Design KV store with sliding-window QPS metrics

Problem

Design an in-memory key–value store that supports basic operations and can report the average operation load over a recent time window.

Functional requirements

1. KV operations
   • PUT(key, value) stores/overwrites a value.
   • GET(key) retrieves the value (or null /not found).
2. Load/throughput metric query
   • Provide a function that can answer, for a given time window (e.g., the last 10 minutes ):
     • Average GETs per second during that window
     • Average PUTs per second during that window
   • Example query: “In the past 10 minutes, what is the average GET QPS and PUT QPS?”

Clarifications to resolve with the interviewer (state assumptions if not provided)

• Is the window always “last X” (sliding window) vs. “between start/end timestamps”? Assume sliding window: last X .
• Maximum window size / retention (e.g., up to 1 year). Assume queries can be up to 1 year .
• Exactness vs approximation. Assume exact counts are preferred if feasible.
• Concurrency expectations. Assume multi-threaded callers.

Non-functional goals

• KV operations should be low latency.
• Metric queries should be efficient for common windows (minutes/hours) and not require scanning raw logs.
• Memory usage should be bounded given a maximum retention.