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Table: Customers
+---------------+---------+ | Column Name | Type | +---------------+---------+ | customer_id | int | | name | varchar | +---------------+---------+ customer_id is the column with unique values for this table. This table contains information about the customers.
Table: Orders
+---------------+---------+ | Column Name | Type | +---------------+---------+ | order_id | int | | order_date | date | | customer_id | int | | product_id | int | +---------------+---------+ order_id is the column with unique values for this table. This table contains information about the orders made by customer_id. No customer will order the same product more than once in a single day.
Table: Products
+---------------+---------+ | Column Name | Type | +---------------+---------+ | product_id | int | | product_name | varchar | | price | int | +---------------+---------+ product_id is the column with unique values for this table. This table contains information about the products.
Write a solution to find the most frequently ordered product(s) for each customer.
The result table should have the product_id and product_name for each customer_id who ordered at least one order.
Return the result table in any order.
The result format is in the following example.
Example 1:
Input: Customers table: +-------------+-------+ | customer_id | name | +-------------+-------+ | 1 | Alice | | 2 | Bob | | 3 | Tom | | 4 | Jerry | | 5 | John | +-------------+-------+ Orders table: +----------+------------+-------------+------------+ | order_id | order_date | customer_id | product_id | +----------+------------+-------------+------------+ | 1 | 2020-07-31 | 1 | 1 | | 2 | 2020-07-30 | 2 | 2 | | 3 | 2020-08-29 | 3 | 3 | | 4 | 2020-07-29 | 4 | 1 | | 5 | 2020-06-10 | 1 | 2 | | 6 | 2020-08-01 | 2 | 1 | | 7 | 2020-08-01 | 3 | 3 | | 8 | 2020-08-03 | 1 | 2 | | 9 | 2020-08-07 | 2 | 3 | | 10 | 2020-07-15 | 1 | 2 | +----------+------------+-------------+------------+ Products table: +------------+--------------+-------+ | product_id | product_name | price | +------------+--------------+-------+ | 1 | keyboard | 120 | | 2 | mouse | 80 | | 3 | screen | 600 | | 4 | hard disk | 450 | +------------+--------------+-------+ Output: +-------------+------------+--------------+ | customer_id | product_id | product_name | +-------------+------------+--------------+ | 1 | 2 | mouse | | 2 | 1 | keyboard | | 2 | 2 | mouse | | 2 | 3 | screen | | 3 | 3 | screen | | 4 | 1 | keyboard | +-------------+------------+--------------+ Explanation: Alice (customer 1) ordered the mouse three times and the keyboard one time, so the mouse is the most frequently ordered product for them. Bob (customer 2) ordered the keyboard, the mouse, and the screen one time, so those are the most frequently ordered products for them. Tom (customer 3) only ordered the screen (two times), so that is the most frequently ordered product for them. Jerry (customer 4) only ordered the keyboard (one time), so that is the most frequently ordered product for them. John (customer 5) did not order anything, so we do not include them in the result table.
We group the Orders table by customer_id and product_id, and then use the window function rank(), which assigns a rank to each product_id in each customer_id group based on its frequency in descending order. Finally, we select the product_id with a rank of customer_id, which is the most frequently ordered product for that customer_id.
# Write your MySQL query statement below
WITH
T AS (
SELECT
customer_id,
product_id,
RANK() OVER (
PARTITION BY customer_id
ORDER BY COUNT(1) DESC
) AS rk
FROM Orders
GROUP BY 1, 2
)
SELECT customer_id, product_id, product_name
FROM
T
JOIN Products USING (product_id)
WHERE rk = 1;