intermediateTop 15 System Design Questions
Design Netflix's content recommendation system.
Viewing history: Cassandra — high-write time-series; partition by userId User-item matrix: stored as sparse vectors in Redis or Cassandra Collaborative filtering: offline job (Spark) computes similarity; results in Redis Cache recommendations: SETEX user:{id}:recs 3600 [videoIds] in Redis A/B testing: different recommendation algorithms; Redis for variant assignment Graph-based: Neo4j for person-g
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