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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。。。
更多关于MySQL相关内容感兴趣的读者可查看本站专题:《MySQL查询技巧大全》、《MySQL事务操作技巧汇总》、《MySQL存储过程技巧大全》、《MySQL数据库锁相关技巧汇总》及《MySQL常用函数大汇总》
希望本文所述对大家MySQL数据库计有所帮助。
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