Clarify the billing rules and edge cases first, then outline a two-pass algorithm: first aggregate usage per user per month and compute each plan's cost, then combine costs proportionally when a user has both plans. Discuss data structures, complexity, and how to handle scale and correctness.
Pro tip: Show you think about real-world billing by mentioning idempotency, auditability, and handling late-arriving records—Stripe cares deeply about correctness and money movement.
Ask about exact rates, subscription fee, threshold definition (input+output tokens?), and how to handle users with zero usage or missing months. Confirm the proportional split rule and rounding.
Group records by user_id and month, summing input_tokens and output_tokens per plan. Use a hash map keyed by (user_id, month) to accumulate totals efficiently.
For pay-as-you-go: cost = input_tokens * input_rate + output_tokens * output_rate. For subscription: cost = flat_fee + max(0, total_tokens - threshold) * pay_as_you_go_rate (using appropriate input/output rates for overage).
If a user has both plans in a month, compute each plan's cost based on its own usage, then split the total proportionally by each plan's usage share (e.g., tokens). Ensure the sum of split costs equals total cost.
Analyze time O(N) and space O(U) where U is unique user-month pairs. Mention handling large datasets via streaming or MapReduce, and ensuring idempotency and audit trails.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.