Your question is Top-N Movie Recommendations. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Design a top-N movie recommendation system based on views collected over the last 7 days.
Asked in the HLD round stage. Explain the data flow, storage and aggregation strategy, recommendation logic, serving architecture, and how you would evaluate correctness and freshness. Clarify whether recommendations are global or personalized, define the meaning of a view, and discuss how the system handles new movies, late events, duplicate events, traffic spikes, and unavailable dependencies. Address both batch and online components, latency and availability expectations, monitoring, and recovery from stale or incorrect aggregates.