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用實例解析MySQL多表關聯一對多查詢如何實現取最新一條數據

發布時間:2020-07-21 17:05:30 來源:億速云 閱讀:1022 作者:小豬 欄目:MySQL數據庫

這篇文章主要用實例解析MySQL多表關聯一對多查詢如何實現取最新一條數據,內容簡而易懂,希望大家可以學習一下,學習完之后肯定會有收獲的,下面讓小編帶大家一起來看看吧。

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 customer
INSERT 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_info
INSERT 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
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;

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
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;
  • 執行結果如下:
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,終于解決了。。。

以上就是關于用實例解析MySQL多表關聯一對多查詢如何實現取最新一條數據的內容,如果你們有學習到知識或者技能,可以把它分享出去讓更多的人看到。

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