Design top-K frequency store for varying workloads

### Scenario You need to design an in-memory component that tracks how often each key appears in a stream of events. The component must support these operations: - `record(key)`: increment the count for `key` by 1 (insert `key` if not present). - `topK(k)`: return the `k` keys with the highest counts so far (order among them does not matter). Assume: - There can be up to `N` distinct keys. - Operations happen online as the stream arrives. ### Task Describe how you would implement this component under two different workload patterns: 1. **Read-heavy**: there are many more `topK(k)` calls than `record(key)` calls. 2. **Write-heavy**: there are many more `record(key)` calls than `topK(k)` calls. For each case, specify: - The main data structures you would use. - Time complexity of `record` and `topK`. - Space complexity. - Why your design is appropriate for that workload (the trade-offs you’re making).