Data Structure Selection and Trade Offs Questions

Skill in selecting appropriate data structures and algorithmic approaches for practical problems and performance constraints. Candidates should demonstrate how to choose between arrays lists maps sets trees heaps and specialized structures based on access patterns memory and CPU requirements and concurrency considerations. Coverage includes case based selection for domain specific systems such as games inventory or spatial indexing where structures like quadtrees or spatial hashing are appropriate, and language specific considerations such as value versus reference types or object pooling. Emphasis is on explaining rationale trade offs and expected performance implications in concrete scenarios.

HardSystem Design

65 practiced

Design the ingestion and in-memory index for a time-series database that must handle 1M metric samples per second and support queries for arbitrary time-range scans with sub-second tail latency for recent data. Explain data structures for ingestion buffers, per-metric indexes, chunking, compression, and retention tiers.

HardTechnical

74 practiced

Implement a thread-safe sharded LRU cache capable of holding millions of keys. Describe how you shard (by hash ranges), maintain per-shard LRU, enforce a global capacity, and perform evictions to respect memory limits while minimizing coordination across shards.

HardTechnical

84 practiced

High-frequency allocation servers are experiencing high latency due to GC and malloc overhead. Propose an object pooling or slab allocator design that reduces allocation churn and fragmentation. Explain block sizes, free-list management, per-thread caches, and how to mitigate fragmentation over time.

HardSystem Design

124 practiced

Design a real-time alert deduplication system for thousands of clusters producing millions of alerts per hour. Constraints: memory per processing node limited, deduplicate alerts within 2 minutes per cluster, and preserve low latency. Describe chosen data structures, sharding strategy, and how you handle false positives, expirations, and multi-instance processing.

EasyTechnical

116 practiced

Explain the trade-offs of using a hash map/dictionary for lookup-heavy state in an SRE control-plane component. Cover average/worst-case access time, resizing, memory overhead, collision strategies (chaining vs open addressing), and how load factor affects performance and memory.

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