Table: ProductPurchases +-------------+------+ | Column Name | Type | +-------------+------+ | user_id | int | | product_id | int | | quantity | int | +-------------+------+ (user_id, product_id) is the unique key for this table. Each row represents a purchase of a product by a user in a specific quantity. Table: ProductInfo +-------------+---------+ | Column Name | Type | +-------------+---------+ | product_id | int | | category | varchar | | price | decimal | +-------------+---------+ product_id is the primary key for this table. Each row assigns a category and price to a product. Amazon wants to implement the Customers who bought this also bought... feature based on co-purchase patterns . Write a solution to : Identify distinct product pairs frequently purchased together by the same customers (where product1_id < product2_id ) For each product pair , determine how many customers purchased both products A product pair is considered for recommendation if at least 3 different customers have purchased both products . Return the result table ordered by customer_count in descending order, and in case of a tie, by product1_id in ascending order, and then by product2_id in ascending order . The result format is in the following example. Example: Input: ProductPurchases table: +---------+------------+----------+ | user_id | product_id | quantity | +---------+------------+----------+ | 1 | 101 | 2 | | 1 | 102 | 1 | | 1 | 103 | 3 | | 2 | 101 | 1 | | 2 | 102 | 5 | | 2 | 104 | 1 | | 3 | 101 | 2 | | 3 | 103 | 1 | | 3 | 105 | 4 | | 4 | 101 | 1 | | 4 | 102 | 1 | | 4 | 103 | 2 | | 4 | 104 | 3 | | 5 | 102 | 2 | | 5 | 104 | 1 | +---------+------------+----------+ ProductInfo table: +------------+-------------+-------+ | product_id | category | price | +------------+-------------+-------+ | 101 | Electronics | 100 | | 102 | Books | 20 | | 103 | Clothing | 35 | | 104 | Kitchen | 50 | | 105 | Sports | 75 | +------------+-------------+-------+ Output: +-------------+-------------+-------------------+-------------------+----------------+ | product1_id | product2_id | product1_category | product2_category | customer_count | +-------------+-------------+-------------------+-------------------+----------------+ | 101 | 102 | Electronics | Books | 3 | | 101 | 103 | Electronics | Clothing | 3 | | 102 | 104 | Books | Kitchen | 3 | +-------------+-------------+-------------------+-------------------+----------------+ Explanation: Product pair (101, 102): Purchased by users 1, 2, and 4 (3 customers) Product 101 is in Electronics category Product 102 is in Books category Product pair (101, 103): Purchased by users 1, 3, and 4 (3 customers) Product 101 is in Electronics category Product 103 is in Clothing category Product pair (102, 104): Purchased by users 2, 4, and 5 (3 customers) Product 102 is in Books category Product 104 is in Kitchen category The result is ordered by customer_count in descending order. For pairs with the same customer_count, they are ordered by product1_id and then product2_id in ascending order.