我还没有测试大DB，但我认为这可能比连接表更快:

SELECT *, Max(Id) FROM messages GROUP BY Name

试试这个:

SELECT jos_categories.title AS name,
       joined .catid,
       joined .title,
       joined .introtext
FROM   jos_categories
       INNER JOIN (SELECT *
                   FROM   (SELECT `title`,
                                  catid,
                                  `created`,
                                  introtext
                           FROM   `jos_content`
                           WHERE  `sectionid` = 6
                           ORDER  BY `id` DESC) AS yes
                   GROUP  BY `yes`.`catid` DESC
                   ORDER  BY `yes`.`created` DESC) AS joined
         ON( joined.catid = jos_categories.id )  

我还没有测试大DB，但我认为这可能比连接表更快:

SELECT *, Max(Id) FROM messages GROUP BY Name

Hi @Vijay Dev如果你的表消息包含Id，这是自动增加主键，然后在主键上获取最新的记录，你的查询应该如下所示:

SELECT m1.* FROM messages m1 INNER JOIN (SELECT max(Id) as lastmsgId FROM messages GROUP BY Name) m2 ON m1.Id=m2.lastmsgId

这个怎么样:

SELECT DISTINCT ON (name) *
FROM messages
ORDER BY name, id DESC;

我也有类似的问题(在postgresql tough上)，在1M的记录表上。这个解决方案需要1.7秒，而使用LEFT JOIN的解决方案需要44秒。 在我的例子中，我必须根据NULL值过滤您的名称字段的对应项，从而使性能更好0.2秒

MySQL 8.0现在支持窗口函数，就像几乎所有流行的SQL实现一样。使用这个标准语法，我们可以编写每组最大n个查询:

WITH ranked_messages AS (
  SELECT m.*, ROW_NUMBER() OVER (PARTITION BY name ORDER BY id DESC) AS rn
  FROM messages AS m
)
SELECT * FROM ranked_messages WHERE rn = 1;

这种方法和其他查找分组最大行的方法在MySQL手册中有说明。

以下是我在2009年写的关于这个问题的原始答案:

我这样写解:

SELECT m1.*
FROM messages m1 LEFT JOIN messages m2
 ON (m1.name = m2.name AND m1.id < m2.id)
WHERE m2.id IS NULL;

关于性能，一种解决方案或另一种解决方案可能更好，这取决于数据的性质。因此，您应该同时测试这两个查询，并在给定数据库的情况下使用性能更好的查询。

例如，我有一个StackOverflow八月数据转储的副本。我将使用它进行基准测试。Posts表中有1,114,357行。这是在我的Macbook Pro 2.40GHz的MySQL 5.0.75上运行的。

我将编写一个查询，为给定的用户ID(我的)查找最近的帖子。

首先在子查询中使用@Eric所展示的GROUP by技术:

SELECT p1.postid
FROM Posts p1
INNER JOIN (SELECT pi.owneruserid, MAX(pi.postid) AS maxpostid
            FROM Posts pi GROUP BY pi.owneruserid) p2
  ON (p1.postid = p2.maxpostid)
WHERE p1.owneruserid = 20860;

1 row in set (1 min 17.89 sec)

即使是EXPLAIN分析也需要超过16秒:

+----+-------------+------------+--------+----------------------------+-------------+---------+--------------+---------+-------------+
| id | select_type | table      | type   | possible_keys              | key         | key_len | ref          | rows    | Extra       |
+----+-------------+------------+--------+----------------------------+-------------+---------+--------------+---------+-------------+
|  1 | PRIMARY     | <derived2> | ALL    | NULL                       | NULL        | NULL    | NULL         |   76756 |             | 
|  1 | PRIMARY     | p1         | eq_ref | PRIMARY,PostId,OwnerUserId | PRIMARY     | 8       | p2.maxpostid |       1 | Using where | 
|  2 | DERIVED     | pi         | index  | NULL                       | OwnerUserId | 8       | NULL         | 1151268 | Using index | 
+----+-------------+------------+--------+----------------------------+-------------+---------+--------------+---------+-------------+
3 rows in set (16.09 sec)

现在使用我的LEFT JOIN技术生成相同的查询结果:

SELECT p1.postid
FROM Posts p1 LEFT JOIN posts p2
  ON (p1.owneruserid = p2.owneruserid AND p1.postid < p2.postid)
WHERE p2.postid IS NULL AND p1.owneruserid = 20860;

1 row in set (0.28 sec)

EXPLAIN分析表明这两个表都可以使用它们的索引:

+----+-------------+-------+------+----------------------------+-------------+---------+-------+------+--------------------------------------+
| id | select_type | table | type | possible_keys              | key         | key_len | ref   | rows | Extra                                |
+----+-------------+-------+------+----------------------------+-------------+---------+-------+------+--------------------------------------+
|  1 | SIMPLE      | p1    | ref  | OwnerUserId                | OwnerUserId | 8       | const | 1384 | Using index                          | 
|  1 | SIMPLE      | p2    | ref  | PRIMARY,PostId,OwnerUserId | OwnerUserId | 8       | const | 1384 | Using where; Using index; Not exists | 
+----+-------------+-------+------+----------------------------+-------------+---------+-------+------+--------------------------------------+
2 rows in set (0.00 sec)

下面是我Posts表的DDL:

CREATE TABLE `posts` (
  `PostId` bigint(20) unsigned NOT NULL auto_increment,
  `PostTypeId` bigint(20) unsigned NOT NULL,
  `AcceptedAnswerId` bigint(20) unsigned default NULL,
  `ParentId` bigint(20) unsigned default NULL,
  `CreationDate` datetime NOT NULL,
  `Score` int(11) NOT NULL default '0',
  `ViewCount` int(11) NOT NULL default '0',
  `Body` text NOT NULL,
  `OwnerUserId` bigint(20) unsigned NOT NULL,
  `OwnerDisplayName` varchar(40) default NULL,
  `LastEditorUserId` bigint(20) unsigned default NULL,
  `LastEditDate` datetime default NULL,
  `LastActivityDate` datetime default NULL,
  `Title` varchar(250) NOT NULL default '',
  `Tags` varchar(150) NOT NULL default '',
  `AnswerCount` int(11) NOT NULL default '0',
  `CommentCount` int(11) NOT NULL default '0',
  `FavoriteCount` int(11) NOT NULL default '0',
  `ClosedDate` datetime default NULL,
  PRIMARY KEY  (`PostId`),
  UNIQUE KEY `PostId` (`PostId`),
  KEY `PostTypeId` (`PostTypeId`),
  KEY `AcceptedAnswerId` (`AcceptedAnswerId`),
  KEY `OwnerUserId` (`OwnerUserId`),
  KEY `LastEditorUserId` (`LastEditorUserId`),
  KEY `ParentId` (`ParentId`),
  CONSTRAINT `posts_ibfk_1` FOREIGN KEY (`PostTypeId`) REFERENCES `posttypes` (`PostTypeId`)
) ENGINE=InnoDB;

评论者注意:如果你想用不同版本的MySQL，不同的数据集，或者不同的表设计来做另一个基准测试，你可以自己做。我已经展示了上面的技术。Stack Overflow在这里向您展示如何进行软件开发工作，而不是为您做所有的工作。