复杂SQL优化实例

待我称王封你为后i 2023-10-12 11:24 111阅读 0赞

### SQL语句的执行顺序： ###

![在这里插入图片描述][5ec479a8ec274909a95a32bccb67c342.png_pic_center]

### 执行计划指标查看 ###

![在这里插入图片描述][309adaa0a22949b6bd8fde4c4965de8e.png_pic_center]

### 优化实例一 ###

#### LIMIT 语句 ####

分页查询是最常用的场景之一，但也通常也是最容易出问题的地方。比如对于下面简单的语句，一般 DBA 想到的办法是在 type, name, create\_time 字段上加组合索引。这样条件排序都能有效的利用到索引，性能迅速提升。

SELECT *
    FROM   operation
    WHERE  type = 'SQLStats'
           AND name = 'SlowLog'
    ORDER  BY create_time
    LIMIT  1000, 10;

当 LIMIT 子句变成 “LIMIT 1000000,10” 时，程序员仍然会抱怨：我只取10条记录为什么还是慢？  
要知道数据库也并不知道第1000000条记录从什么地方开始，即使有索引也需要从头计算一次。  
在前端数据浏览翻页，或者大数据分批导出等场景下，是可以将上一页的最大值当成参数作为查询条件的。SQL 重新设计如下：

SELECT   *
    FROM     operation
    WHERE    type = 'SQLStats'
    AND      name = 'SlowLog'
    AND      create_time > '2017-03-16 14:00:00'
    ORDER BY create_time limit 10;

### 优化实例二 ###

#### 关联更新、删除 ####

虽然 MySQL5.6 引入了物化特性，但需要特别注意它目前仅仅针对查询语句的优化。对于更新或删除需要手工重写成 JOIN。

比如下面 UPDATE 语句，MySQL 实际执行的是循环/嵌套子查询（DEPENDENT SUBQUERY)，其执行时间可想而知。

UPDATE operation o
    SET    status = 'applying'
    WHERE  o.id IN (SELECT id
                    FROM   (SELECT o.id,
                                   o.status
                            FROM   operation o
                            WHERE  o.group = 123
                                   AND o.status NOT IN ( 'done' )
                            ORDER  BY o.parent,
                                      o.id
                            LIMIT  1) t);

执行计划：

+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
    | id | select_type        | table | type  | possible_keys | key     | key_len | ref   | rows | Extra                                               |
    +----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
    | 1  | PRIMARY            | o     | index |               | PRIMARY | 8       |       | 24   | Using where; Using temporary                        |
    | 2  | DEPENDENT SUBQUERY |       |       |               |         |         |       |      | Impossible WHERE noticed after reading const tables |
    | 3  | DERIVED            | o     | ref   | idx_2,idx_5   | idx_5   | 8       | const | 1    | Using where; Using filesort                         |
    +----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+

重写为 JOIN 之后，子查询的选择模式从 DEPENDENT SUBQUERY 变成 DERIVED，执行速度大大加快，从7秒降低到2毫秒。

UPDATE operation o
           JOIN  (SELECT o.id,
                                o.status
                         FROM   operation o
                         WHERE  o.group = 123
                                AND o.status NOT IN ( 'done' )
                         ORDER  BY o.parent,
                                   o.id
                         LIMIT  1) t
             ON o.id = t.id
    SET    status = 'applying'

执行计划简化为：

+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+
    | id | select_type | table | type | possible_keys | key   | key_len | ref   | rows | Extra                                               |
    +----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+
    | 1  | PRIMARY     |       |      |               |       |         |       |      | Impossible WHERE noticed after reading const tables |
    | 2  | DERIVED     | o     | ref  | idx_2,idx_5   | idx_5 | 8       | const | 1    | Using where; Using filesort                         |
    +----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+

### 优化实例三 ###

#### 混合排序 ####

MySQL 不能利用索引进行混合排序。但在某些场景，还是有机会使用特殊方法提升性能的。

SELECT *
    FROM   my_order o
           INNER JOIN my_appraise a ON a.orderid = o.id
    ORDER  BY a.is_reply ASC,
              a.appraise_time DESC
    LIMIT  0, 20

执行计划显示为全表扫描：

+----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+
    | id | select_type | table | type   | possible_keys     | key     | key_len | ref      | rows    | Extra
    +----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+
    |  1 | SIMPLE      | a     | ALL    | idx_orderid | NULL    | NULL    | NULL    | 1967647 | Using filesort |
    |  1 | SIMPLE      | o     | eq_ref | PRIMARY     | PRIMARY | 122     | a.orderid |       1 | NULL           |
    +----+-------------+-------+--------+---------+---------+---------+-----------------+---------+-+

由于 is\_reply 只有0和1两种状态，我们按照下面的方法重写后，执行时间从1.58秒降低到2毫秒。

SELECT *
    FROM   ((SELECT *
             FROM   my_order o
                    INNER JOIN my_appraise a
                            ON a.orderid = o.id
                               AND is_reply = 0
             ORDER  BY appraise_time DESC
             LIMIT  0, 20)
            UNION ALL
            (SELECT *
             FROM   my_order o
                    INNER JOIN my_appraise a
                            ON a.orderid = o.id
                               AND is_reply = 1
             ORDER  BY appraise_time DESC
             LIMIT  0, 20)) t
    ORDER  BY  is_reply ASC,
              appraisetime DESC
    LIMIT  20;

### 优化实例四 ###

#### EXISTS语句 ####

MySQL 对待 EXISTS 子句时，仍然采用嵌套子查询的执行方式。如下面的 SQL 语句：

SELECT *
    FROM   my_neighbor n
           LEFT JOIN my_neighbor_apply sra
                  ON n.id = sra.neighbor_id
                     AND sra.user_id = 'xxx'
    WHERE  n.topic_status < 4
           AND EXISTS(SELECT 1
                      FROM   message_info m
                      WHERE  n.id = m.neighbor_id
                             AND m.inuser = 'xxx')
           AND n.topic_type <> 5

执行计划为：

+----+--------------------+-------+------+-----+------------------------------------------+---------+-------+---------+ -----+
    | id | select_type        | table | type | possible_keys     | key   | key_len | ref   | rows    | Extra   |
    +----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+
    |  1 | PRIMARY            | n     | ALL  |  | NULL     | NULL    | NULL  | 1086041 | Using where                   |
    |  1 | PRIMARY            | sra   | ref  |  | idx_user_id | 123     | const |       1 | Using where          |
    |  2 | DEPENDENT SUBQUERY | m     | ref  |  | idx_message_info   | 122     | const |       1 | Using index condition; Using where |
    +----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+

去掉 exists 更改为 join，能够避免嵌套子查询，将执行时间从1.93秒降低为1毫秒。

SELECT *
    FROM   my_neighbor n
           INNER JOIN message_info m
                   ON n.id = m.neighbor_id
                      AND m.inuser = 'xxx'
           LEFT JOIN my_neighbor_apply sra
                  ON n.id = sra.neighbor_id
                     AND sra.user_id = 'xxx'
    WHERE  n.topic_status < 4
           AND n.topic_type <> 5

新的执行计划：

+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+
    | id | select_type | table | type   | possible_keys     | key       | key_len | ref   | rows | Extra                 |
    +----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+
    |  1 | SIMPLE      | m     | ref    | | idx_message_info   | 122     | const    |    1 | Using index condition |
    |  1 | SIMPLE      | n     | eq_ref | | PRIMARY   | 122     | ighbor_id |    1 | Using where      |
    |  1 | SIMPLE      | sra   | ref    | | idx_user_id | 123     | const     |    1 | Using where           |
    +----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+

### 优化实例五 ###

#### 条件下推 ####

外部查询条件不能够下推到复杂的视图或子查询的情况有：

1、聚合子查询；

2、含有 LIMIT 的子查询；

3、UNION 或 UNION ALL 子查询；

4、输出字段中的子查询；

如下面的语句，从执行计划可以看出其条件作用于聚合子查询之后：

SELECT *
    FROM   (SELECT target,
                   Count(*)
            FROM   operation
            GROUP  BY target) t
    WHERE  target = 'rm-xxxx'
    +----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+
    | id | select_type | table      | type  | possible_keys | key         | key_len | ref   | rows | Extra       |
    +----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+
    |  1 | PRIMARY     | <derived2> | ref   | <auto_key0>   | <auto_key0> | 514     | const |    2 | Using where |
    |  2 | DERIVED     | operation  | index | idx_4         | idx_4       | 519     | NULL  |   20 | Using index |
    +----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+

确定从语义上查询条件可以直接下推后，重写如下：

SELECT target,
           Count(*)
    FROM   operation
    WHERE  target = 'rm-xxxx'
    GROUP  BY target

执行计划变为：

+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
    | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
    +----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
    | 1 | SIMPLE | operation | ref | idx_4 | idx_4 | 514 | const | 1 | Using where; Using index |
    +----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+

### 优化实例六 ###

#### 提前缩小范围 ####

先上初始 SQL 语句：

SELECT *
    FROM   my_order o
           LEFT JOIN my_userinfo u
                  ON o.uid = u.uid
           LEFT JOIN my_productinfo p
                  ON o.pid = p.pid
    WHERE  ( o.display = 0 )
           AND ( o.ostaus = 1 )
    ORDER  BY o.selltime DESC
    LIMIT  0, 15

该SQL语句原意是：先做一系列的左连接，然后排序取前15条记录。从执行计划也可以看出，最后一步估算排序记录数为90万，时间消耗为12秒。

+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+
    | id | select_type | table | type   | possible_keys | key     | key_len | ref             | rows   | Extra                                              |
    +----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+
    |  1 | SIMPLE      | o     | ALL    | NULL          | NULL    | NULL    | NULL            | 909119 | Using where; Using temporary; Using filesort       |
    |  1 | SIMPLE      | u     | eq_ref | PRIMARY       | PRIMARY | 4       | o.uid |      1 | NULL                                               |
    |  1 | SIMPLE      | p     | ALL    | PRIMARY       | NULL    | NULL    | NULL            |      6 | Using where; Using join buffer (Block Nested Loop) |
    +----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+

由于最后 WHERE 条件以及排序均针对最左主表，因此可以先对 my\_order 排序提前缩小数据量再做左连接。SQL 重写后如下，执行时间缩小为1毫秒左右。

SELECT *
    FROM (
    SELECT *
    FROM   my_order o
    WHERE  ( o.display = 0 )
           AND ( o.ostaus = 1 )
    ORDER  BY o.selltime DESC
    LIMIT  0, 15
    ) o
         LEFT JOIN my_userinfo u
                  ON o.uid = u.uid
         LEFT JOIN my_productinfo p
                  ON o.pid = p.pid
    ORDER BY  o.selltime DESC
    limit 0, 15

再检查执行计划：子查询物化后（select\_type=DERIVED)参与 JOIN。虽然估算行扫描仍然为90万，但是利用了索引以及 LIMIT 子句后，实际执行时间变得很小。

+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
    | id | select_type | table      | type   | possible_keys | key     | key_len | ref   | rows   | Extra                                              |
    +----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
    |  1 | PRIMARY     | <derived2> | ALL    | NULL          | NULL    | NULL    | NULL  |     15 | Using temporary; Using filesort                    |
    |  1 | PRIMARY     | u          | eq_ref | PRIMARY       | PRIMARY | 4       | o.uid |      1 | NULL                                               |
    |  1 | PRIMARY     | p          | ALL    | PRIMARY       | NULL    | NULL    | NULL  |      6 | Using where; Using join buffer (Block Nested Loop) |
    |  2 | DERIVED     | o          | index  | NULL          | idx_1   | 5       | NULL  | 909112 | Using where                                        |
    +----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+

### 优化实例七 ###

#### 中间结果集下推 ####

再来看下面这个已经初步优化过的例子(左连接中的主表优先作用查询条件)：

那么该语句还存在其它问题吗？不难看出子查询 c 是全表聚合查询，在表数量特别大的情况下会导致整个语句的性能下降。

其实对于子查询 c，左连接最后结果集只关心能和主表 resourceid 能匹配的数据。因此我们可以重写语句如下，执行时间从原来的2秒下降到2毫秒。

SELECT    a.*,
              c.allocated
    FROM      (
                       SELECT   resourceid
                       FROM     my_distribute d
                       WHERE    isdelete = 0
                       AND      cusmanagercode = '1234567'
                       ORDER BY salecode limit 20) a
    LEFT JOIN
              (
                       SELECT   resourcesid， sum(ifnull(allocation, 0) * 12345) allocated
                       FROM     my_resources r,
                                (
                                         SELECT   resourceid
                                         FROM     my_distribute d
                                         WHERE    isdelete = 0
                                         AND      cusmanagercode = '1234567'
                                         ORDER BY salecode limit 20) a
                       WHERE    r.resourcesid = a.resourcesid
                       GROUP BY resourcesid) c
    ON        a.resourceid = c.resourcesid

但是子查询 a 在我们的SQL语句中出现了多次。这种写法不仅存在额外的开销，还使得整个语句显的繁杂。使用 WITH 语句再次重写：

WITH a AS
    (
             SELECT   resourceid
             FROM     my_distribute d
             WHERE    isdelete = 0
             AND      cusmanagercode = '1234567'
             ORDER BY salecode limit 20)
    SELECT    a.*,
              c.allocated
    FROM      a
    LEFT JOIN
              (
                       SELECT   resourcesid， sum(ifnull(allocation, 0) * 12345) allocated
                       FROM     my_resources r,
                                a
                       WHERE    r.resourcesid = a.resourcesid
                       GROUP BY resourcesid) c
    ON        a.resourceid = c.resourcesid

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