I started by sketching out a state machine in my head and that was probably the right instinct, but I got sidetracked thinking about data structures before I'd even nailed down the core logic.
Clarify the pay model and event semantics first, then outline a stateful streaming approach that processes events in order, computes per-delivery pay, and applies the shift-level minimum guarantee. Discuss trade-offs between real-time and batch processing, and how to handle edge cases like cancellations and late events.
Pro tip: Emphasize idempotency and exactly-once processing to avoid double-paying drivers, and mention that the minimum guarantee should be applied only after aggregating all deliveries in the shift.
Ask about the exact pay formula, event ordering guarantees, and how cancellations affect pay. Confirm whether the minimum guarantee is per shift or per delivery.
Identify the state needed: current shift, active delivery, accumulated pay components. Process events in timestamp order, updating state and computing pay upon dropoff or cancel.
For each completed delivery, calculate base pay, mileage pay, time pay, and tips. Sum these to get delivery pay. Track total shift pay.
At shift_end, compare total shift pay to the minimum guarantee. If total pay is less, adjust to the guarantee amount.
Talk about handling out-of-order events, late data, and scalability. Consider batch vs. streaming, and how to ensure correctness with retries.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.