Mysql十题

181. 超过经理收入的员工

表:Employee 

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| id          | int     |
| name        | varchar |
| salary      | int     |
| managerId   | int     |
+-------------+---------+
Id是该表的主键。
该表的每一行都表示雇员的ID、姓名、工资和经理的ID。

 

编写一个SQL查询来查找收入比经理高的员工。

任意顺序 返回结果表。

查询结果格式如下所示。

 

示例 1:

输入: 
Employee 表:
+----+-------+--------+-----------+
| id | name  | salary | managerId |
+----+-------+--------+-----------+
| 1  | Joe   | 70000  | 3         |
| 2  | Henry | 80000  | 4         |
| 3  | Sam   | 60000  | Null      |
| 4  | Max   | 90000  | Null      |
+----+-------+--------+-----------+
输出: 
+----------+
| Employee |
+----------+
| Joe      |
+----------+
解释: Joe 是唯一挣得比经理多的雇员。
SELECT
    a.name AS Employee
FROM
    Employee a,
    Employee b
WHERE
    a.managerId = b.id 
        AND a.salary > b.salary;

184. 部门工资最高的员工

表: Employee

+--------------+---------+
| 列名          | 类型    |
+--------------+---------+
| id           | int     |
| name         | varchar |
| salary       | int     |
| departmentId | int     |
+--------------+---------+
id是此表的主键列。
departmentId是Department表中ID的外键。
此表的每一行都表示员工的ID、姓名和工资。它还包含他们所在部门的ID。

 

表: Department

+-------------+---------+
| 列名         | 类型    |
+-------------+---------+
| id          | int     |
| name        | varchar |
+-------------+---------+
id是此表的主键列。
此表的每一行都表示一个部门的ID及其名称。

 

编写SQL查询以查找每个部门中薪资最高的员工。
任意顺序 返回结果表。
查询结果格式如下例所示。

 

示例 1:

输入:
Employee 表:
+----+-------+--------+--------------+
| id | name  | salary | departmentId |
+----+-------+--------+--------------+
| 1  | Joe   | 70000  | 1            |
| 2  | Jim   | 90000  | 1            |
| 3  | Henry | 80000  | 2            |
| 4  | Sam   | 60000  | 2            |
| 5  | Max   | 90000  | 1            |
+----+-------+--------+--------------+
Department 表:
+----+-------+
| id | name  |
+----+-------+
| 1  | IT    |
| 2  | Sales |
+----+-------+
输出:
+------------+----------+--------+
| Department | Employee | Salary |
+------------+----------+--------+
| IT         | Jim      | 90000  |
| Sales      | Henry    | 80000  |
| IT         | Max      | 90000  |
+------------+----------+--------+
解释:Max 和 Jim 在 IT 部门的工资都是最高的,Henry 在销售部的工资最高。
select Department.name as Department,Employee.name as Employee,salary
from Employee
left join Department on Employee.departmentId = Department.id
where (Employee.departmentId,salary)  in

    (select departmentId,max(salary)
    from Employee
    group by departmentId)

 

511. 游戏玩法分析 I

活动表 Activity

+--------------+---------+
| Column Name  | Type    |
+--------------+---------+
| player_id    | int     |
| device_id    | int     |
| event_date   | date    |
| games_played | int     |
+--------------+---------+
表的主键是 (player_id, event_date)。
这张表展示了一些游戏玩家在游戏平台上的行为活动。
每行数据记录了一名玩家在退出平台之前,当天使用同一台设备登录平台后打开的游戏的数目(可能是 0 个)。

 

写一条 SQL 查询语句获取每位玩家 第一次登陆平台的日期

查询结果的格式如下所示:

Activity 表:
+-----------+-----------+------------+--------------+
| player_id | device_id | event_date | games_played |
+-----------+-----------+------------+--------------+
| 1         | 2         | 2016-03-01 | 5            |
| 1         | 2         | 2016-05-02 | 6            |
| 2         | 3         | 2017-06-25 | 1            |
| 3         | 1         | 2016-03-02 | 0            |
| 3         | 4         | 2018-07-03 | 5            |
+-----------+-----------+------------+--------------+

Result 表:
+-----------+-------------+
| player_id | first_login |
+-----------+-------------+
| 1         | 2016-03-01  |
| 2         | 2017-06-25  |
| 3         | 2016-03-02  |
+-----------+-------------+
select player_id, min(event_date) as first_login
from Activity
group by player_id

620. 有趣的电影

某城市开了一家新的电影院,吸引了很多人过来看电影。该电影院特别注意用户体验,专门有个 LED显示板做电影推荐,上面公布着影评和相关电影描述。

作为该电影院的信息部主管,您需要编写一个 SQL查询,找出所有影片描述为 boring (不无聊) 的并且 id 为奇数 的影片,结果请按等级 rating 排列。

 

例如,下表 cinema:

+---------+-----------+--------------+-----------+
|   id    | movie     |  description |  rating   |
+---------+-----------+--------------+-----------+
|   1     | War       |   great 3D   |   8.9     |
|   2     | Science   |   fiction    |   8.5     |
|   3     | irish     |   boring     |   6.2     |
|   4     | Ice song  |   Fantacy    |   8.6     |
|   5     | House card|   Interesting|   9.1     |
+---------+-----------+--------------+-----------+

对于上面的例子,则正确的输出是为:

+---------+-----------+--------------+-----------+
|   id    | movie     |  description |  rating   |
+---------+-----------+--------------+-----------+
|   5     | House card|   Interesting|   9.1     |
|   1     | War       |   great 3D   |   8.9     |
+---------+-----------+--------------+-----------+
select *
from cinema
where description != "boring" and id%2 != 0
order by rating desc

1068. 产品销售分析 I

销售表 Sales

+-------------+-------+
| Column Name | Type  |
+-------------+-------+
| sale_id     | int   |
| product_id  | int   |
| year        | int   |
| quantity    | int   |
| price       | int   |
+-------------+-------+
(sale_id, year) 是销售表 Sales 的主键.
product_id 是关联到产品表 Product 的外键.
注意: price 表示每单位价格

产品表 Product

+--------------+---------+
| Column Name  | Type    |
+--------------+---------+
| product_id   | int     |
| product_name | varchar |
+--------------+---------+
product_id 是表的主键.

 

写一条SQL 查询语句获取 Sales 表中所有产品对应的 产品名称 product_name 以及该产品的所有 售卖年份 year 和 价格 price

查询结果中的顺序无特定要求。

查询结果格式示例如下:

 

Sales 表:
+---------+------------+------+----------+-------+
| sale_id | product_id | year | quantity | price |
+---------+------------+------+----------+-------+ 
| 1       | 100        | 2008 | 10       | 5000  |
| 2       | 100        | 2009 | 12       | 5000  |
| 7       | 200        | 2011 | 15       | 9000  |
+---------+------------+------+----------+-------+

Product 表:
+------------+--------------+
| product_id | product_name |
+------------+--------------+
| 100        | Nokia        |
| 200        | Apple        |
| 300        | Samsung      |
+------------+--------------+

Result 表:
+--------------+-------+-------+
| product_name | year  | price |
+--------------+-------+-------+
| Nokia        | 2008  | 5000  |
| Nokia        | 2009  | 5000  |
| Apple        | 2011  | 9000  |
+--------------+-------+-------+
select p.product_name,s.year,s.price 
from Product p 
left join Sales s on p.product_id=s.product_id 

196. 删除重复的电子邮箱

表: Person

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| id          | int     |
| email       | varchar |
+-------------+---------+
id是该表的主键列。
该表的每一行包含一封电子邮件。电子邮件将不包含大写字母。

 

编写一个 SQL 删除语句删除 所有重复的电子邮件,只保留一个id最小的唯一电子邮件。

任意顺序 返回结果表。 (注意: 仅需要写删除语句,将自动对剩余结果进行查询)

查询结果格式如下所示。

 

 

示例 1:

输入: 
Person 表:
+----+------------------+
| id | email            |
+----+------------------+
| 1  | john@example.com |
| 2  | bob@example.com  |
| 3  | john@example.com |
+----+------------------+
输出: 
+----+------------------+
| id | email            |
+----+------------------+
| 1  | john@example.com |
| 2  | bob@example.com  |
+----+------------------+
解释: john@example.com重复两次。我们保留最小的Id = 1。
delete p1 from Person p1 ,Person p2
where p1.Email =p2.Email and p1.Id > p2.Id

1075. 项目员工 I

项目表 Project: 

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| project_id  | int     |
| employee_id | int     |
+-------------+---------+
主键为 (project_id, employee_id)。
employee_id 是员工表 Employee 表的外键。

员工表 Employee

+------------------+---------+
| Column Name      | Type    |
+------------------+---------+
| employee_id      | int     |
| name             | varchar |
| experience_years | int     |
+------------------+---------+
主键是 employee_id。

 

请写一个 SQL 语句,查询每一个项目中员工的 平均 工作年限,精确到小数点后两位

查询结果的格式如下:

Project 表:
+-------------+-------------+
| project_id  | employee_id |
+-------------+-------------+
| 1           | 1           |
| 1           | 2           |
| 1           | 3           |
| 2           | 1           |
| 2           | 4           |
+-------------+-------------+

Employee 表:
+-------------+--------+------------------+
| employee_id | name   | experience_years |
+-------------+--------+------------------+
| 1           | Khaled | 3                |
| 2           | Ali    | 2                |
| 3           | John   | 1                |
| 4           | Doe    | 2                |
+-------------+--------+------------------+

Result 表:
+-------------+---------------+
| project_id  | average_years |
+-------------+---------------+
| 1           | 2.00          |
| 2           | 2.50          |
+-------------+---------------+
第一个项目中,员工的平均工作年限是 (3 + 2 + 1) / 3 = 2.00;第二个项目中,员工的平均工作年限是 (3 + 2) / 2 = 2.50
select distinct project_id,round(sum(experience_years)/count(Project.employee_id),2) as average_years
from Project 
left join Employee
on Project.employee_id = Employee.employee_id
group by project_id

1141. 查询近30天活跃用户数

活动记录表:Activity

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| user_id       | int     |
| session_id    | int     |
| activity_date | date    |
| activity_type | enum    |
+---------------+---------+
该表是用户在社交网站的活动记录。
该表没有主键,可能包含重复数据。
activity_type 字段为以下四种值 ('open_session', 'end_session', 'scroll_down', 'send_message')。
每个 session_id 只属于一个用户。

 

请写SQL查询出截至 2019-07-27(包含2019-07-27),近 30 天的每日活跃用户数(当天只要有一条活动记录,即为活跃用户)。

任意顺序 返回结果表。

查询结果示例如下。

 

示例 1:

输入:
Activity table:
+---------+------------+---------------+---------------+
| user_id | session_id | activity_date | activity_type |
+---------+------------+---------------+---------------+
| 1       | 1          | 2019-07-20    | open_session  |
| 1       | 1          | 2019-07-20    | scroll_down   |
| 1       | 1          | 2019-07-20    | end_session   |
| 2       | 4          | 2019-07-20    | open_session  |
| 2       | 4          | 2019-07-21    | send_message  |
| 2       | 4          | 2019-07-21    | end_session   |
| 3       | 2          | 2019-07-21    | open_session  |
| 3       | 2          | 2019-07-21    | send_message  |
| 3       | 2          | 2019-07-21    | end_session   |
| 4       | 3          | 2019-06-25    | open_session  |
| 4       | 3          | 2019-06-25    | end_session   |
+---------+------------+---------------+---------------+
输出:
+------------+--------------+ 
| day        | active_users |
+------------+--------------+ 
| 2019-07-20 | 2            |
| 2019-07-21 | 2            |
+------------+--------------+ 
解释:注意非活跃用户的记录不需要展示。
select activity_date as day, count(user_id) as active_users
from
(select distinct user_id,activity_date
from Activity
where activity_date between "2019-06-28" and "2019-07-27") as t 
group by activity_date

# 优质解
# SELECT activity_date AS day,COUNT(DISTINCT user_id) AS active_users
# FROM Activity
# WHERE activity_date BETWEEN '2019-6-28' AND '2019-7-27'
# GROUP BY day;

1179. 重新格式化部门表

部门表 Department

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| id            | int     |
| revenue       | int     |
| month         | varchar |
+---------------+---------+
(id, month) 是表的联合主键。
这个表格有关于每个部门每月收入的信息。
月份(month)可以取下列值 ["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"]。

 

编写一个 SQL 查询来重新格式化表,使得新的表中有一个部门 id 列和一些对应 每个月 的收入(revenue)列。

查询结果格式如下面的示例所示:

Department 表:
+------+---------+-------+
| id   | revenue | month |
+------+---------+-------+
| 1    | 8000    | Jan   |
| 2    | 9000    | Jan   |
| 3    | 10000   | Feb   |
| 1    | 7000    | Feb   |
| 1    | 6000    | Mar   |
+------+---------+-------+

查询得到的结果表:
+------+-------------+-------------+-------------+-----+-------------+
| id   | Jan_Revenue | Feb_Revenue | Mar_Revenue | ... | Dec_Revenue |
+------+-------------+-------------+-------------+-----+-------------+
| 1    | 8000        | 7000        | 6000        | ... | null        |
| 2    | 9000        | null        | null        | ... | null        |
| 3    | null        | 10000       | null        | ... | null        |
+------+-------------+-------------+-------------+-----+-------------+

注意,结果表有 13 列 (1个部门 id 列 + 12个月份的收入列)。
select
    id,
    sum(case month when 'Jan' then revenue else null end) as Jan_Revenue,
    sum(case month when 'Feb' then revenue else null end) as Feb_Revenue,
    sum(case month when 'Mar' then revenue else null end) as Mar_Revenue,
    sum(case month when 'Apr' then revenue else null end) as Apr_Revenue,
    sum(case month when 'May' then revenue else null end) as May_Revenue,
    sum(case month when 'Jun' then revenue else null end) as Jun_Revenue,
    sum(case month when 'Jul' then revenue else null end) as Jul_Revenue,
    sum(case month when 'Aug' then revenue else null end) as Aug_Revenue,
    sum(case month when 'Sep' then revenue else null end) as Sep_Revenue,
    sum(case month when 'Oct' then revenue else null end) as Oct_Revenue,
    sum(case month when 'Nov' then revenue else null end) as Nov_Revenue,
    sum(case month when 'Dec' then revenue else null end) as Dec_Revenue

from Department
group by id

1174. 即时食物配送 II

配送表: Delivery

+-----------------------------+---------+
| Column Name                 | Type    |
+-----------------------------+---------+
| delivery_id                 | int     |
| customer_id                 | int     |
| order_date                  | date    |
| customer_pref_delivery_date | date    |
+-----------------------------+---------+
delivery_id 是表的主键。
该表保存着顾客的食物配送信息,顾客在某个日期下了订单,并指定了一个期望的配送日期(和下单日期相同或者在那之后)。

 

如果顾客期望的配送日期和下单日期相同,则该订单称为 「即时订单」,否则称为「计划订单」。

「首次订单」是顾客最早创建的订单。我们保证一个顾客只会有一个「首次订单」。

写一条 SQL 查询语句获取即时订单在所有用户的首次订单中的比例。保留两位小数。

 

查询结果如下所示:

Delivery 表:
+-------------+-------------+------------+-----------------------------+
| delivery_id | customer_id | order_date | customer_pref_delivery_date |
+-------------+-------------+------------+-----------------------------+
| 1           | 1           | 2019-08-01 | 2019-08-02                  |
| 2           | 2           | 2019-08-02 | 2019-08-02                  |
| 3           | 1           | 2019-08-11 | 2019-08-12                  |
| 4           | 3           | 2019-08-24 | 2019-08-24                  |
| 5           | 3           | 2019-08-21 | 2019-08-22                  |
| 6           | 2           | 2019-08-11 | 2019-08-13                  |
| 7           | 4           | 2019-08-09 | 2019-08-09                  |
+-------------+-------------+------------+-----------------------------+

Result 表:
+----------------------+
| immediate_percentage |
+----------------------+
| 50.00                |
+----------------------+
1 号顾客的 1 号订单是首次订单,并且是计划订单。
2 号顾客的 2 号订单是首次订单,并且是即时订单。
3 号顾客的 5 号订单是首次订单,并且是计划订单。
4 号顾客的 7 号订单是首次订单,并且是即时订单。
因此,一半顾客的首次订单是即时的。
select round (
    sum(order_date = customer_pref_delivery_date) * 100 /
    count(*),
    2
) as immediate_percentage
from Delivery
where (customer_id, order_date) in (
    select customer_id, min(order_date)
    from delivery
    group by customer_id
)

 

posted on 2023-06-29 11:15  HHHuskie  阅读(16)  评论(0编辑  收藏  举报

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