## Problem You are given three tables represented as **2D string arrays** (each row is a record, no headers). You need to produce a mapping from **`userId` → `customerName`** by matching and joining information across tables. ### Table 1: `customers` Each row: `[customerName, email, productName, quantity]` - `quantity` is an integer in string form. - Assumption: **each customer buys only one type of product** (i.e., one `productName` per customer). ### Table 2: `orders` Each row: `[userId, email, orderTotal]` - `orderTotal` is a number in string form (integer or decimal). - `email` **may be null** (or an empty string, depending on how the input is represented). ### Table 3: `products` Each row: `[productName, unitPrice]` - `unitPrice` is a number in string form. ## Matching / Join requirement For each `order` record, identify which customer placed it, then output `userId -> customerName`. Use these matching rules: 1. If `orders.email` is present (non-null/non-empty), match the customer by **email**. 2. If `orders.email` is missing, match by using the fact that: - `orderTotal = quantity * unitPrice` for the customer’s purchased product. - Use `customers.productName` joined to `products.productName` to get `unitPrice`. ## Output Return a mapping/dictionary from `userId` to `customerName` for all orders. ## Assumptions / Edge cases - If multiple customers could match an order (e.g., same computed total), specify and implement a deterministic tie-breaker (e.g., pick lexicographically smallest name) or return all candidates—clarify with the interviewer. - Assume inputs are well-formed aside from possible null/empty emails.