MySQL之——GROUP BY分组取字段最大值

转载自：http://blog.csdn.net/l1028386804/article/details/54657412

假设有一个业务场景，需要查询用户登录记录信息，其中表结构如下：

CREATE TABLE `tb` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `uid` int(11) NOT NULL,
  `ip` varchar(16) NOT NULL,
  `login_time` datetime,
  PRIMARY KEY (`id`),
  KEY (`uid`)
);

再来点测试数据：

INSERT INTO tb SELECT null, 1001, '192.168.1.1', '2017-01-21 16:30:47';
INSERT INTO tb SELECT null, 1003, '192.168.1.153', '2017-01-21 19:30:51';
INSERT INTO tb SELECT null, 1001, '192.168.1.61', '2017-01-21 16:50:41';
INSERT INTO tb SELECT null, 1002, '192.168.1.31', '2017-01-21 18:30:21';
INSERT INTO tb SELECT null, 1002, '192.168.1.66', '2017-01-21 19:12:32';
INSERT INTO tb SELECT null, 1001, '192.168.1.81', '2017-01-21 19:53:09';
INSERT INTO tb SELECT null, 1001, '192.168.1.231', '2017-01-21 19:55:34';

表数据情况：

+----+------+---------------+---------------------+
| id | uid  | ip            | login_time          |
+----+------+---------------+---------------------+
| 1  | 1001 | 192.168.1.1   | 2017-01-21 16:30:47 |
| 2  | 1003 | 192.168.1.153 | 2017-01-21 19:30:51 |
| 3  | 1001 | 192.168.1.61  | 2017-01-21 16:50:41 |
| 4  | 1002 | 192.168.1.31  | 2017-01-21 18:30:21 |
| 5  | 1002 | 192.168.1.66  | 2017-01-21 19:12:32 |
| 6  | 1001 | 192.168.1.81  | 2017-01-21 19:53:09 |
| 7  | 1001 | 192.168.1.231 | 2017-01-21 19:55:34 |
+----+------+---------------+---------------------+

如果只需要针对用户查出其最后登录的时间，可以简单写出：

SELECT uid, max(login_time)
FROM tb
GROUP BY uid;

+------+---------------------+
| uid  | max(login_time)       |
+------+---------------------+
| 1001 | 2017-01-21 19:55:34 |
| 1002 | 2017-01-21 19:12:32 |
| 1003 | 2017-01-21 19:30:51 |
+------+---------------------+

若还需要查询用户最后登录时的其他信息，就不能用这种sql写了：

-- 错误写法
SELECT uid, ip, max(login_time)
FROM tb
GROUP BY uid;
-- 错误写法

这样的语句是非SQL标准的，虽然能够在MySQL数据库中执行成功，但返回的却是未知的
（如果sql_mode开启了only_full_group_by，则不会执行成功。）
可能ip字段会取uid分组前的第一个row的值，显然不是所需信息
写法1
写一个子查询：

SELECT a.uid, a.ip, a.login_time
FROM tb a
WHERE a.login_time in (
SELECT max(login_time)
FROM tb
GROUP BY uid);

写法2
再或者换一个写法：

SELECT a.uid, a.ip, a.login_time
FROM tb a
WHERE a.login_time = (
SELECT max(login_time)
FROM tb
WHERE a.uid = uid);

顺便测了一下
在5.6以前的版本中，写法②这条sql在大数据量的情况下，执行计划不理想，目测性能不佳。
在5.6及以后的版本中，写法②这条sql会快很多，执行计划也有了改变
5.5.50：

+----+--------------------+-------+------+---------------+------+---------+------+------+-------------+
| id | select_type        | table | type | possible_keys | key  | key_len | ref  | rows | Extra       |
+----+--------------------+-------+------+---------------+------+---------+------+------+-------------+
| 1  | PRIMARY            | a     | ALL  | NULL             | NULL  | NULL      | NULL | 7    | Using where |
| 2  | DEPENDENT SUBQUERY | tb    | ALL  | uid           | NULL  | NULL      | NULL | 7    | Using where |
+----+--------------------+-------+------+---------------+------+---------+------+------+-------------+

5.6.30：

+----+--------------------+-------+------+---------------+------+---------+------------+------+-------------+
| id | select_type        | table  | type | possible_keys | key  | key_len | ref       | rows  | Extra      |
+----+--------------------+-------+------+---------------+------+---------+------------+------+-------------+
| 1  | PRIMARY            | a     | ALL  | NULL              | NULL | NULL      | NULL        | 7    | Using where |
| 2  | DEPENDENT SUBQUERY | tb    | ref  | uid           | uid  | 4       | test.a.uid | 1    | NULL           |
+----+--------------------+-------+------+---------------+------+---------+------------+------+-------------+

写法3
直接改成join性能会更加好：

SELECT a.uid, a.ip, a.login_time
FROM (SELECT uid, max(login_time) login_time
FROM tb
GROUP BY uid
) b JOIN tb a ON a.uid = b.uid AND a.login_time = b.login_time;

当然，结果都相同：

+------+---------------+---------------------+
| uid  | ip            | login_time          |
+------+---------------+---------------------+
| 1003 | 192.168.1.153 | 2017-01-21 19:30:51 |
| 1002 | 192.168.1.66  | 2017-01-21 19:12:32 |
| 1001 | 192.168.1.231 | 2017-01-21 19:55:34 |
+------+---------------+---------------------+