The core routing logic isn't too bad once you break it down: filter unhealthy, sort by distance then name, walk the list for the first one with load under capacity, bump its load.
Start by clarifying the requirements and edge cases, then outline the data structures and algorithm for the ROUTE command. Implement the solution step-by-step, ensuring efficiency and correctness, and finally test with various scenarios.
Pro tip: Mention that you would use a priority queue or sorting by distance to efficiently find the nearest healthy datacenter, and discuss how to handle ties or capacity constraints gracefully.
Ask questions to confirm the expected behavior: what defines 'nearest' (Haversine distance), how capacity is tracked, what happens when no healthy datacenter has capacity, and the format of the sorted list.
Choose appropriate structures to store datacenters (e.g., a list or map) with fields for location, health, capacity, and load. Consider how to efficiently retrieve and update them.
For each ROUTE command, filter healthy datacenters with remaining capacity, compute Haversine distances from the source, sort by distance, select the nearest, increment its load, and return the chosen datacenter and the sorted list.
Address scenarios like no available datacenters, ties in distance, and capacity exhaustion. Ensure the solution returns appropriate errors or messages.
Walk through test cases (e.g., multiple datacenters, toggling health, capacity limits) and discuss potential optimizations like caching distances or using a heap for repeated queries.
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