本文實例講述了MySQL 多表關聯一對多查詢實現取最新一條數據的方法。分享給大家供大家參考，具體如下：

由于歷史原因，表結構設計不合理；產品告訴我說需要導出客戶信息數據，需要導出客戶的 所屬行業，納稅性質 數據；但是這兩個字段卻在訂單表里面，每次客戶下單都會要求客戶填寫；由此可知，客戶數據和訂單數據是一對多的關系；那這樣的話，問題就來了，我到底以訂單中的哪一條數據為準呢？經過協商后一致同意以最新的一條數據為準；

數據測試初始化SQL腳本

DROP TABLE IF EXISTS `customer`;CREATE TABLE `customer` (`id` BIGINT NOT NULL COMMENT ’客戶ID’,`real_name` VARCHAR(20) NOT NULL COMMENT ’客戶名字’,`create_time` DATETIME NOT NULL COMMENT ’創建時間’,PRIMARY KEY(`id`))ENGINE=INNODB DEFAULT CHARSET = UTF8 COMMENT ’客戶信息表’;-- DATA FOR TABLE customerINSERT INTO `demo`.`customer` (`id`, `real_name`, `create_time`) VALUES (’7717194510959685632’, ’張三’, ’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’, ’劉六’, ’2019-01-23 16:23:05’);INSERT INTO `demo`.`customer` (`id`, `real_name`, `create_time`) VALUES (’7722233303626055680’, ’寶寶’, ’2019-01-23 16:23:05’);INSERT INTO `demo`.`customer` (`id`, `real_name`, `create_time`) VALUES (’7722233895811448832’, ’小寶’, ’2019-01-23 16:23:05’);INSERT INTO `demo`.`customer` (`id`, `real_name`, `create_time`) VALUES (’7722234507982700544’, ’大寶’, ’2019-01-23 16:23:05’);INSERT INTO `demo`.`customer` (`id`, `real_name`, `create_time`) VALUES (’7722234927631204352’, ’二寶’, ’2019-01-23 16:23:05’);INSERT INTO `demo`.`customer` (`id`, `real_name`, `create_time`) VALUES (’7722235550724423680’, ’小賤’, ’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’, ’小紅’, ’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’, ’阿嬌’, ’2019-01-23 16:23:05’);INSERT INTO `demo`.`customer` (`id`, `real_name`, `create_time`) VALUES (’7722318974421546780’, ’阿貓’, ’2019-01-23 16:23:05’);DROP TABLE IF EXISTS `order_info`;CREATE TABLE `order_info` (`id` BIGINT NOT NULL COMMENT ’訂單ID’,`industry` VARCHAR(255) DEFAULT NULL COMMENT ’所屬行業’, `nature_tax` VARCHAR(255) DEFAULT NULL COMMENT ’納稅性質’,`customer_id` VARCHAR(20) NOT NULL COMMENT ’客戶ID’,`create_time` DATETIME NOT NULL COMMENT ’創建時間’,PRIMARY KEY(`id`))ENGINE=INNODB DEFAULT CHARSET = UTF8 COMMENT ’訂單信息表’;-- DATA FOR TABLE order_infoINSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7700163609453207552’, ’餐飲酒店類’, ’小規模’, ’7717194510959685632’, ’2019-01-23 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7700163609453207553’, ’餐飲酒店類’, ’小規模’, ’7717194510959685632’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7700167995646615552’, ’高新技術’, ’一般納稅人’, ’7718605481599623168’, ’2019-01-23 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7700167995646615553’, ’商貿’, ’一般納稅人’, ’7718605481599623168’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7700193633216569344’, ’商貿’, ’一般納稅人’, ’7720804666226278400’, ’2019-01-23 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7700193633216569345’, ’高新技術’, ’一般納稅人’, ’7720804666226278400’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7700197875671179264’, ’餐飲酒店類’, ’一般納稅人’, ’7720882041353961472’, ’2019-01-23 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7700197875671179266’, ’餐飲酒店類’, ’一般納稅人’, ’7720882041353961472’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7703053372673171456’, ’高新技術’, ’小規模’, ’7722233303626055680’, ’2019-01-23 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7703053372673171457’, ’高新技術’, ’小規模’, ’7722233303626055680’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709742385262698496’, ’服務類’, ’一般納稅人’, ’7722233895811448832’, ’2019-01-23 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709742385262698498’, ’服務類’, ’一般納稅人’, ’7722233895811448832’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745055683780608’, ’高新技術’, ’小規模’, ’7722234507982700544’, ’2019-01-23 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745055683780609’, ’進出口’, ’小規模’, ’7722234507982700544’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745249439653888’, ’文化體育’, ’一般納稅人’, ’7722234927631204352’, ’2019-01-24 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745249439653889’, ’高新技術’, ’一般納稅人’, ’7722234927631204352’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745453266051072’, ’高新技術’, ’小規模’, ’7722235550724423680’, ’2019-01-24 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745453266051073’, ’文化體育’, ’小規模’, ’7722235550724423680’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745539848413184’, ’科技’, ’一般納稅人’, ’7722235921488314368’, ’2019-01-24 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745539848413185’, ’高新技術’, ’一般納稅人’, ’7722235921488314368’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745652603887616’, ’高新技術’, ’一般納稅人’, ’7722238233975881728’, ’2019-01-24 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745652603887617’, ’科技’, ’一般納稅人’, ’7722238233975881728’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745755528568832’, ’進出口’, ’一般納稅人’, ’7722246644138409984’, ’2019-01-24 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745755528568833’, ’教育咨詢’, ’小規模’, ’7722246644138409984’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745892539047936’, ’教育咨詢’, ’一般納稅人’, ’7722318634321346560’, ’2019-01-24 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709745892539047937’, ’進出口’, ’一般納稅人’, ’7722318634321346560’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709746000127139840’, ’生產類’, ’小規模’, ’7722318674321346586’, ’2019-01-24 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709746000127139841’, ’農業’, ’一般納稅人’, ’7722318674321346586’, ’2019-01-23 17:09:53’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709746447445467136’, ’農業’, ’一般納稅人’, ’7722318974421546780’, ’2019-01-24 16:54:25’);INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES (’7709746447445467137’, ’生產類’, ’小規模’, ’7722318974421546780’, ’2019-01-23 17:09:53’); 按需求寫的SQL語句：

UPDATE order_info SET create_time = NOW(); 嘗試解決問題

SELECTcr.id,cr.real_name,oi.industry,oi.nature_taxFROMcustomer AS crLEFT JOIN (SELECT a.industry, a.nature_tax, a.customer_id, a.create_time FROM order_info AS aLEFT 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_idWHERE a.create_time = b.create_time) AS oi ON oi.customer_id = cr.idGROUP BY cr.id;

數據重復嘛，小意思，加個 GROUP BY 不就解決了嗎？我怎么會這么機智，哈哈哈！！！但是當我執行完SQL的那一瞬間，我又懵逼了，查詢出來的結果中 所屬行業，納稅性質 仍然不是最新的；看來是我想太多了，還是老老實實的解決問題吧。。。

SELECTcr.id,cr.real_name,oi.industry,oi.nature_taxFROMcustomer AS crLEFT JOIN (SELECT a.industry, a.nature_tax, a.customer_id, a.create_time FROM order_info AS aLEFT 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_idWHERE a.create_time = b.create_time) AS oi ON oi.customer_id = cr.idGROUP BY cr.id HAVING COUNT(cr.id) >= 2; 執行結果如下：

SELECTcr.id,cr.real_name,oi.industry,oi.nature_taxFROMcustomer AS crLEFT JOIN (SELECT a.industry, a.nature_tax, a.customer_id, a.create_time FROM order_info AS aLEFT JOIN (SELECT MAX(id) AS id, customer_id FROM order_info GROUP BY customer_id) AS b ON a.customer_id = b.customer_idWHERE a.id = b.id) AS oi ON oi.customer_id = cr.id;

哎，終于解決了。。。

更多關于MySQL相關內容感興趣的讀者可查看本站專題：《MySQL查詢技巧大全》、《MySQL事務操作技巧匯總》、《MySQL存儲過程技巧大全》、《MySQL數據庫鎖相關技巧匯總》及《MySQL常用函數大匯總》

希望本文所述對大家MySQL數據庫計有所幫助。