Trending Topics / Top-K Service — Simple

Problem statement (interviewer prompt)

Design a real-time "trending topics" / top-K hashtags service for Twitter-scale traffic. Identify the top 10 + top 100 hashtags over a sliding 5-minute / 1-hour / 1-day window, with bounded memory, using probabilistic structures (CMS + heap or Space-Saving).

flowchart LR
  E[[Event stream]]
  CMS[Count-Min Sketch]
  HEAP[Top-K heap]
  API[Top-K API]
  E --> CMS --> HEAP --> API

    classDef client fill:#dbeafe,stroke:#1e40af,stroke-width:1px,color:#0f172a;
    classDef edge fill:#cffafe,stroke:#0e7490,stroke-width:1px,color:#0f172a;
    classDef service fill:#fef3c7,stroke:#92400e,stroke-width:1px,color:#0f172a;
    classDef datastore fill:#fee2e2,stroke:#991b1b,stroke-width:1px,color:#0f172a;
    classDef cache fill:#fed7aa,stroke:#9a3412,stroke-width:1px,color:#0f172a;
    classDef queue fill:#ede9fe,stroke:#5b21b6,stroke-width:1px,color:#0f172a;
    classDef compute fill:#d1fae5,stroke:#065f46,stroke-width:1px,color:#0f172a;
    classDef storage fill:#e5e7eb,stroke:#374151,stroke-width:1px,color:#0f172a;
    classDef external fill:#fce7f3,stroke:#9d174d,stroke-width:1px,color:#0f172a;
    classDef obs fill:#f3e8ff,stroke:#6b21a8,stroke-width:1px,color:#0f172a;
    class CMS,HEAP,API service;
    class E queue;