MySQL 多表關聯一對多查詢實現取最新一條數據的方法示例
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：
MySQL 多表關聯一對多查詢取最新的一條數據遇到的問題多表關聯一對多查詢取最新的一條數據，數據出現重復由于歷史原因，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。。。
找出重復數據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。
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