Example of how to retrieve the latest data using MySQL multi-table association one-to-many query

This article uses an example to describe how to retrieve the latest data using a one-to-many query with multiple tables in MySQL. Share with you for your reference, the details are as follows:

MySQL multi-table association one-to-many query to get the latest data

Problems encountered

Multiple tables are associated with one-to-many queries to obtain the latest data, and the data is repeated

Due to historical reasons, the table structure design is unreasonable; the product told me that I need to export customer information data, the customer's industry , and tax nature data; but these two fields are in the order table, and customers are required to fill them in every time they place an order; it can be seen that customer data and order data are a one-to-many relationship; then the question is, which data in the order should I take as the basis? After consultation, it was agreed that the latest data shall prevail;

Data test initialization SQL script

DROP TABLE IF EXISTS `customer`;
CREATE TABLE `customer` (
	`id` BIGINT NOT NULL COMMENT 'Customer ID',
	`real_name` VARCHAR(20) NOT NULL COMMENT 'Customer name',
	`create_time` DATETIME NOT NULL COMMENT 'Creation time',
	PRIMARY KEY (`id`)
)ENGINE=INNODB DEFAULT CHARSET = UTF8 COMMENT 'Customer information table';

-- 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', 'Baby', '2019-01-23 16:23:05');
INSERT INTO `demo`.`customer` (`id`, `real_name`, `create_time`) VALUES ('7722233895811448832', 'Xiaobao', '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', 'Xiao Ming', '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', 'Xiaohong', '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 'Order ID',
	`industry` VARCHAR(255) DEFAULT NULL COMMENT 'Industry',
 `nature_tax` VARCHAR(255) DEFAULT NULL COMMENT 'Tax nature',
	`customer_id` VARCHAR(20) NOT NULL COMMENT 'Customer ID',
	`create_time` DATETIME NOT NULL COMMENT 'Creation time',
	PRIMARY KEY (`id`)
)ENGINE=INNODB DEFAULT CHARSET = UTF8 COMMENT 'Order information table';

-- DATA FOR TABLE order_info
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7700163609453207552', 'catering and hotel', 'small scale', '7717194510959685632', '2019-01-23 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7700163609453207553', 'catering and hotel', 'small scale', '7717194510959685632', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7700167995646615552', 'High-tech', 'General taxpayer', '7718605481599623168', '2019-01-23 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7700167995646615553', 'Commerce', 'General Taxpayer', '7718605481599623168', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7700193633216569344', 'Commerce', 'General Taxpayer', '7720804666226278400', '2019-01-23 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7700193633216569345', 'High-tech', 'General taxpayer', '7720804666226278400', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7700197875671179264', 'catering and hotel category', 'general taxpayer', '7720882041353961472', '2019-01-23 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7700197875671179266', 'catering and hotel category', 'general taxpayer', '7720882041353961472', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7703053372673171456', 'High-tech', 'Small scale', '7722233303626055680', '2019-01-23 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7703053372673171457', 'High-tech', 'Small scale', '7722233303626055680', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709742385262698496', 'Service Category', 'General Taxpayer', '7722233895811448832', '2019-01-23 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709742385262698498', 'Service Category', 'General Taxpayer', '7722233895811448832', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745055683780608', 'High-tech', 'Small scale', '7722234507982700544', '2019-01-23 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745055683780609', 'Import and Export', 'Small Scale', '7722234507982700544', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745249439653888', 'Culture and Sports', 'General Taxpayer', '7722234927631204352', '2019-01-24 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745249439653889', 'High-tech', 'General taxpayer', '7722234927631204352', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745453266051072', 'High-tech', 'Small scale', '7722235550724423680', '2019-01-24 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745453266051073', 'Culture and Sports', 'Small Scale', '7722235550724423680', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745539848413184', 'Technology', 'General Taxpayer', '7722235921488314368', '2019-01-24 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745539848413185', 'High-tech', 'General taxpayer', '7722235921488314368', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745652603887616', 'High-tech', 'General taxpayer', '7722238233975881728', '2019-01-24 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745652603887617', 'Technology', 'General Taxpayer', '7722238233975881728', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745755528568832', 'Import and Export', 'General Taxpayer', '7722246644138409984', '2019-01-24 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745755528568833', 'Education Consulting', 'Small Scale', '7722246644138409984', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745892539047936', 'Education Consulting', 'General Taxpayer', '7722318634321346560', '2019-01-24 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709745892539047937', 'Import and Export', 'General Taxpayer', '7722318634321346560', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709746000127139840', 'Production', 'Small Scale', '7722318674321346586', '2019-01-24 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709746000127139841', 'Agriculture', 'General Taxpayer', '7722318674321346586', '2019-01-23 17:09:53');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709746447445467136', 'Agriculture', 'General taxpayer', '7722318974421546780', '2019-01-24 16:54:25');
INSERT INTO `demo`.`order_info` (`id`, `industry`, `nature_tax`, `customer_id`, `create_time`) VALUES ('7709746447445467137', 'Production', 'Small Scale', '7722318974421546780', '2019-01-23 17:09:53');

SQL statements written as required:

UPDATE order_info SET create_time = NOW();

Try to solve the problem

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;

Data duplication? No problem. Can’t we just add a GROUP BY to solve the problem? How can I be so clever, hahaha! ! ! But when I finished executing the SQL, I was confused again. The industry and tax nature in the query results were still not the latest. It seemed that I thought too much, so I should solve the problem honestly. . .

Find duplicate data

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;

The execution results are as follows:

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;

Hey, finally solved it. . .

Readers who are interested in more MySQL-related content can check out the following topics on this site: "MySQL query skills", "MySQL transaction operation skills", "MySQL stored procedure skills", "MySQL database lock related skills summary" and "MySQL common function summary"

I hope this article will be helpful to everyone's MySQL database design.

You may also be interested in:

MySQL implements multi-table association statistics (subquery statistics) example
A brief discussion on the implementation of multi-table unrelated query in MySQL
MySQL detailed explanation of multi-table association query

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