,‘20190502120000‘,‘2‘,‘522131199901016667‘);
表3 车票表
create table tickets(
ticket_id varchar(18) primary key,
train_number varchar(10) not null,
start_station char(11) not null,
arrive_station varchar(16) not null,
seat_type varchar(18) not null,
price varchar(18),
go_time timestamp,
arrive_time timestamp,
type varchar(18),
order_number varchar(18)
);
insert into tickets values(‘ticket201904200001‘,‘Z49‘,‘上海‘,‘杭州‘,‘硬座‘,‘20.00‘,‘2019-04-20 21:01:00‘,‘2019-04-20 22:00:00‘,‘成人票‘,‘201904200001‘);
insert into tickets values(‘ticket201904200002‘,‘Z50‘,‘嘉兴‘,‘杭州‘,‘硬座‘,‘10.00‘,‘2019-04-02 21:00:00‘,‘2019-04-02 22:00:00‘,‘成人票‘,‘201904020001‘);
insert into tickets values(‘ticket201904200003‘,‘Z50‘,‘上海‘,‘南京‘,‘硬座‘,‘10.00‘,‘2019-04-02 21:00:00‘,‘2019-04-02 22:00:00‘,‘成人票‘,‘201904020004‘);
insert into tickets values(‘ticket201904200004‘,‘Z50‘,‘上海‘,‘杭州‘,‘硬卧‘,‘10.00‘,‘2019-04-02 21:00:00‘,‘2019-04-02 22:00:00‘,‘成人票‘,‘201904020005‘);
insert into tickets values(‘ticket201904200005‘,‘G11‘,‘上海‘,‘武汉‘,‘硬座‘,‘10.00‘,‘2019-04-02 21:00:00‘,‘2019-04-02 22:00:00‘,‘成人票‘,‘201904020001‘);
三、具体查询需求分析:
日期处理:arrive_time只需要日期+时分。
建表的时候有五种:
https://www.cnblogs.com/Jie-Jack/p/3793304.html
查询的时候:
需要格式化,DATE_FORMAT(tickets.arrive_time,‘%Y%m%d %H:%i:%s‘
select date_format(order_time,‘%Y-%m-%d %H:%m‘) order_time from orders;
主要是车票表的查询:
(1)需求:查询所有从上海出发到杭州的火车的车次,起点,终点站,席位,价格,出发时间
select train_number as 车次,
start_station as 起点,
arrive_station as 终点,
seat_type as 席位,
price as 价格,
date_format(go_time,‘%Y-%m-%d %H:%m‘) 出发时间
from tickets
where start_station = ‘上海‘
and
arrive_station = ‘杭州‘;
![技术图片](https://img.gxlcms.com//Uploads-s/new/2020-10-11-qlqqti/20190420214656092385.png)
type字段显示为All,没有用到索引。
(2)优化:为了加快查找速度,给始发站和终点站添加复合索引
alter table tickets add index idx_start_arrive(start_station,arrive_station);
![技术图片](http://www.mamicode.com/file:///C:/Users/ADMINI~1/AppData/Local/Temp/enhtmlclip/Image(10).png)
![技术图片](http://www.mamicode.com/data:image/png;base64,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)
type字段为ref,性能优化较好。
表结构参考了:
http://www.mayiwenku.com/p-5808164.html
火车票订票系统的数据库设计与实现(某某乐后端实习面试题)
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