Skip to content

Latest commit

 

History

History
146 lines (116 loc) · 4.06 KB

File metadata and controls

146 lines (116 loc) · 4.06 KB
comments difficulty edit_url tags
true
Easy
Database

中文文档

Description

Table: Customer

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| customer_id   | int     |
| customer_name | varchar |
+---------------+---------+
customer_id is the column with unique values for this table.
Each row of this table contains the information of each customer in the WebStore.

 

Table: Orders

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| order_id      | int     |
| sale_date     | date    |
| order_cost    | int     |
| customer_id   | int     |
| seller_id     | int     |
+---------------+---------+
order_id is the column with unique values for this table.
Each row of this table contains all orders made in the webstore.
sale_date is the date when the transaction was made between the customer (customer_id) and the seller (seller_id).

 

Table: Seller

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| seller_id     | int     |
| seller_name   | varchar |
+---------------+---------+
seller_id is the column with unique values for this table.
Each row of this table contains the information of each seller.

 

Write a solution to report the names of all sellers who did not make any sales in 2020.

Return the result table ordered by seller_name in ascending order.

The result format is in the following example.

 

Example 1:

Input: 
Customer table:
+--------------+---------------+
| customer_id  | customer_name |
+--------------+---------------+
| 101          | Alice         |
| 102          | Bob           |
| 103          | Charlie       |
+--------------+---------------+
Orders table:
+-------------+------------+--------------+-------------+-------------+
| order_id    | sale_date  | order_cost   | customer_id | seller_id   |
+-------------+------------+--------------+-------------+-------------+
| 1           | 2020-03-01 | 1500         | 101         | 1           |
| 2           | 2020-05-25 | 2400         | 102         | 2           |
| 3           | 2019-05-25 | 800          | 101         | 3           |
| 4           | 2020-09-13 | 1000         | 103         | 2           |
| 5           | 2019-02-11 | 700          | 101         | 2           |
+-------------+------------+--------------+-------------+-------------+
Seller table:
+-------------+-------------+
| seller_id   | seller_name |
+-------------+-------------+
| 1           | Daniel      |
| 2           | Elizabeth   |
| 3           | Frank       |
+-------------+-------------+
Output: 
+-------------+
| seller_name |
+-------------+
| Frank       |
+-------------+
Explanation: 
Daniel made 1 sale in March 2020.
Elizabeth made 2 sales in 2020 and 1 sale in 2019.
Frank made 1 sale in 2019 but no sales in 2020.

Solutions

Solution 1: LEFT JOIN + GROUP BY + FILTER

We can use a left join to join the Seller table with the Orders table on the condition seller_id, and then group by seller_id to count the number of sales for each seller in the year $2020$. Finally, we can filter out the sellers with zero sales.

MySQL

# Write your MySQL query statement below
SELECT seller_name
FROM
    Seller
    LEFT JOIN Orders USING (seller_id)
GROUP BY seller_id
HAVING IFNULL(SUM(YEAR(sale_date) = 2020), 0) = 0
ORDER BY 1;