Table: Customers
+---------------+---------+ | Column Name | Type | +---------------+---------+ | customer_id | int | | name | varchar | | country | varchar | +---------------+---------+ customer_id is the primary key for this table. This table contains information of the customers in the company.
Table: Product
+---------------+---------+ | Column Name | Type | +---------------+---------+ | product_id | int | | description | varchar | | price | int | +---------------+---------+ product_id is the primary key for this table. This table contains information of the products in the company. price is the product cost.
Table: Orders
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| order_id | int |
| customer_id | int |
| product_id | int |
| order_date | date |
| quantity | int |
+---------------+---------+
order_id is the primary key for this table.
This table contains information on customer orders.
customer_id is the id of the customer who bought "quantity" products with id "product_id".
Order_date is the date in format ('YYYY-MM-DD') when the order was shipped.
Write an SQL query to report the customer_id and customer_name of customers who have spent at least $100 in each month of June and July 2020.
Return the result table in any order.
The query result format is in the following example.
Customers+--------------+-----------+-------------+ | customer_id | name | country | +--------------+-----------+-------------+ | 1 | Winston | USA | | 2 | Jonathan | Peru | | 3 | Moustafa | Egypt | +--------------+-----------+-------------+Product+--------------+-------------+-------------+ | product_id | description | price | +--------------+-------------+-------------+ | 10 | LC Phone | 300 | | 20 | LC T-Shirt | 10 | | 30 | LC Book | 45 | | 40 | LC Keychain | 2 | +--------------+-------------+-------------+Orders+--------------+-------------+-------------+-------------+-----------+ | order_id | customer_id | product_id | order_date | quantity | +--------------+-------------+-------------+-------------+-----------+ | 1 | 1 | 10 | 2020-06-10 | 1 | | 2 | 1 | 20 | 2020-07-01 | 1 | | 3 | 1 | 30 | 2020-07-08 | 2 | | 4 | 2 | 10 | 2020-06-15 | 2 | | 5 | 2 | 40 | 2020-07-01 | 10 | | 6 | 3 | 20 | 2020-06-24 | 2 | | 7 | 3 | 30 | 2020-06-25 | 2 | | 9 | 3 | 30 | 2020-05-08 | 3 | +--------------+-------------+-------------+-------------+-----------+ Result table: +--------------+------------+ | customer_id | name | +--------------+------------+ | 1 | Winston | +--------------+------------+ Winston spent $300 (300 * 1) in June and $100 ( 10 * 1 + 45 * 2) in July 2020. Jonathan spent $600 (300 * 2) in June and $20 ( 2 * 10) in July 2020. Moustafa spent $110 (10 * 2 + 45 * 2) in June and $0 in July 2020.
# Write your MySQL query statement below
SELECT
c.customer_id AS CUSTOMER_ID,
c.name AS NAME
FROM
Customers c, Product p, Orders o
WHERE
c.customer_id = o.customer_id
AND p.product_id = o.product_id
GROUP BY c.customer_id
HAVING sum(if(month(o.order_date)=6, price*quantity, 0)) >= 100
AND sum(if(month(o.order_date)=7, price*quantity, 0)) >= 100;