SQL力扣刷题五_select books()

1098. 小众书籍

Create table If Not Exists Books (book_id int, name varchar(50), available_from date)
Create table If Not Exists Orders (order_id int, book_id int, quantity int, dispatch_date date)
Truncate table Books
insert into Books (book_id, name, available_from) values ('1', 'Kalila And Demna', '2010-01-01')
insert into Books (book_id, name, available_from) values ('2', '28 Letters', '2012-05-12')
insert into Books (book_id, name, available_from) values ('3', 'The Hobbit', '2019-06-10')
insert into Books (book_id, name, available_from) values ('4', '13 Reasons Why', '2019-06-01')
insert into Books (book_id, name, available_from) values ('5', 'The Hunger Games', '2008-09-21')
Truncate table Orders
insert into Orders (order_id, book_id, quantity, dispatch_date) values ('1', '1', '2', '2018-07-26')
insert into Orders (order_id, book_id, quantity, dispatch_date) values ('2', '1', '1', '2018-11-05')
insert into Orders (order_id, book_id, quantity, dispatch_date) values ('3', '3', '8', '2019-06-11')
insert into Orders (order_id, book_id, quantity, dispatch_date) values ('4', '4', '6', '2019-06-05')
insert into Orders (order_id, book_id, quantity, dispatch_date) values ('5', '4', '5', '2019-06-20')
insert into Orders (order_id, book_id, quantity, dispatch_date) values ('6', '5', '9', '2009-02-02')
insert into Orders (order_id, book_id, quantity, dispatch_date) values ('7', '5', '8', '2010-04-13')
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书籍表 Books：

+----------------+---------+
| Column Name    | Type    |
+----------------+---------+
| book_id        | int     |
| name           | varchar |
| available_from | date    |
+----------------+---------+
book_id 是这个表的主键。
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订单表 Orders：

+----------------+---------+
| Column Name    | Type    |
+----------------+---------+
| order_id       | int     |
| book_id        | int     |
| quantity       | int     |
| dispatch_date  | date    |
+----------------+---------+
order_id 是这个表的主键。
book_id  是 Books 表的外键。
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你需要写一段 SQL 命令，筛选出过去一年中订单总量 少于10本 的 书籍 。

注意：不考虑 上架（available from）距今 不满一个月 的书籍。并且 假设今天是 2019-06-23 。

下面是样例输出结果：

Books 表：
+---------+--------------------+----------------+
| book_id | name               | available_from |
+---------+--------------------+----------------+
| 1       | "Kalila And Demna" | 2010-01-01     |
| 2       | "28 Letters"       | 2012-05-12     |
| 3       | "The Hobbit"       | 2019-06-10     |
| 4       | "13 Reasons Why"   | 2019-06-01     |
| 5       | "The Hunger Games" | 2008-09-21     |
+---------+--------------------+----------------+

Orders 表：
+----------+---------+----------+---------------+
| order_id | book_id | quantity | dispatch_date |
+----------+---------+----------+---------------+
| 1        | 1       | 2        | 2018-07-26    |
| 2        | 1       | 1        | 2018-11-05    |
| 3        | 3       | 8        | 2019-06-11    |
| 4        | 4       | 6        | 2019-06-05    |
| 5        | 4       | 5        | 2019-06-20    |
| 6        | 5       | 9        | 2009-02-02    |
| 7        | 5       | 8        | 2010-04-13    |
+----------+---------+----------+---------------+

Result 表：
+-----------+--------------------+
| book_id   | name               |
+-----------+--------------------+
| 1         | "Kalila And Demna" |
| 2         | "28 Letters"       |
| 5         | "The Hunger Games" |
+-----------+--------------------+
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题解一

select temp1.book_id, temp1.name from (
	select book_id, name from books 
	where datediff('2019-06-23', available_from) > 30
) as temp1 left join (
	select book_id, sum(quantity) as total_sales from orders 
	where datediff('2019-06-23', dispatch_date) < 365
    group by book_id
) as temp2 on temp1.book_id = temp2.book_id 
where ifnull(total_sales, 0) < 10;
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题解二

select books.book_id, books.name from books left join orders
on books.book_id = orders.book_id 
and ifnull(datediff('2019-06-23', dispatch_date), 0) < 365
where datediff('2019-06-23', available_from) > 30 
group by books.book_id, name having ifnull(sum(quantity), 0) < 10;
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题解三

select temp1.book_id, temp1.name from (
	select book_id, name from books 
	where datediff('2019-06-23', available_from) > 30
) as temp1 left join orders on temp1.book_id = orders.book_id 
and ifnull(datediff('2019-06-23', dispatch_date), 0) < 365
group by temp1.book_id, temp1.name having ifnull(sum(quantity), 0) < 10;
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1107. 每日新用户统计

Create table If Not Exists Traffic (user_id int, activity ENUM('login', 'logout', 'jobs', 'groups', 'homepage'), activity_date date)
Truncate table Traffic
insert into Traffic (user_id, activity, activity_date) values ('1', 'login', '2019-05-01')
insert into Traffic (user_id, activity, activity_date) values ('1', 'homepage', '2019-05-01')
insert into Traffic (user_id, activity, activity_date) values ('1', 'logout', '2019-05-01')
insert into Traffic (user_id, activity, activity_date) values ('2', 'login', '2019-06-21')
insert into Traffic (user_id, activity, activity_date) values ('2', 'logout', '2019-06-21')
insert into Traffic (user_id, activity, activity_date) values ('3', 'login', '2019-01-01')
insert into Traffic (user_id, activity, activity_date) values ('3', 'jobs', '2019-01-01')
insert into Traffic (user_id, activity, activity_date) values ('3', 'logout', '2019-01-01')
insert into Traffic (user_id, activity, activity_date) values ('4', 'login', '2019-06-21')
insert into Traffic (user_id, activity, activity_date) values ('4', 'groups', '2019-06-21')
insert into Traffic (user_id, activity, activity_date) values ('4', 'logout', '2019-06-21')
insert into Traffic (user_id, activity, activity_date) values ('5', 'login', '2019-03-01')
insert into Traffic (user_id, activity, activity_date) values ('5', 'logout', '2019-03-01')
insert into Traffic (user_id, activity, activity_date) values ('5', 'login', '2019-06-21')
insert into Traffic (user_id, activity, activity_date) values ('5', 'logout', '2019-06-21')
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Traffic 表：

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| user_id       | int     |
| activity      | enum    |
| activity_date | date    |
+---------------+---------+
该表没有主键，它可能有重复的行。
activity 列是 ENUM 类型，可能取 ('login', 'logout', 'jobs', 'groups', 'homepage') 几个值之一。
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编写一个 SQL 查询，以查询从今天起最多 90 天内，每个日期该日期首次登录的用户数。假设今天是 2019-06-30.

查询结果格式如下例所示：

Traffic 表：
+---------+----------+---------------+
| user_id | activity | activity_date |
+---------+----------+---------------+
| 1       | login    | 2019-05-01    |
| 1       | homepage | 2019-05-01    |
| 1       | logout   | 2019-05-01    |
| 2       | login    | 2019-06-21    |
| 2       | logout   | 2019-06-21    |
| 3       | login    | 2019-01-01    |
| 3       | jobs     | 2019-01-01    |
| 3       | logout   | 2019-01-01    |
| 4       | login    | 2019-06-21    |
| 4       | groups   | 2019-06-21    |
| 4       | logout   | 2019-06-21    |
| 5       | login    | 2019-03-01    |
| 5       | logout   | 2019-03-01    |
| 5       | login    | 2019-06-21    |
| 5       | logout   | 2019-06-21    |
+---------+----------+--------
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