SchoolWork-LaTeX/数据库系统原理与实践/平时作业/第三次作业.tex
423A35C7 4a4d9e0e21 数据库系统原理与实践——修改第三次作业
题目改了,之前应该是出错了。按照正常情况就应该是返回订单总金额。
2024-10-10 18:49:30 +08:00

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\documentclass[全部作业]{subfiles}
\input{mysubpreamble}
\begin{document}
\setcounter{chapter}{2}
\chapter{第三次作业}
\begin{enumerate}
\item \choice[1]{在 SQL 中,如果在 SELECT 语句中使用了未被聚合的属性,那么这些属性必须如何处理?
A
它们可以随意出现,不需要在 GROUP BY 中列出
B
它们必须在 GROUP BY 子句中出现
C
它们可以出现在 HAVING 子句中,而不需要在 GROUP BY 中
D
它们只能出现在 WHERE 子句中
}{2}
\item \choice[1]{WHERE和HAVING子句的主要区别是什么
A
WHERE 子句只能用于数值列,而 HAVING 子句可以用于所有类型的列
B
WHERE 子句在数据分组之前过滤数据,而 HAVING 子句在数据分组之后过滤聚合结果
C
HAVING 子句只能在没有 GROUP BY 的情况下使用,而 WHERE 子句可以在有 GROUP BY 的情况下使用
D
WHERE 子句和 HAVING 子句的功能完全相同
}{2}
\item \choice[1]{标量子查询的主要特征是什么?
A
返回多个行和多个列的结果
B
返回一个单一的值,通常是一个属性的聚合结果
C
只能在 INSERT 语句中使用
D
只能用于 WHERE 子句中
}{2}
\item \choice[1]{在MySQL中为什么在执行插入操作之前先执行 SELECT FROM WHERE 查询非常重要?
A
以便查看表的结构和数据类型
B
以确保要插入的数据不会导致主键或唯一性约束冲突
C
以便快速获取插入操作的执行时间
D
以便在插入后自动更新相关的其他表}{2}
\item \choice[1]{在 SQL 中,以下关于 EXISTS 和 NOT EXISTS 的描述哪项是正确的?
A
EXISTS 总是返回 TRUE无论子查询是否返回结果。
B
EXISTS r 为 TRUE 当且仅当子查询 r 返回至少一行结果
C
NOT EXISTS r 为 TRUE 当且仅当子查询 r 返回至少一行结果。
D
EXISTS 子查询可以返回多个列,但必须返回唯一的值。}{2}
\item \choice[1]{假设有两个表格,"employees" 和 "departments",它们的结构如下。我们想要查询每个部门的员工人数。以下选项中,哪个是合适的嵌套子查询语句?
\includegraphics[width=1\linewidth]{imgs/2024-10-03-23-33-32.png}
A
\mint{SQL}|SELECT department_name, COUNT(*) FROM employees JOIN departments ON employees.department_id = departments.id;|
B
\mint{SQL}|SELECT department_name, COUNT(*) FROM employees WHERE department_id = departments.id;|
C
\mint{SQL}|SELECT department_name, (SELECT COUNT(*) FROM employees WHERE employees.department_id = departments.id) FROM departments;|
D
\mint{SQL}|SELECT department_name, COUNT(*) FROM departments JOIN employees ON employees.department_id = departments.id;|
}{3}
\begin{verification}
\begin{minted}{SQL}
drop table if exists employees, departments;
create table employees(
id int auto_increment primary key ,
name varchar(10),
department_id varchar(10)
);
create table departments(
id int auto_increment primary key ,
department_name varchar(10)
);
insert into employees(name, department_id)
values ('John', 1),
('Alice', 1),
('Tom', 2),
('Lisa', 2),
('Mike', 3);
insert into departments(department_name)
values ('HR'),
('IT'),
('Sales');
SELECT department_name, (SELECT COUNT(*) FROM employees WHERE employees.department_id = departments.id) FROM departments;
\end{minted}
\begin{csv}
,department_name,(SELECT ...)
1,HR,2
2,IT,2
3,Sales,1
\end{csv}
\end{verification}
\questionandanswer[]{
count(1)、count(*) 与 count(列名) 的区别?
}{
在执行效果上count(1)和count(*)都会把空值算入结果而count(列名)会忽略空值。
在执行效率上count(主键列名) > count(1) > count(非主键列名)。
}
\questionandanswer[]{
Mysql中exist和in的区别
}{
参考
\url{https://blog.csdn.net/jinjiniao1/article/details/92666614}\\
\url{https://cloud.tencent.com/developer/article/1144244}\\
\url{https://cloud.tencent.com/developer/article/1144253}
那么可以考虑以下两条语句:
\mint{SQL}|select * from A where exists (select * from B where B.id = A.id);|
\mint{SQL}|select * from A where A.id in (select id from B);|
以下称A为内表B为外表两条语句中括号内的内容为子查询结果。
根据参考文章可知exists语句的执行过程是先把内表的数据全部取出来然后对每一条数据判断是否满足子查询的条件只用到了子查询的索引而in语句的执行过程是先将子查询结果查询出来再和内表连接用到了内表和外表的索引。
所以当子查询结果的数据较多外表的数据较少时exists有Block嵌套循环优化目前还不理解查询效率更高而子查询结果的数据较少外表的数据较多时in由于能用到外表的索引所以效率更高。
}
\questionandanswer[]{
OrderItems 表示订单商品表含有字段订单号order_num订单价格item_priceOrders 表代表订单信息表,含有顾客 idcust_id 和订单号order_num。使用子查询返回购买价格为 10 美元或以上产品的顾客列表,结果无需排序。
\includegraphics[width=0.4\linewidth]{imgs/2024-10-04-09-59-11.png}
\includegraphics[width=0.4\linewidth]{imgs/2024-10-04-10-04-16.png}
}{}
{
\begin{minted}{SQL}
select cust_id from Orders where order_num in (
select order_num from OrderItems where item_price >= 10
);
\end{minted}
}
\begin{verification}
\begin{minted}{SQL}
drop table if exists orderitems, orders;
create table if not exists OrderItems
(
order_num varchar(10),
item_price int
);
insert into OrderItems
values ('a1', 10),
('a2', 1),
('a2', 1),
('a2', 1),
('a4', 2),
('a5', 5),
('a2', 1),
('a7', 7);
create table if not exists Orders
(
order_num varchar(10),
cust_id varchar(10)
);
insert into Orders
values ('a1', 'cust10'),
('a2', 'cust1'),
('a2', 'cust1'),
('a4', 'cust2'),
('a5', 'cust5'),
('a2', 'cust4'),
('a7', 'cust7');
select cust_id
from Orders
where order_num in (select order_num
from OrderItems
where item_price >= 10);
\end{minted}
\begin{csv}
,cust_id
1,cust10
\end{csv}
\end{verification}
\questionandanswer[]{
表 OrderItems 代表订单商品信息表prod_id 为产品 idOrders 表代表订单表有 cust_id 代表顾客 id 和订单日期 order_date。编写SQL语句使用子查询来确定哪些订单在 OrderItems 中)购买了 prod_id 为 "BR01" 的产品,然后从 Orders 表中返回每个产品对应的顾客 IDcust_id和订单日期order_date按订购日期对结果进行升序排序。
\includegraphics[width=0.5\linewidth]{imgs/2024-10-04-10-27-04.png}
}{}
{\kaishu
由于要使用子查询这里不考虑使用连接使用exists和in可以分别写出如下SQL语句其功能一样
\begin{minted}{SQL}
select cust_id, order_date from Orders where exists(
select * from OrderItems where prod_id='BR01' and Orders.order_num = OrderItems.order_num
) order by order_date;
select cust_id, order_date from Orders where order_num in (
select order_num from OrderItems where prod_id='BR01'
) order by order_date;
\end{minted}
}
\begin{verification}
\begin{minted}{SQL}
drop table if exists OrderItems;
create table if not exists OrderItems(
prod_id varchar(10),
order_num varchar(10)
);
insert into OrderItems
values ('BR01', 'a0001'),
('BR01', 'a0002'),
('BR02', 'a0003'),
('BR02', 'a0013');
drop table if exists Orders;
create table if not exists Orders(
order_num varchar(10),
cust_id varchar(10),
order_date datetime
);
insert into Orders
values ('a0001', 'cust10', '2022-01-01 00:00:00'),
('a0002', 'cust1', '2022-01-01 00:01:00'),
('a0003', 'cust1', '2022-01-02 00:00:00'),
('a0013', 'cust2', '2022-01-01 00:20:00');
\end{minted}
以下三种不同语句分别使用exists、in和连接可以得到相同结果。
\begin{minted}{SQL}
select cust_id, order_date from Orders where exists(
select * from OrderItems where prod_id='BR01' and Orders.order_num = OrderItems.order_num
) order by order_date;
select cust_id, order_date from Orders where order_num in (
select order_num from OrderItems where prod_id='BR01'
) order by order_date;
select cust_id, order_date from Orders natural join OrderItems where prod_id='BR01' order by order_date;
\end{minted}
\begin{csv}
,cust_id,order_date
1,cust10,2022-01-01 00:00:00
2,cust1,2022-01-01 00:01:00
\end{csv}
\end{verification}
\questionandanswer[]{
有一个顾客ID列表其中包含他们已订购的总金额。OrderItems 表代表订单信息OrderItems 表有订单号order_num 和商品售出价格item_price、商品数量quantity。编写SQL语句返回顾客 IDOrders 表中的 cust_id并使用子查询返回 total_ordered 每个顾客的所有订单总金额,将结果按金额从大到小排序。
\includegraphics[width=0.5\linewidth]{imgs/2024-10-04-10-27-32.png}
}{}
{
\begin{minted}{SQL}
select cust_id, sum(total) as total_ordered
from Orders
join (select order_num, sum(item_price * quantity) as total
from OrderItems
group by order_num) as a on Orders.order_num = a.order_num
group by cust_id
order by total_ordered desc;
\end{minted}
}
\begin{verification}
\begin{minted}{SQL}
drop table if exists orderitems, orders;
create table OrderItems(
order_num varchar(10),
item_price int,
quantity int
);
create table Orders(
order_num varchar(10),
cust_id varchar(10)
);
insert into OrderItems
values ('a0001', 10, 105),
('a0002', 1,1100),
('a0002', 1, 200),
('a0013', 2, 1121),
('a0003', 5, 10),
('a0003', 1, 19),
('a0003', 7, 5);
insert into Orders
values ('a0001', 'cust10'),
('a0002', 'cust1'),
('a0003', 'cust1'),
('a0013', 'cust2');
select cust_id, sum(total) as total_ordered
from Orders
join (select order_num, sum(item_price * quantity) as total
from OrderItems
group by order_num) as a on Orders.order_num = a.order_num
group by cust_id
order by total_ordered desc;
\end{minted}
\begin{csv}
,cust_id,total_ordered
1,cust2,2242
2,cust1,1404
3,cust10,1050
\end{csv}
\end{verification}
\questionandanswer[]{
Products 表中检索所有的产品名称prod_name、产品 idprod_idOrderItems 代表订单商品表订单产品prod_id、售出数量quantity。编写 SQL 语句,从 Products 表中检索所有的产品名称prod_name以及名为 quant_sold 的计算列,其中包含所售产品的总数(在 OrderItems 表上使用子查询和 SUM(quantity) 检索)。
\includegraphics[width=0.4\linewidth]{imgs/2024-10-04-10-27-50.png}
\includegraphics[width=0.4\linewidth]{imgs/2024-10-04-10-28-03.png}
}{}
{\kaishu
\begin{minted}{SQL}
select Products.prod_name, a.quant_sold as quant_sold
from Products
natural join (select prod_id, sum(quantity) as quant_sold
from OrderItems
group by prod_id) as a;
\end{minted}
}
\begin{verification}
\begin{minted}{SQL}
drop table if exists Products, OrderItems;
create table Products (
prod_id varchar(10),
prod_name varchar(10)
);
create table OrderItems (
prod_id varchar(10),
quantity int
);
insert into Products
values ('a0001', 'egg'),
('a0002', 'sockets'),
('a0013', 'coffee'),
('a0003', 'cola');
insert into OrderItems
values ('a0001', 105),
('a0002', 1100),
('a0002', 200),
('a0013', 1121),
('a0003', 10),
('a0003', 19),
('a0003', 5);
select Products.prod_name, a.quant_sold as quant_sold
from Products
natural join (select prod_id, sum(quantity) as quant_sold
from OrderItems
group by prod_id) as a;
\end{minted}
\begin{csv}
,prod_name,quant_sold
1,egg,105
2,sockets,1300
3,coffee,1121
4,cola,34
\end{csv}
\end{verification}
\end{enumerate}
\end{document}