximations are acceptable.

2. Design Core Data Structures

Use a hash map for key-value storage and a circular buffer (or deque) of per-second counters for tracking put/get calls over the last 5 minutes.

3. Implement Rate Calculation

Maintain a running sum of counts and timestamps; on each operation, update the current second's counter and evict expired buckets to keep O(1) amortized time.

4. Address Concurrency and Edge Cases

Discuss thread-safety using locks or atomic operations, and handle edge cases like empty store, time synchronization, and bucket rollover.

5. Analyze Trade-offs

Compare exact vs. approximate rates, memory usage, and performance under high load; mention alternative approaches like exponential moving averages.

Key Points to Mention

Hash map for O(1) put/get operations
Circular buffer or deque of per-second counters for O(1) rate tracking
Sliding window with timestamps to maintain last 5 minutes
Thread-safety and concurrency considerations (locks, atomics, sharding)
Trade-offs between exact and approximate rate calculations
Memory management and eviction of old data

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.