返回介绍

solution / 1100-1199 / 1158.Market Analysis I / README_EN

发布于 2024-06-17 01:03:22 字数 3971 浏览 0 评论 0 收藏 0

1158. Market Analysis I

中文文档

Description

Table: Users

+----------------+---------+
| Column Name  | Type  |
+----------------+---------+
| user_id    | int   |
| join_date    | date  |
| favorite_brand | varchar |
+----------------+---------+
user_id is the primary key (column with unique values) of this table.
This table has the info of the users of an online shopping website where users can sell and buy items.

 

Table: Orders

+---------------+---------+
| Column Name   | Type  |
+---------------+---------+
| order_id    | int   |
| order_date  | date  |
| item_id     | int   |
| buyer_id    | int   |
| seller_id   | int   |
+---------------+---------+
order_id is the primary key (column with unique values) of this table.
item_id is a foreign key (reference column) to the Items table.
buyer_id and seller_id are foreign keys to the Users table.

 

Table: Items

+---------------+---------+
| Column Name   | Type  |
+---------------+---------+
| item_id     | int   |
| item_brand  | varchar |
+---------------+---------+
item_id is the primary key (column with unique values) of this table.

 

Write a solution to find for each user, the join date and the number of orders they made as a buyer in 2019.

Return the result table in any order.

The result format is in the following example.

 

Example 1:

Input: 
Users table:
+---------+------------+----------------+
| user_id | join_date  | favorite_brand |
+---------+------------+----------------+
| 1     | 2018-01-01 | Lenovo     |
| 2     | 2018-02-09 | Samsung    |
| 3     | 2018-01-19 | LG       |
| 4     | 2018-05-21 | HP       |
+---------+------------+----------------+
Orders table:
+----------+------------+---------+----------+-----------+
| order_id | order_date | item_id | buyer_id | seller_id |
+----------+------------+---------+----------+-----------+
| 1    | 2019-08-01 | 4     | 1    | 2     |
| 2    | 2018-08-02 | 2     | 1    | 3     |
| 3    | 2019-08-03 | 3     | 2    | 3     |
| 4    | 2018-08-04 | 1     | 4    | 2     |
| 5    | 2018-08-04 | 1     | 3    | 4     |
| 6    | 2019-08-05 | 2     | 2    | 4     |
+----------+------------+---------+----------+-----------+
Items table:
+---------+------------+
| item_id | item_brand |
+---------+------------+
| 1     | Samsung  |
| 2     | Lenovo   |
| 3     | LG     |
| 4     | HP     |
+---------+------------+
Output: 
+-----------+------------+----------------+
| buyer_id  | join_date  | orders_in_2019 |
+-----------+------------+----------------+
| 1     | 2018-01-01 | 1        |
| 2     | 2018-02-09 | 2        |
| 3     | 2018-01-19 | 0        |
| 4     | 2018-05-21 | 0        |
+-----------+------------+----------------+

Solutions

Solution 1

# Write your MySQL query statement below
SELECT
  u.user_id AS buyer_id,
  u.join_date,
  COUNT(order_id) AS orders_in_2019
FROM
  Users AS u
  LEFT JOIN Orders AS o ON u.user_id = o.buyer_id AND YEAR(order_date) = 2019
GROUP BY user_id;

Solution 2

# Write your MySQL query statement below
SELECT
  user_id AS buyer_id,
  join_date,
  IFNULL(SUM(YEAR(order_date) = 2019), 0) AS orders_in_2019
FROM
  Users AS u
  LEFT JOIN Orders AS o ON u.user_id = buyer_id
GROUP BY 1;

如果你对这篇内容有疑问,欢迎到本站社区发帖提问 参与讨论,获取更多帮助,或者扫码二维码加入 Web 技术交流群。

扫码二维码加入Web技术交流群

发布评论

需要 登录 才能够评论, 你可以免费 注册 一个本站的账号。
列表为空,暂无数据
    我们使用 Cookies 和其他技术来定制您的体验包括您的登录状态等。通过阅读我们的 隐私政策 了解更多相关信息。 单击 接受 或继续使用网站,即表示您同意使用 Cookies 和您的相关数据。
    原文