\documentclass[全部作业]{subfiles} \input{mysubpreamble} \BeforeBeginEnvironment{minted}{\begin{framed}} \AfterEndEnvironment{minted}{\end{framed}} \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_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。 \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 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。 \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 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。 \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 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)。 \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}