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.

EasyTechnical

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Explain amortized complexity with examples. For SRE, why does vector/array append typically behave O(1) amortized rather than O(n)? How does resizing strategy (factor 2 vs 1.5) impact memory and performance in long-running services?

MediumTechnical

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Design an in-memory prefix index for fast lookup of hostnames by prefix (autocomplete) for an SRE UI. Consider tries, compressed radix trees, and a sorted array with binary search. Discuss trade-offs in memory, construction time, incremental updates, and typical query performance.

HardTechnical

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A telemetry collector in a garbage-collected language suffers from GC pauses due to many short-lived allocations. Propose concrete memory-layout and data-structure changes to reduce GC pressure: consider value vs reference types (language permitting), object pooling, slab allocation, and off-heap buffers. Explain the trade-offs and fragmentation risks.

HardTechnical

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For near-real-time anomaly detection on metric streams with sub-second latency, choose data structures for sliding windows, feature aggregation, and a lightweight in-memory feature store. Discuss memory per-stream, approximate vs exact aggregation, and trade-offs between CPU and memory for detection accuracy.

EasyTechnical

0 practiced

When storing telemetry samples for high-throughput ingestion, explain the trade-offs between 'array of structs' (AoS) vs 'struct of arrays' (SoA). Discuss cache locality, vectorized operations, and serialization costs for SRE telemetry pipelines.

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