1

leetcode考试题

 

 考试题1    262. 行程和用户  leetcode

 

 

+-------------+----------+
| Column Name | Type     |
+-------------+----------+
| id          | int      |
| client_id   | int      |
| driver_id   | int      |
| city_id     | int      |
| status      | enum     |
| request_at  | varchar  |     
+-------------+----------+
id 是这张表的主键(具有唯一值的列)。
这张表中存所有出租车的行程信息。每段行程有唯一 id ,其中 client_id 和 driver_id 是 Users 表中 users_id 的外键。
status 是一个表示行程状态的枚举类型,枚举成员为(‘completed’, ‘cancelled_by_driver’, ‘cancelled_by_client’) 。

 

表:Users

+-------------+----------+
| Column Name | Type     |
+-------------+----------+
| users_id    | int      |
| banned      | enum     |
| role        | enum     |
+-------------+----------+
users_id 是这张表的主键(具有唯一值的列)。
这张表中存所有用户,每个用户都有一个唯一的 users_id ,role 是一个表示用户身份的枚举类型,枚举成员为 (‘client’, ‘driver’, ‘partner’) 。
banned 是一个表示用户是否被禁止的枚举类型,枚举成员为 (‘Yes’, ‘No’) 。

 

取消率 的计算方式如下:(被司机或乘客取消的非禁止用户生成的订单数量) / (非禁止用户生成的订单总数)。

编写解决方案找出 "2013-10-01" 至 "2013-10-03" 期间非禁止用户(乘客和司机都必须未被禁止)的取消率。非禁止用户即 banned 为 No 的用户,禁止用户即 banned 为 Yes 的用户。其中取消率 Cancellation Rate 需要四舍五入保留 两位小数

返回结果表中的数据 无顺序要求

结果格式如下例所示。

 

示例 1:

输入: 
Trips 表:
+----+-----------+-----------+---------+---------------------+------------+
| id | client_id | driver_id | city_id | status              | request_at |
+----+-----------+-----------+---------+---------------------+------------+
| 1  | 1         | 10        | 1       | completed           | 2013-10-01 |
| 2  | 2         | 11        | 1       | cancelled_by_driver | 2013-10-01 |
| 3  | 3         | 12        | 6       | completed           | 2013-10-01 |
| 4  | 4         | 13        | 6       | cancelled_by_client | 2013-10-01 |
| 5  | 1         | 10        | 1       | completed           | 2013-10-02 |
| 6  | 2         | 11        | 6       | completed           | 2013-10-02 |
| 7  | 3         | 12        | 6       | completed           | 2013-10-02 |
| 8  | 2         | 12        | 12      | completed           | 2013-10-03 |
| 9  | 3         | 10        | 12      | completed           | 2013-10-03 |
| 10 | 4         | 13        | 12      | cancelled_by_driver | 2013-10-03 |
+----+-----------+-----------+---------+---------------------+------------+
Users 表:
+----------+--------+--------+
| users_id | banned | role   |
+----------+--------+--------+
| 1        | No     | client |
| 2        | Yes    | client |
| 3        | No     | client |
| 4        | No     | client |
| 10       | No     | driver |
| 11       | No     | driver |
| 12       | No     | driver |
| 13       | No     | driver |
+----------+--------+--------+
输出:
+------------+-------------------+
| Day        | Cancellation Rate |
+------------+-------------------+
| 2013-10-01 | 0.33              |
| 2013-10-02 | 0.00              |
| 2013-10-03 | 0.50              |
+------------+-------------------+
解释:
2013-10-01:
  - 共有 4 条请求,其中 2 条取消。
  - 然而,id=2 的请求是由禁止用户(user_id=2)发出的,所以计算时应当忽略它。
  - 因此,总共有 3 条非禁止请求参与计算,其中 1 条取消。
  - 取消率为 (1 / 3) = 0.33
2013-10-02:
  - 共有 3 条请求,其中 0 条取消。
  - 然而,id=6 的请求是由禁止用户发出的,所以计算时应当忽略它。
  - 因此,总共有 2 条非禁止请求参与计算,其中 0 条取消。
  - 取消率为 (0 / 2) = 0.00
2013-10-03:
  - 共有 3 条请求,其中 1 条取消。
  - 然而,id=8 的请求是由禁止用户发出的,所以计算时应当忽略它。
  - 因此,总共有 2 条非禁止请求参与计算,其中 1 条取消。
  - 取消率为 (1 / 2) = 0.50



解答:
# Write your MySQL query statement below #对Trips表和Users表连接,连接条件是行程对应的乘客非禁止且司机非禁止 #筛选订单日期在目标日期之间(BETWEEN AND) #用日期进行分组(GROUP BY) #分别统计所有订单数和被取消的订单数,其中取消订单数用一个bool条件来得到0或1,再用avg求均值 #对订单取消率保留两位小数,对输出列名改名。(round) SELECT Request_at 'Day', round(avg(Status!='completed'), 2) 'Cancellation Rate' FROM Trips t JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No') JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No') WHERE Request_at BETWEEN '2013-10-01' AND '2013-10-03' GROUP BY Request_at;# Write your MySQL query statement below #对Trips表和Users表连接,连接条件是行程对应的乘客非禁止且司机非禁止 #筛选订单日期在目标日期之间(BETWEEN AND) #用日期进行分组(GROUP BY) #分别统计所有订单数和被取消的订单数,其中取消订单数用一个bool条件来得到0或1,再用avg求均值 #对订单取消率保留两位小数,对输出列名改名。(round) SELECT Request_at 'Day', round(avg(Status!='completed'), 2) 'Cancellation Rate' FROM Trips t JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No') JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No') WHERE Request_at BETWEEN '2013-10-01' AND '2013-10-03' GROUP BY Request_at;# Write your MySQL query statement below #对Trips表和Users表连接,连接条件是行程对应的乘客非禁止且司机非禁止 #筛选订单日期在目标日期之间(BETWEEN AND) #用日期进行分组(GROUP BY) #分别统计所有订单数和被取消的订单数,其中取消订单数用一个bool条件来得到0或1,再用avg求均值 #对订单取消率保留两位小数,对输出列名改名。(round) SELECT Request_at 'Day', round(avg(Status!='completed'), 2) 'Cancellation Rate' FROM Trips t JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No') JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No') WHERE Request_at BETWEEN '2013-10-01' AND '2013-10-03' GROUP BY Request_at;# Write your MySQL query statement below #对Trips表和Users表连接,连接条件是行程对应的乘客非禁止且司机非禁止 #筛选订单日期在目标日期之间(BETWEEN AND) #用日期进行分组(GROUP BY) #分别统计所有订单数和被取消的订单数,其中取消订单数用一个bool条件来得到0或1,再用avg求均值 #对订单取消率保留两位小数,对输出列名改名。(round) SELECT Request_at 'Day', round(avg(Status!='completed'), 2) 'Cancellation Rate' FROM Trips t JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No') JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No') WHERE Request_at BETWEEN '2013-10-01' AND '2013-10-03' GROUP BY Request_at;# Write your MySQL query statement below #对Trips表和Users表连接,连接条件是行程对应的乘客非禁止且司机非禁止 #筛选订单日期在目标日期之间(BETWEEN AND) #用日期进行分组(GROUP BY) #分别统计所有订单数和被取消的订单数,其中取消订单数用一个bool条件来得到0或1,再用avg求均值 #对订单取消率保留两位小数,对输出列名改名。(round) SELECT Request_at 'Day', round(avg(Status!='completed'), 2) 'Cancellation Rate' FROM Trips t JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No') JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No') WHERE Request_at BETWEEN '2013-10-01' AND '2013-10-03' GROUP BY Request_at;

 

SELECT
    Request_at 'Day', 
	round ( sum(case when  status != 'completed' then 1 else 0 end  ) /count(1) ,2)  'Cancellation Rate'
FROM Trips t 
    JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No')
    JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No')
WHERE	
    Request_at BETWEEN '2013-10-01' AND '2013-10-03'
GROUP BY 
    Request_at;
 
 

#对Trips表和Users表连接,连接条件是行程对应的乘客非禁止且司机非禁止
#筛选订单日期在目标日期之间(BETWEEN AND)
#用日期进行分组(GROUP BY)
#分别统计所有订单数和被取消的订单数,其中取消订单数用一个bool条件来得到0或1,再用avg求均值
#对订单取消率保留两位小数,对输出列名改名。(round)

SELECT
    Request_at 'Day', round(avg(Status!='completed'), 2) 'Cancellation Rate'
FROM Trips t
    JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No')
    JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No')
WHERE    
    Request_at BETWEEN '2013-10-01' AND '2013-10-03'
GROUP BY
    Request_at;


# Write your MySQL query statement below #对Trips表和Users表连接,连接条件是行程对应的乘客非禁止且司机非禁止 #筛选订单日期在目标日期之间(BETWEEN AND) #用日期进行分组(GROUP BY) #分别统计所有订单数和被取消的订单数,其中取消订单数用一个bool条件来得到0或1,再用avg求均值 #对订单取消率保留两位小数,对输出列名改名。(round) SELECT Request_at 'Day', round(avg(Status!='completed'), 2) 'Cancellation Rate' FROM Trips t JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No') JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No') WHERE Request_at BETWEEN '2013-10-01' AND '2013-10-03' GROUP BY Request_at;# Write your MySQL query statement below #对Trips表和Users表连接,连接条件是行程对应的乘客非禁止且司机非禁止 #筛选订单日期在目标日期之间(BETWEEN AND) #用日期进行分组(GROUP BY) #分别统计所有订单数和被取消的订单数,其中取消订单数用一个bool条件来得到0或1,再用avg求均值 #对订单取消率保留两位小数,对输出列名改名。(round) SELECT Request_at 'Day', round(avg(Status!='completed'), 2) 'Cancellation Rate' FROM Trips t JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No') JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No') WHERE Request_at BETWEEN '2013-10-01' AND '2013-10-03' GROUP BY Request_at;

SELECT Request_at 'Day', round ( sum(case when status != 'completed' then 1 else 0 end ) /count(1) ,2) 'Cancellation Rate' FROM Trips t JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No') JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No') WHERE Request_at BETWEEN '2013-10-01' AND '2013-10-03' GROUP BY Request_at; 方法1 如上 方法2 如下 # Write your MySQL query statement below #对Trips表和Users表连接,连接条件是行程对应的乘客非禁止且司机非禁止 #筛选订单日期在目标日期之间(BETWEEN AND) #用日期进行分组(GROUP BY) #分别统计所有订单数和被取消的订单数,其中取消订单数用一个bool条件来得到0或1,再用avg求均值 #对订单取消率保留两位小数,对输出列名改名。(round) SELECT Request_at 'Day', round(avg(Status!='completed'), 2) 'Cancellation Rate' FROM Trips t JOIN Users u1 ON (t.Client_id = u1.Users_id AND u1.Banned = 'No') JOIN Users u2 ON (t.Driver_id = u2.Users_id AND u2.Banned = 'No') WHERE Request_at BETWEEN '2013-10-01' AND '2013-10-03' GROUP BY Request_at;

avg(Status!='completed') 是一个 SQL 表达式,用于计算布尔条件的平均值。在这个表达式中:

  • Status != 'completed' 是一个布尔条件,它返回 TRUEFALSE。在 SQL 中,TRUE 通常被当作 1,FALSE 被当作 0。
  • avg() 函数计算传入表达式的平均值。

所以,avg(Status!='completed') 实际上是计算 Status 列中不等于 'completed' 的记录的比例。例如,如果有 30% 的记录的 Status 不是 'completed',那么结果就是 0.3。

 

考试 题2 SQL219 获取员工其当前的薪水比其manager当前薪水还高的相关信息 
描述
有一个,部门关系表dept_emp简况如下:
emp_no
    dept_no 
    from_date 
    to_date
10001     d001
    1986-06-26     9999-01-01
10002     d001
    1996-08-03     9999-01-01

有一个部门经理表dept_manager简况如下:
dept_no 
    emp_no
    from_date 
    to_date
d001
    10002
    1996-08-03     9999-01-01

有一个薪水表salaries简况如下:
emp_no 
    salary
    from_date 
    to_date
10001
    88958     2002-06-22
    9999-01-01
10002
    72527     1996-08-03
    9999-01-01

获取员工其当前的薪水比其manager当前薪水还高的相关信息,
第一列给出员工的emp_no,
第二列给出其manager的manager_no,
第三列给出该员工当前的薪水emp_salary,
第四列给该员工对应的manager当前的薪水manager_salary
以上例子输出如下:
emp_no     manager_no     emp_salary     manager_salary
10001     10002     88958     72527 
View Code
SELECT
    m.emp_no,
    m.manager_no,
    n.salary emp_salary,
    o.salary manager_salary
FROM
    (
        SELECT
            a.emp_no,
            b.emp_no manager_no
        FROM
            dept_emp a
            INNER JOIN dept_manager b ON a.dept_no = b.dept_no
            AND a.emp_no <> b.emp_no
    ) m
    INNER JOIN salaries n ON m.emp_no     = n.emp_no
    INNER JOIN salaries o ON m.manager_no = o.emp_no
where  n.salary emp_salary > o.salary manager_salary
    


**查询员工当前工资表 emp_sal**
select de.emp_no,de.dept_no,s1.salary as emp_salary
    from dept_emp de,salaries s1
    where de.emp_no=s1.emp_no
    and s1.to_date='9999-01-01'
    and de.to_date='9999-01-01'
**查询经理当前工资表mag_sal**
 select dm.emp_no as manager_no,dm.dept_no,s2.salary as manager_salary
    from dept_manager dm,salaries s2
    where dm.emp_no=s2.emp_no
    and s2.to_date='9999-01-01'
    and dm.to_date='9999-01-01'
**联结表emp_sal和表mag_sal,连接条件部门编号相等,要求:员工工资>经理工资**
select emp_sal.emp_no,mag_sal.manager_no,
emp_sal.emp_salary,mag_sal.manager_salary
from (
    select de.emp_no,de.dept_no,s1.salary as emp_salary
    from dept_emp de,salaries s1
    where de.emp_no=s1.emp_no
    and s1.to_date='9999-01-01'
    and de.to_date='9999-01-01'
)as emp_sal
inner join(
    select dm.emp_no as manager_no,dm.dept_no,s2.salary as manager_salary
    from dept_manager dm,salaries s2
    where dm.emp_no=s2.emp_no
    and s2.to_date='9999-01-01'
    and dm.to_date='9999-01-01'
)as mag_sal
on emp_sal.dept_no=mag_sal.dept_no
where mag_sal.manager_salary<emp_sal.emp_salary;

 

 180. 连续出现的数字

 

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| id          | int     |
| num         | varchar |
+-------------+---------+
在 SQL 中,id 是该表的主键。
id 是一个自增列。

 

找出所有至少连续出现三次的数字。

返回的结果表中的数据可以按 任意顺序 排列。

结果格式如下面的例子所示:

 

示例 1:

输入:
Logs 表:
+----+-----+
| id | num |
+----+-----+
| 1  | 1   |
| 2  | 1   |
| 3  | 1   |
| 4  | 2   |
| 5  | 1   |
| 6  | 2   |
| 7  | 2   |
+----+-----+
输出:
Result 表:
+-----------------+
| ConsecutiveNums |
+-----------------+
| 1               |
+-----------------+
解释:1 是唯一连续出现至少三次的数字。

    
---# 
1. 三表直接连接
select distinct l1.num as ConsecutiveNums
from Logs as l1, Logs as l2, Logs as l3
where l1.id = l2.id - 1 and l1.id = l3.id - 2 and l1.num = l2.num and l2.num = l3.num

# 2. 利用窗口函数求出diff后进行分组,再用having子句过滤
select distinct num as ConsecutiveNums
from (select num, id + 1 - row_number() over(partition by num order by id) as diff
      from Logs) t
group by num, diff
having count(*) >= 3

# 3. 如果id不是连续的,要求按照表中连续3个以上的记录
select distinct num as ConsecutiveNums
from (select num, (row_number() over(order by id) - row_number() over(partition by num order by id)) as diff
      from Logs) t
group by num, diff
having count(*) >= 3


SELECT DISTINCT
    NUM AS CONSECUTIVENUMS
FROM
    (   SELECT
            NUM,
            ID  - ROW_NUMBER() OVER ( PARTITION BY NUM ORDER BY  ID ) AS DIFF
        FROM LOGS  )  T
GROUP BY
    NUM,
    DIFF
HAVING
    COUNT(*) >= 3

 

 





posted @ 2024-08-09 11:58  萌哥-爱学习  阅读(3)  评论(0编辑  收藏  举报