【本人秃顶程序员】8 种常被忽视的 SQL 错误用法

墨蓝 2022-03-10 17:27 333阅读 0赞

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**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 >

## 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;

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。

## 二、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。

## 三、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                         |
    +----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+

## 四、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;

## 五、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           |
    +----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+

## 六、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 |
    +----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+

## 七、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                                        |
    +----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+

## 八、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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## 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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