Compute prices, distances, and Top-K for orders

Q: Compute prices, distances, and Top-K for orders

This question evaluates algorithmic problem solving and data-structure design for spatial queries, price lookup, time-windowed revenue aggregation, and Top-K computation, including reasoning about tie-breaking and computational complexity.

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Question

Build functions for a food‑delivery analytics module. Data:

Restaurants: id, (x, y) location, menu mapping item -> price.
Orders: id, restaurantId, timestamp (Unix ms), line items: (item, quantity). Tasks: (a) Given the user's (x, y) and a target item, return the restaurant (s) offering the lowest price for that item and, among ties, the nearest by Euclidean distance (return id and distance). (b) For a time window [start, end), compute total revenue, order count, and average order value. (c) For a time window [start, end), return Top K orders by total price (id, total) and Top K items by quantity sold (item, quantity). Specify tie‑breaking rules, chosen data structures, and complexity.

Compute prices, distances, and Top-K for orders

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