mysql之—group by分组取字段最大值的示例代码详情：
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：<br>
+----+------+---------------+---------------------+ | 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：<br>
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：<br>
-- 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<br>（如果sql_mode开启了only_full_group_by，则不会执行成功。）
<br>
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<br>写法1<br>写一个子查询：<br>
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<br>再或者换一个写法：<br>
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<br>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。<br>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<br>5.5.50：<br>
+----+--------------------+-------+------+---------------+------+---------+------+------+-------------+ | 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：<br>
+----+--------------------+-------+------+---------------+------+---------+------------+------+-------------+ | 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<br>直接改成join性能会更加好：<br>
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：<br>
+------+---------------+---------------------+ | 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 | +------+---------------+---------------------+
注：如果要分组取最小值直接改对应函数和符号就行了。<br><br>
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