欢迎您访问程序员文章站本站旨在为大家提供分享程序员计算机编程知识!
您现在的位置是: 首页  >  IT编程

MySQL 多表关联一对多查询实现取最新一条数据的方法示例

程序员文章站 2022-11-22 16:10:42
本文实例讲述了mysql 多表关联一对多查询实现取最新一条数据的方法。分享给大家供大家参考,具体如下:mysql 多表关联一对多查询取最新的一条数据遇到的问题多表关联一对多查询取最新的一条数据,数据出...

本文实例讲述了mysql 多表关联一对多查询实现取最新一条数据的方法。分享给大家供大家参考,具体如下:

mysql 多表关联一对多查询取最新的一条数据

遇到的问题

多表关联一对多查询取最新的一条数据,数据出现重复

由于历史原因,表结构设计不合理;产品告诉我说需要导出客户信息数据,需要导出客户的 所属行业纳税性质 数据;但是这两个字段却在订单表里面,每次客户下单都会要求客户填写;由此可知,客户数据和订单数据是一对多的关系;那这样的话,问题就来了,我到底以订单中的哪一条数据为准呢?经过协商后一致同意以最新的一条数据为准;

数据测试初始化sql脚本

drop table if exists `customer`;
create table `customer` (
	`id` bigint not null comment '客户id',
	`real_name` varchar(20) not null comment '客户名字',
	`create_time` datetime not null comment '创建时间',
	primary key(`id`)
)engine=innodb default charset = utf8 comment '客户信息表';

-- data for table customer
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7717194510959685632', '张三', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7718605481599623168', '李四', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7720804666226278400', '王五', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7720882041353961472', '刘六', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722233303626055680', '宝宝', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722233895811448832', '小宝', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722234507982700544', '大宝', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722234927631204352', '二宝', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722235550724423680', '小贱', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722235921488314368', '小明', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722238233975881728', '小黑', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722246644138409984', '小红', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722318634321346560', '阿狗', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722318674321346586', '阿娇', '2019-01-23 16:23:05');
insert into `demo`.`customer` (`id`, `real_name`, `create_time`) values ('7722318974421546780', '阿猫', '2019-01-23 16:23:05');


drop table if exists `order_info`;
create table `order_info` (
	`id` bigint not null comment '订单id',
	`industry` varchar(255) default null comment '所属行业',
 `nature_tax` varchar(255) default null comment '纳税性质',
	`customer_id` varchar(20) not null comment '客户id',
	`create_time` datetime not null comment '创建时间',
	primary key(`id`)
)engine=innodb default charset = utf8 comment '订单信息表';

-- data for table order_info
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7700163609453207552', '餐饮酒店类', '小规模', '7717194510959685632', '2019-01-23 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7700163609453207553', '餐饮酒店类', '小规模', '7717194510959685632', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7700167995646615552', '高新技术', '一般纳税人', '7718605481599623168', '2019-01-23 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7700167995646615553', '商贸', '一般纳税人', '7718605481599623168', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7700193633216569344', '商贸', '一般纳税人', '7720804666226278400', '2019-01-23 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7700193633216569345', '高新技术', '一般纳税人', '7720804666226278400', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7700197875671179264', '餐饮酒店类', '一般纳税人', '7720882041353961472', '2019-01-23 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7700197875671179266', '餐饮酒店类', '一般纳税人', '7720882041353961472', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7703053372673171456', '高新技术', '小规模', '7722233303626055680', '2019-01-23 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7703053372673171457', '高新技术', '小规模', '7722233303626055680', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709742385262698496', '服务类', '一般纳税人', '7722233895811448832', '2019-01-23 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709742385262698498', '服务类', '一般纳税人', '7722233895811448832', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745055683780608', '高新技术', '小规模', '7722234507982700544', '2019-01-23 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745055683780609', '进出口', '小规模', '7722234507982700544', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745249439653888', '文化体育', '一般纳税人', '7722234927631204352', '2019-01-24 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745249439653889', '高新技术', '一般纳税人', '7722234927631204352', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745453266051072', '高新技术', '小规模', '7722235550724423680', '2019-01-24 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745453266051073', '文化体育', '小规模', '7722235550724423680', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745539848413184', '科技', '一般纳税人', '7722235921488314368', '2019-01-24 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745539848413185', '高新技术', '一般纳税人', '7722235921488314368', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745652603887616', '高新技术', '一般纳税人', '7722238233975881728', '2019-01-24 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745652603887617', '科技', '一般纳税人', '7722238233975881728', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745755528568832', '进出口', '一般纳税人', '7722246644138409984', '2019-01-24 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745755528568833', '教育咨询', '小规模', '7722246644138409984', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745892539047936', '教育咨询', '一般纳税人', '7722318634321346560', '2019-01-24 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709745892539047937', '进出口', '一般纳税人', '7722318634321346560', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709746000127139840', '生产类', '小规模', '7722318674321346586', '2019-01-24 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709746000127139841', '农业', '一般纳税人', '7722318674321346586', '2019-01-23 17:09:53');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709746447445467136', '农业', '一般纳税人', '7722318974421546780', '2019-01-24 16:54:25');
insert into `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) values ('7709746447445467137', '生产类', '小规模', '7722318974421546780', '2019-01-23 17:09:53');

  • 按需求写的sql语句:
update order_info set create_time = now();
  • 尝试解决问题
select
	cr.id,
	cr.real_name,
	oi.industry,
	oi.nature_tax
from
	customer as cr
left join (
	select a.industry, a.nature_tax, a.customer_id, a.create_time from order_info as a
	left join (
		select max(create_time) as create_time, customer_id from order_info group by customer_id
	) as b on a.customer_id = b.customer_id
where a.create_time = b.create_time
) as oi on oi.customer_id = cr.id
group by cr.id;

数据重复嘛,小意思,加个 group by 不就解决了吗?我怎么会这么机智,哈哈哈!!!但是当我执行完sql的那一瞬间,我又懵逼了,查询出来的结果中 所属行业纳税性质 仍然不是最新的;看来是我想太多了,还是老老实实的解决问题吧。。。

  • 找出重复数据
select
	cr.id,
	cr.real_name,
	oi.industry,
	oi.nature_tax
from
	customer as cr
left join (
	select a.industry, a.nature_tax, a.customer_id, a.create_time from order_info as a
	left join (
		select max(create_time) as create_time, customer_id from order_info group by customer_id
	) as b on a.customer_id = b.customer_id
where a.create_time = b.create_time
) as oi on oi.customer_id = cr.id
group by cr.id having count(cr.id) >= 2;
  • 执行结果如下:
select
	cr.id,
	cr.real_name,
	oi.industry,
	oi.nature_tax
from
	customer as cr
left join (
	select a.industry, a.nature_tax, a.customer_id, a.create_time from order_info as a
	left join (
		select max(id) as id, customer_id from order_info group by customer_id
	) as b on a.customer_id = b.customer_id
where a.id = b.id
) as oi on oi.customer_id = cr.id;

哎,终于解决了。。。