Master Redis Interview: Deep Dive into Architecture, Data Structures, and Performance

PART1 Basics

Redis is a key‑value in‑memory NoSQL database used mainly for caching; interviewers often start with its definition, the BASE theory versus ACID, and expiration policies (timed, periodic, lazy).

PART2 Data Structures

Redis exposes five primary data types—String, List, Hash, Set, Zset—implemented on lower‑level structures such as SDS, ziplist, skiplist, and dict. Detailed explanations cover string storage, hash incremental rehash, skiplist levels, and why Zset combines a dictionary with a skiplist for fast range queries.

PART3 System Resilience

Persistence is achieved via RDB snapshots and AOF logs, with AOF rewrite to prevent file bloat. High availability uses master‑slave replication and Sentinel for automatic failover, selecting a new master based on priority, offset, and runid.

PART4 Performance

Redis runs a single‑threaded reactor model, using efficient I/O multiplexing; since 6.0 a multithreaded I/O layer speeds up network parsing. Memory eviction policies are configurable, and clustering with consistent hashing distributes data across nodes.

PART5 Application Scenarios

Cache‑aside vs read‑through patterns, strategies for cache invalidation, handling cache avalanche with random expiration, preventing cache penetration with Bloom filters, mitigating cache breakdown with hot‑key protection, and using Redis for rate limiting via token‑bucket algorithms.

PART6 Interview Review

The article concludes with a recap of key Redis concepts that frequently appear in backend interviews, emphasizing the importance of understanding data structures, persistence, high availability, and practical usage patterns.