445 lines
13 KiB
TeX
445 lines
13 KiB
TeX
\documentclass[全部作业]{subfiles}
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\input{mysubpreamble}
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\BeforeBeginEnvironment{minted}{\begin{framed}}
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\AfterEndEnvironment{minted}{\end{framed}}
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\begin{document}
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\setcounter{chapter}{2}
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\chapter{第三次作业}
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\begin{enumerate}
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\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？
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A
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它们可以随意出现，不需要在 GROUP BY 中列出
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B
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它们必须在 GROUP BY 子句中出现
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C
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它们可以出现在 HAVING 子句中，而不需要在 GROUP BY 中
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D
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它们只能出现在 WHERE 子句中
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}{2}
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\item \choice[1]{WHERE和HAVING子句的主要区别是什么？
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A
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WHERE 子句只能用于数值列，而 HAVING 子句可以用于所有类型的列
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B
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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
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C
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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
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D
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WHERE 子句和 HAVING 子句的功能完全相同
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}{2}
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\item \choice[1]{标量子查询的主要特征是什么？
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A
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返回多个行和多个列的结果
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B
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返回一个单一的值，通常是一个属性的聚合结果
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C
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只能在 INSERT 语句中使用
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D
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只能用于 WHERE 子句中
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}{2}
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\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？
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A
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以便查看表的结构和数据类型
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B
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以确保要插入的数据不会导致主键或唯一性约束冲突
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C
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以便快速获取插入操作的执行时间
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D
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以便在插入后自动更新相关的其他表}{2}
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\item \choice[1]{在 SQL 中，以下关于 EXISTS 和 NOT EXISTS 的描述哪项是正确的？
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A
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EXISTS 总是返回 TRUE，无论子查询是否返回结果。
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B
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EXISTS r 为 TRUE 当且仅当子查询 r 返回至少一行结果
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C
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NOT EXISTS r 为 TRUE 当且仅当子查询 r 返回至少一行结果。
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D
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EXISTS 子查询可以返回多个列，但必须返回唯一的值。}{2}
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\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？
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\includegraphics[width=1\linewidth]{imgs/2024-10-03-23-33-32.png}
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A
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\mint{SQL}|SELECT department_name, COUNT(*) FROM employees JOIN departments ON employees.department_id = departments.id;|
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B
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\mint{SQL}|SELECT department_name, COUNT(*) FROM employees WHERE department_id = departments.id;|
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C
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\mint{SQL}|SELECT department_name, (SELECT COUNT(*) FROM employees WHERE employees.department_id = departments.id) FROM departments;|
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D
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\mint{SQL}|SELECT department_name, COUNT(*) FROM departments JOIN employees ON employees.department_id = departments.id;|
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}{3}
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\begin{verification}
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\begin{minted}{SQL}
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drop table if exists employees, departments;
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create table employees(
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id int auto_increment primary key ,
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name varchar(10),
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department_id varchar(10)
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);
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create table departments(
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id int auto_increment primary key ,
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department_name varchar(10)
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);
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insert into employees(name, department_id)
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values ('John', 1),
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('Alice', 1),
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('Tom', 2),
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('Lisa', 2),
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('Mike', 3);
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insert into departments(department_name)
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values ('HR'),
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('IT'),
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('Sales');
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SELECT department_name, (SELECT COUNT(*) FROM employees WHERE employees.department_id = departments.id) FROM departments;
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\end{minted}
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\begin{csv}
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,department_name,(SELECT ...)
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1,HR,2
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2,IT,2
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3,Sales,1
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\end{csv}
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\end{verification}
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\questionandanswer[]{
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count(1)、count(*) 与 count(列名) 的区别？
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}{
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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。
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在执行效率上，count(主键列名) > count(1) > count(非主键列名)。
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}
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\questionandanswer[]{
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Mysql中exist和in的区别？
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}{
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参考
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\url{https://blog.csdn.net/jinjiniao1/article/details/92666614}\\
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\url{https://cloud.tencent.com/developer/article/1144244}\\
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\url{https://cloud.tencent.com/developer/article/1144253}
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那么可以考虑以下两条语句：
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\mint{SQL}|select * from A where exists (select * from B where B.id = A.id);|
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\mint{SQL}|select * from A where A.id in (select id from B);|
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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。
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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。
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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。
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}
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\questionandanswer[]{
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OrderItems 表示订单商品表，含有字段订单号：order_num，订单价格：item_price；Orders 表代表订单信息表，含有顾客 id：cust_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。
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\includegraphics[width=0.4\linewidth]{imgs/2024-10-04-09-59-11.png}
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\includegraphics[width=0.4\linewidth]{imgs/2024-10-04-10-04-16.png}
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}{}
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{
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\begin{minted}{SQL}
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select cust_id from Orders where order_num in (
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select order_num from OrderItems where item_price >= 10
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);
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\end{minted}
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}
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\begin{verification}
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\begin{minted}{SQL}
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drop table if exists orderitems, orders;
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create table if not exists OrderItems
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(
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order_num varchar(10),
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item_price int
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);
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insert into OrderItems
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values ('a1', 10),
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('a2', 1),
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('a2', 1),
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('a2', 1),
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('a4', 2),
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('a5', 5),
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('a2', 1),
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('a7', 7);
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create table if not exists Orders
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(
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order_num varchar(10),
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cust_id varchar(10)
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);
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insert into Orders
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values ('a1', 'cust10'),
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('a2', 'cust1'),
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('a2', 'cust1'),
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('a4', 'cust2'),
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('a5', 'cust5'),
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('a2', 'cust4'),
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('a7', 'cust7');
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select cust_id
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from Orders
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where order_num in (select order_num
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from OrderItems
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where item_price >= 10);
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\end{minted}
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\begin{csv}
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,cust_id
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1,cust10
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\end{csv}
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\end{verification}
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\questionandanswer[]{
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表 OrderItems 代表订单商品信息表，prod_id 为产品 id；Orders 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 ID（cust_id）和订单日期（order_date），按订购日期对结果进行升序排序。
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\includegraphics[width=0.5\linewidth]{imgs/2024-10-04-10-27-04.png}
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}{}
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{\kaishu
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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：
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\begin{minted}{SQL}
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select cust_id, order_date from Orders where exists(
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select * from OrderItems where prod_id='BR01' and Orders.order_num = OrderItems.order_num
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) order by order_date;
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select cust_id, order_date from Orders where order_num in (
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select order_num from OrderItems where prod_id='BR01'
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) order by order_date;
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\end{minted}
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}
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\begin{verification}
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\begin{minted}{SQL}
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drop table if exists OrderItems;
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create table if not exists OrderItems(
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prod_id varchar(10),
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order_num varchar(10)
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);
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insert into OrderItems
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values ('BR01', 'a0001'),
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('BR01', 'a0002'),
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('BR02', 'a0003'),
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('BR02', 'a0013');
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drop table if exists Orders;
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create table if not exists Orders(
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order_num varchar(10),
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cust_id varchar(10),
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order_date datetime
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);
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insert into Orders
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values ('a0001', 'cust10', '2022-01-01 00:00:00'),
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('a0002', 'cust1', '2022-01-01 00:01:00'),
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('a0003', 'cust1', '2022-01-02 00:00:00'),
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('a0013', 'cust2', '2022-01-01 00:20:00');
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\end{minted}
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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。
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\begin{minted}{SQL}
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select cust_id, order_date from Orders where exists(
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select * from OrderItems where prod_id='BR01' and Orders.order_num = OrderItems.order_num
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) order by order_date;
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select cust_id, order_date from Orders where order_num in (
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select order_num from OrderItems where prod_id='BR01'
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) order by order_date;
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select cust_id, order_date from Orders natural join OrderItems where prod_id='BR01' order by order_date;
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\end{minted}
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\begin{csv}
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,cust_id,order_date
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1,cust10,2022-01-01 00:00:00
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2,cust1,2022-01-01 00:01:00
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\end{csv}
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\end{verification}
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\questionandanswer[]{
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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 ID（Orders 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。
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\includegraphics[width=0.5\linewidth]{imgs/2024-10-04-10-27-32.png}
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}{}
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{
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\begin{minted}{SQL}
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select cust_id, sum(total) as total_ordered
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from Orders
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join (select order_num, sum(item_price * quantity) as total
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from OrderItems
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group by order_num) as a on Orders.order_num = a.order_num
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group by cust_id
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order by total_ordered desc;
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\end{minted}
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}
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\begin{verification}
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\begin{minted}{SQL}
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drop table if exists orderitems, orders;
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create table OrderItems(
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order_num varchar(10),
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item_price int,
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quantity int
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);
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create table Orders(
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order_num varchar(10),
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cust_id varchar(10)
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);
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insert into OrderItems
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values ('a0001', 10, 105),
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('a0002', 1,1100),
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('a0002', 1, 200),
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('a0013', 2, 1121),
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('a0003', 5, 10),
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('a0003', 1, 19),
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('a0003', 7, 5);
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insert into Orders
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values ('a0001', 'cust10'),
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('a0002', 'cust1'),
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('a0003', 'cust1'),
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('a0013', 'cust2');
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select cust_id, sum(total) as total_ordered
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from Orders
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join (select order_num, sum(item_price * quantity) as total
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from OrderItems
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group by order_num) as a on Orders.order_num = a.order_num
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group by cust_id
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order by total_ordered desc;
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\end{minted}
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\begin{csv}
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,cust_id,total_ordered
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1,cust2,2242
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2,cust1,1404
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3,cust10,1050
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\end{csv}
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\end{verification}
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\questionandanswer[]{
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Products 表中检索所有的产品名称：prod_name、产品 id：prod_id；OrderItems 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）。
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\includegraphics[width=0.4\linewidth]{imgs/2024-10-04-10-27-50.png}
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\includegraphics[width=0.4\linewidth]{imgs/2024-10-04-10-28-03.png}
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}{}
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{\kaishu
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\begin{minted}{SQL}
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select Products.prod_name, a.quant_sold as quant_sold
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from Products
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natural join (select prod_id, sum(quantity) as quant_sold
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from OrderItems
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group by prod_id) as a;
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\end{minted}
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}
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\begin{verification}
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\begin{minted}{SQL}
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drop table if exists Products, OrderItems;
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create table Products (
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prod_id varchar(10),
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prod_name varchar(10)
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);
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create table OrderItems (
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prod_id varchar(10),
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quantity int
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);
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insert into Products
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values ('a0001', 'egg'),
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('a0002', 'sockets'),
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('a0013', 'coffee'),
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('a0003', 'cola');
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insert into OrderItems
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values ('a0001', 105),
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('a0002', 1100),
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('a0002', 200),
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('a0013', 1121),
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('a0003', 10),
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('a0003', 19),
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('a0003', 5);
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select Products.prod_name, a.quant_sold as quant_sold
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from Products
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natural join (select prod_id, sum(quantity) as quant_sold
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from OrderItems
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group by prod_id) as a;
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\end{minted}
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\begin{csv}
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,prod_name,quant_sold
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1,egg,105
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2,sockets,1300
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3,coffee,1121
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4,cola,34
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\end{csv}
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\end{verification}
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\end{enumerate}
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\end{document} |