8 种最坑SQL语法，工作中踩过吗？-轻识

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来源：developer.aliyun.com/article/72501

# sql语句的执行顺序：

FROM<left_table>
ON<join_condition>
<join_type> JOIN<right_table>
WHERE<where_condition>
GROUP BY<group_by_list>
HAVING<having_condition>
SELECT
DISTINCT<select_list>
ORDER BY<order_by_condition>
LIMIT<limit_number>

# 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;

好吧，可能90%以上的DBA解决该问题就到此为止。但当 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。出现这种性能问题，多数情形下是程序员偷懒了。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;

在新设计下查询时间基本固定，不会随着数据量的增长而发生变化。

# 隐式转换

SQL语句中查询变量和字段定义类型不匹配是另一个常见的错误。比如下面的语句：

mysql> explain extended SELECT *      > FROM   my_balance b      > WHERE  b.bpn = 14000000123      >       AND b.isverified IS NULL ;mysql> show warnings;| Warning | 1739 | Cannot use ref access on index 'bpn' due to type or collation conversion on field 'bpn'

其中字段bpn的定义为varchar(20)，MySQL的策略是将字符串转换为数字之后再比较。函数作用于表字段，索引失效。

上述情况可能是应用程序框架自动填入的参数，而不是程序员的原意。现在应用框架很多很繁杂，使用方便的同时也小心它可能给自己挖坑。

# 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                         |+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+

# 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;

# 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           |+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+

# 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：

聚合子查询；
含有LIMIT的子查询；
UNION 或UNION ALL子查询；
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 |+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+

关于MySQL外部条件不能下推的详细解释说明请参考以前文章：MySQL · 性能优化 · 条件下推到物化表

# 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 DESClimit 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                                        |+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+

# 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)：

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                    GROUP BY resourcesid) c ON        a.resourceid = c.resourcesid

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

AliSQL即将推出WITH语法，敬请期待。

# 总结

数据库编译器产生执行计划，决定着SQL的实际执行方式。但是编译器只是尽力服务，所有数据库的编译器都不是尽善尽美的。

上述提到的多数场景，在其它数据库中也存在性能问题。了解数据库编译器的特性，才能避规其短处，写出高性能的SQL语句。

程序员在设计数据模型以及编写SQL语句时，要把算法的思想或意识带进来。

编写复杂SQL语句要养成使用WITH语句的习惯。简洁且思路清晰的SQL语句也能减小数据库的负担 ^^。

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