02-Explain详解与索引最佳实践（tuling）

2020年12月14日

01 explain工具介绍

使用explain关键字可以模拟优化器执行sql语句，分析你的查询语句或是结构的性能瓶颈。在select语句之前增加explain关键字，mysql会在查询上设置一个标记，执行查询会返回执行计划的信息，而不是执行这条sql。

note：explain执行计划。
note：如果from中包含子查询，仍会执行该子查询，将结果放入临时表中。

02 创建explain分析的sql

DROP TABLE IF EXISTS `actor`;
CREATE TABLE `actor` (
  `id` int(11) NOT NULL,
  `name` varchar(45) DEFAULT NULL,
  `update_time` datetime DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

INSERT INTO `actor` (`id`, `name`, `update_time`) 
VALUES (1,'a','2017-12-22 15:27:18'), 
(2,'b','2017-12-22 15:27:18'), 
(3,'c','2017-12-22 15:27:18');

DROP TABLE IF EXISTS `film`;
CREATE TABLE `film` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `name` varchar(10) DEFAULT NULL,
  PRIMARY KEY (`id`),
  KEY `idx_name` (`name`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

INSERT INTO `film` (`id`, `name`) VALUES (3,'film0'),(1,'film1'),(2,'film2');

DROP TABLE IF EXISTS `film_actor`;
CREATE TABLE `film_actor` (
  `id` int(11) NOT NULL,
  `film_id` int(11) NOT NULL,
  `actor_id` int(11) NOT NULL,
  `remark` varchar(255) DEFAULT NULL,
  PRIMARY KEY (`id`),
  KEY `idx_film_actor_id` (`film_id`,`actor_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

INSERT INTO `film_actor` (`id`, `film_id`, `actor_id`) VALUES (1,1,1),(2,1,2),(3,2,1);

mysql> explain select * from actor;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------+
|  1 | SIMPLE      | actor | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |   100.00 | NULL  |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

在查询中的每个表会输出一行，如果有两个表通过join连接查询，那么会输出两行。表的意义相当广泛：可以是子查询、一个union结果等。

explain有两个变种：

(1) explain extended：会在explain的基础上额外提供一些查询优化的信息。紧随其后通过show warnings命令可以得到优化后的查询语句，从而看出优化器优化了什么。额外还有filtered列，是一个百分比的值，$rows×filtered/100$可以估算出将要和explain中前一个表进行连接的行数（前一个表指explain中的id值比当前表id值小的表）。

mysql> explain extended select * from film where id = 1;
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type  | possible_keys | key     | key_len | ref   | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | film  | NULL       | const | PRIMARY       | PRIMARY | 4       | const |    1 |   100.00 | NULL  |
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
1 row in set, 2 warnings (0.00 sec)

mysql> show warnings;
+---------+------+----------------------------------------------------------------------------------+
| Level   | Code | Message                                                                          |
+---------+------+----------------------------------------------------------------------------------+
| Warning | 1681 | 'EXTENDED' is deprecated and will be removed in a future release.                |
| Note    | 1003 | /* select#1 */ select '1' AS `id`,'film1' AS `name` from `tuling`.`film` where 1 |
+---------+------+----------------------------------------------------------------------------------+
2 rows in set (0.00 sec)

(2) explain partitions：相比explain多了个partitions字段，如果查询是基于分区表的话，会显示查询将访问的分区。

mysql> explain partitions select * from film where id = 1;
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type  | possible_keys | key     | key_len | ref   | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | film  | NULL       | const | PRIMARY       | PRIMARY | 4       | const |    1 |   100.00 | NULL  |
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
1 row in set, 2 warnings (0.00 sec)

# 实际操作发现，加不加(1)或(2)效果都是一样的，怎么回事？因为5.7版本explain现在都包含了，5.6则没有。
mysql> explain select * from film where id = 1;
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type  | possible_keys | key     | key_len | ref   | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | film  | NULL       | const | PRIMARY       | PRIMARY | 4       | const |    1 |   100.00 | NULL  |
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

03 explain中的列

note：必须掌握select_type、type、key、Extra。

（3.1）id列

id列的编号是select的序列号，有几个select就有几个id，并且id的顺序是按select出现的顺序增长的。id列越大执行优先级越高，id相同则从上往下执行，id为NULL最后执行。

（3.2）select_type列

select_type表示对应行是简单还是复杂的查询。

mysql将select查询分为简单查询（SIMPLE）和复杂查询（PRIMARY）。复杂查询分为三类：简单子查询、派生表（from语句中的子查询）、union查询。

(1)simple：简单查询；查询不包含子查询和union。

mysql> explain select * from film where id=2;
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type  | possible_keys | key     | key_len | ref   | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | film  | NULL       | const | PRIMARY       | PRIMARY | 4       | const |    1 |   100.00 | NULL  |
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

(2)primary：复杂查询中最外层的select。

(3)subquery：包含在select中的子查询（不在from子句中）。

(4)derived：包含在from子句中的子查询。MySQL会将结果存放在一个临时表中，也称为派生表（derived的英文含义）

# 关闭mysql5.7新特性对衍生表的合并优化
mysql> set session optimizer_switch='derived_merge=off';
Query OK, 0 rows affected (0.00 sec)

mysql> explain select (select 1 from actor where id = 1) from (select * from film where id = 1) der;
+----+-------------+------------+------------+--------+---------------+---------+---------+-------+------+----------+-------------+
| id | select_type | table      | partitions | type   | possible_keys | key     | key_len | ref   | rows | filtered | Extra       |
+----+-------------+------------+------------+--------+---------------+---------+---------+-------+------+----------+-------------+
|  1 | PRIMARY     | <derived3> | NULL       | system | NULL          | NULL    | NULL    | NULL  |    1 |   100.00 | NULL        |
|  3 | DERIVED     | film       | NULL       | const  | PRIMARY       | PRIMARY | 4       | const |    1 |   100.00 | NULL        |
|  2 | SUBQUERY    | actor      | NULL       | const  | PRIMARY       | PRIMARY | 4       | const |    1 |   100.00 | Using index |
+----+-------------+------------+------------+--------+---------------+---------+---------+-------+------+----------+-------------+
3 rows in set, 1 warning (0.00 sec)

# 还原默认配置
mysql> set session optimizer_switch='derived_merge=on';
Query OK, 0 rows affected (0.00 sec)

(5)union：在union中的第二个和随后的select。

mysql> explain select 1 union all select 1;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+----------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra          |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+----------------+
|  1 | PRIMARY     | NULL  | NULL       | NULL | NULL          | NULL | NULL    | NULL | NULL |     NULL | No tables used |
|  2 | UNION       | NULL  | NULL       | NULL | NULL          | NULL | NULL    | NULL | NULL |     NULL | No tables used |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+----------------+
2 rows in set, 1 warning (0.00 sec)

（3.3）table列

这一列表示explain的一行正在访问哪个表。

当from子句中有子查询时，table列是<derivenN>格式，表示当前查询依赖id=N的查询，于是先执行id=N的查询。

当有union时，UNION RESULT的table列的值为<union1,2>，1和2表示参与union的select行id。

// TODO: (这个要手动试一下)

（3.4）type列

这一列表示关联类型或访问类型，即MySQL决定如何查找表中的行，查找数据行记录的大概范围。

依次从最优到最差分别为：system > const > eq_ref > ref > range > index > ALL；一般来说，得保证查询达到range级别，最好达到ref。（index级别勉强也可以，但是ALL就要进行优化了）

NULL：mysql能够在优化阶段分解查询语句，在执行阶段用不着再访问表或索引。例如：在索引列中选取最小值，可以单独查找索引来完成，不需要在执行时访问表。

mysql> explain select min(id) from film;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra                        |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+
|  1 | SIMPLE      | NULL  | NULL       | NULL | NULL          | NULL | NULL    | NULL | NULL |     NULL | Select tables optimized away |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+
1 row in set, 1 warning (0.00 sec)

const, system：mysql能对查询的某部分进行优化并将其转化成一个常量（可以看show warnings的结果）。用于primary key或unique key的所有列与常数比较时，所以表最多有一个匹配行，读取1次，速度比较快。system是const的特例，表里只有一条元组匹配时为system。

mysql> explain extended select * from (select * from film where id = 1) tmp;
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type  | possible_keys | key     | key_len | ref   | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | film  | NULL       | const | PRIMARY       | PRIMARY | 4       | const |    1 |   100.00 | NULL  |
+----+-------------+-------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
1 row in set, 2 warnings (0.00 sec)

mysql> show warnings;
+---------+------+----------------------------------------------------------------------------------+
| Level   | Code | Message                                                                          |
+---------+------+----------------------------------------------------------------------------------+
| Warning | 1681 | 'EXTENDED' is deprecated and will be removed in a future release.                |
| Note    | 1003 | /* select#1 */ select '1' AS `id`,'film1' AS `name` from `tuling`.`film` where 1 |
+---------+------+----------------------------------------------------------------------------------+
2 rows in set (0.00 sec)

eq_ref：primary key或unique key索引的所有部分被连接使用，最多只会返回一条符合条件的记录。这可能是在const之外最好的联接类型了，简单的select查询不会出现这种type。

note：eq_ref，即关联的索引是primary key或unique key，这里关联的是film.id（主键索引）。

mysql> explain select * from film_actor left join film on film_actor.film_id = film.id;
+----+-------------+------------+------------+--------+---------------+---------+---------+---------------------------+------+----------+-------+
| id | select_type | table      | partitions | type   | possible_keys | key     | key_len | ref                       | rows | filtered | Extra |
+----+-------------+------------+------------+--------+---------------+---------+---------+---------------------------+------+----------+-------+
|  1 | SIMPLE      | film_actor | NULL       | ALL    | NULL          | NULL    | NULL    | NULL                      |    3 |   100.00 | NULL  |
|  1 | SIMPLE      | film       | NULL       | eq_ref | PRIMARY       | PRIMARY | 4       | tuling.film_actor.film_id |    1 |   100.00 | NULL  |
+----+-------------+------------+------------+--------+---------------+---------+---------+---------------------------+------+----------+-------+
2 rows in set, 1 warning (0.00 sec)

ref：相比eq_ref，不使用唯一索引，而是使用普通索引或者唯一性索引的部分前缀，索引要和某个值相比较，可能会找到多个符合条件的行。

(1)简单select查询；(name是普通索引，非唯一索引)

mysql> explain select * from film where name = 'film1';
+----+-------------+-------+------------+------+---------------+----------+---------+-------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key      | key_len | ref   | rows | filtered | Extra       |
+----+-------------+-------+------------+------+---------------+----------+---------+-------+------+----------+-------------+
|  1 | SIMPLE      | film  | NULL       | ref  | idx_name      | idx_name | 33      | const |    1 |   100.00 | Using index |
+----+-------------+-------+------------+------+---------------+----------+---------+-------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

(2)关联表查询；(idx_film_actor_id是film_id和actor_id的联合索引，这里使用到了film_actor的左边前缀film_id部分。)

note：这里关联的是film_actor.film_id（唯一索引的部分前缀）。

mysql> explain select film_id from film left join film_actor on film.id = film_actor.film_id;
+----+-------------+------------+------------+-------+-------------------+-------------------+---------+----------------+------+----------+-------------+
| id | select_type | table      | partitions | type  | possible_keys     | key               | key_len | ref            | rows | filtered | Extra       |
+----+-------------+------------+------------+-------+-------------------+-------------------+---------+----------------+------+----------+-------------+
|  1 | SIMPLE      | film       | NULL       | index | NULL              | idx_name          | 33      | NULL           |    3 |   100.00 | Using index |
|  1 | SIMPLE      | film_actor | NULL       | ref   | idx_film_actor_id | idx_film_actor_id | 4       | tuling.film.id |    1 |   100.00 | Using index |
+----+-------------+------------+------------+-------+-------------------+-------------------+---------+----------------+------+----------+-------------+
2 rows in set, 1 warning (0.00 sec)

range：范围扫描通常出现在in()，between，>，<，>=等操作中。使用一个索引来检索给定范围的行。

mysql> explain select * from actor where id > 1;
+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type  | possible_keys | key     | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | actor | NULL       | range | PRIMARY       | PRIMARY | 4       | NULL |    2 |   100.00 | Using where |
+----+-------------+-------+------------+-------+---------------+---------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

index：扫描全表索引，这通常比ALL快一些。（全索引扫描）

mysql> explain select * from film;
+----+-------------+-------+------------+-------+---------------+----------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type  | possible_keys | key      | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------+------------+-------+---------------+----------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | film  | NULL       | index | NULL          | idx_name | 33      | NULL |    3 |   100.00 | Using index |
+----+-------------+-------+------------+-------+---------------+----------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

ALL：即全表扫描，意味着mysql需要从头到尾去查找所需要的行。通常情况下这需要增加索引来进行优化了。

mysql> explain select * from actor;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------+
|  1 | SIMPLE      | actor | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |   100.00 | NULL  |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

（3.5）possible_keys列

这一列显示查询可能使用哪些索引来查找。explain时可能出现possible_keys有列，而key显示NULL的情况，这种情况是因为表中数据不多，mysql认为索引对此查询帮助不大，选择了全表查询。

如果该列是NULL，则没有相关的索引。在这种情况下，可以通过检查where子句看是否可以创造一个适当的索引来提高查询性能，然后用explain查看效果。

（3.6）key列

这一列显示mysql实际采用哪个索引来优化对该表的访问。如果没有使用索引，则该列是NULL。如果想强制mysql使用或忽视possible_keys列中的索引，在查询中使用force index、ignore index。

（3.7）key_len列

这一列显示了mysql在索引里使用的字节数，通过这个值可以算出具体使用了索引中的哪些列。

举例来说，film_actor的联合索引idx_film_actor_id由film_id和actor_id两个int列组成，并且每个int是4字节。通过结果中的key_len=4可推断出查询使用了第一个列：film_id列来执行索引查找。

mysql> explain select * from film_actor where film_id = 2;
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------+
| id | select_type | table      | partitions | type | possible_keys     | key               | key_len | ref   | rows | filtered | Extra |
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | film_actor | NULL       | ref  | idx_film_actor_id | idx_film_actor_id | 4       | const |    1 |   100.00 | NULL  |
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

key_len计算规则如下：

字符串
- char(n)：n字节长度
- varchar(n)：2字节存储字符串长度，如果是utf-8，则长度3n+2
数值类型
- tinyint：1B
- smallint：2B
- int：4B
- bigint：8B
时间类型
- date：3B
- timestamp：4B
- datetime：8B
如果字段允许为NULL，需要1字节记录是否为NULL

索引最大长度是768字节，当字符串过长时，mysql会做一个类似左前缀索引的处理，将前半部分的字符提取出来做索引。

（3.8）ref列

这一列显示了在key列记录的索引中，表查找值所用到的列或常量，常见的有：const（常量），字段名（例如:film.id）

mysql> explain select film_id from film_actor where film_id = 1;
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------------+
| id | select_type | table      | partitions | type | possible_keys     | key               | key_len | ref   | rows | filtered | Extra       |
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------------+
|  1 | SIMPLE      | film_actor | NULL       | ref  | idx_film_actor_id | idx_film_actor_id | 4       | const |    2 |   100.00 | Using index |
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

mysql> explain select film_id from film left join film_actor on film.id = film_actor.film_id;
+----+-------------+------------+------------+-------+-------------------+-------------------+---------+----------------+------+----------+-------------+
| id | select_type | table      | partitions | type  | possible_keys     | key               | key_len | ref            | rows | filtered | Extra       |
+----+-------------+------------+------------+-------+-------------------+-------------------+---------+----------------+------+----------+-------------+
|  1 | SIMPLE      | film       | NULL       | index | NULL              | idx_name          | 33      | NULL           |    3 |   100.00 | Using index |
|  1 | SIMPLE      | film_actor | NULL       | ref   | idx_film_actor_id | idx_film_actor_id | 4       | tuling.film.id |    1 |   100.00 | Using index |
+----+-------------+------------+------------+-------+-------------------+-------------------+---------+----------------+------+----------+-------------+
2 rows in set, 1 warning (0.00 sec)

（3.9）rows列

这一列是mysql估计要读取并检测的行数，注意这个不是结果集里的行数。

（3.10）Extra列

这一列展示的是额外信息。常见的重要值如下：

note：Extra列结果集是不确定的，与mysql版本、执行的数据量、内部的优化相关联，仅供参考。

Using index：查询的列被索引覆盖，并且where筛选条件是索引的前导列，是性能高的表现。一般是使用了覆盖索引（查询的字段都在索引里面，比如film_id就是索引）。对于InnoDB来说，如果是辅助索引性能会有不少提高。

mysql> explain select film_id from film_actor where film_id = 1;
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------------+
| id | select_type | table      | partitions | type | possible_keys     | key               | key_len | ref   | rows | filtered | Extra       |
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------------+
|  1 | SIMPLE      | film_actor | NULL       | ref  | idx_film_actor_id | idx_film_actor_id | 4       | const |    2 |   100.00 | Using index |
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

# 加了remark，而remark不是索引，所以就不使用覆盖索引（从联合索引的树结构来理解其性能问题）
mysql>  explain select film_id, remark from film_actor where film_id = 1;
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------+
| id | select_type | table      | partitions | type | possible_keys     | key               | key_len | ref   | rows | filtered | Extra |
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | film_actor | NULL       | ref  | idx_film_actor_id | idx_film_actor_id | 4       | const |    2 |   100.00 | NULL  |
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

Using where：使用where语句来处理结果，查询的列未被索引覆盖，where筛选条件非索引的前导列。

mysql> explain select * from actor where name = 'a';
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | actor | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |    33.33 | Using where |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

Using where; Using index：查询的列被索引覆盖，并且where筛选条件是索引列之一但是不是索引的前导列，意味着无法直接通过索引查找来查询到符合条件的数据。

mysql> explain select film_id from film_actor where actor_id = 1;
+----+-------------+------------+------------+-------+---------------+-------------------+---------+------+------+----------+--------------------------+
| id | select_type | table      | partitions | type  | possible_keys | key               | key_len | ref  | rows | filtered | Extra                    |
+----+-------------+------------+------------+-------+---------------+-------------------+---------+------+------+----------+--------------------------+
|  1 | SIMPLE      | film_actor | NULL       | index | NULL          | idx_film_actor_id | 8       | NULL |    3 |    33.33 | Using where; Using index |
+----+-------------+------------+------------+-------+---------------+-------------------+---------+------+------+----------+--------------------------+
1 row in set, 1 warning (0.00 sec)

NULL：查询的列未被索引覆盖，并且where筛选条件是索引的前导列，意味着用到了索引，但是部分字段未被索引覆盖，必须通过“回表”来实现，不是纯粹地用到了索引，也不是完全没用到索引。

mysql> explain select * from film_actor where film_id = 1;
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------+
| id | select_type | table      | partitions | type | possible_keys     | key               | key_len | ref   | rows | filtered | Extra |
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | film_actor | NULL       | ref  | idx_film_actor_id | idx_film_actor_id | 4       | const |    2 |   100.00 | NULL  |
+----+-------------+------------+------------+------+-------------------+-------------------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

Using index condition：与Using where类似，查询的列不完全被索引覆盖，where条件中是一个前导列的范围；

mysql> explain select * from film_actor where film_id > 1;
+----+-------------+------------+------------+-------+-------------------+-------------------+---------+------+------+----------+-----------------------+
| id | select_type | table      | partitions | type  | possible_keys     | key               | key_len | ref  | rows | filtered | Extra                 |
+----+-------------+------------+------------+-------+-------------------+-------------------+---------+------+------+----------+-----------------------+
|  1 | SIMPLE      | film_actor | NULL       | range | idx_film_actor_id | idx_film_actor_id | 4       | NULL |    1 |   100.00 | Using index condition |
+----+-------------+------------+------------+-------+-------------------+-------------------+---------+------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)

Using temporary：mysql需要创建一张临时表来处理查询。出现这种情况一般是要进行优化的，首先是想到用索引来优化。

(1)actor.name没有索引，此时创建了张临时表来distinct。

mysql> explain select distinct name from actor;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-----------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra           |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-----------------+
|  1 | SIMPLE      | actor | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |   100.00 | Using temporary |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-----------------+
1 row in set, 1 warning (0.00 sec)

(2)film.name建立了idx_name索引，此时查询时extra是using index，没有用临时表。（直接在索引树结构里面去重，而actor.name必须把查出的结果集放入到临时表里面，再去重。最简单的方法，加索引就可以不使用临时表了。）

mysql> explain select distinct name from film;
+----+-------------+-------+------------+-------+---------------+----------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type  | possible_keys | key      | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------+------------+-------+---------------+----------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | film  | NULL       | index | idx_name      | idx_name | 33      | NULL |    3 |   100.00 | Using index |
+----+-------------+-------+------------+-------+---------------+----------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

Using filesort：mysql会对结果使用一个外部索引排序（数据较小时从内存排序，否则需要在磁盘完成排序），而不是按索引次序从表里读取行。此时mysql会根据联接类型浏览所有符合条件的记录，并保存排序关键字和行指针，然后排序关键字并按顺序检索行信息。这种情况下一般也是要考虑使用索引来优化的。

(1)actor.name未创建索引，会浏览actor整个表，保存排序关键字name和对应的id，然后排序name并检索行记录。

mysql> explain select * from actor order by name;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+----------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra          |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+----------------+
|  1 | SIMPLE      | actor | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |   100.00 | Using filesort |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+----------------+
1 row in set, 1 warning (0.00 sec)

(2)film.name建立了idx_name索引，此时查询时extra是using index。（最简单的方法，加索引。）

mysql> explain select * from film order by name;
+----+-------------+-------+------------+-------+---------------+----------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type  | possible_keys | key      | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------+------------+-------+---------------+----------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | film  | NULL       | index | NULL          | idx_name | 33      | NULL |    3 |   100.00 | Using index |
+----+-------------+-------+------------+-------+---------------+----------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

Select tables optimized away：使用某些聚合函数（比如max、min）来访问存在索引的某个字段。（执行效率也是比较高的。）

mysql> explain select min(id) from film;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra                        |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+
|  1 | SIMPLE      | NULL  | NULL       | NULL | NULL          | NULL | NULL    | NULL | NULL |     NULL | Select tables optimized away |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+
1 row in set, 1 warning (0.00 sec)

04 索引最佳实践

实验表

CREATE TABLE `employees` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `name` varchar(24) NOT NULL DEFAULT '' COMMENT '姓名',
  `age` int(11) NOT NULL DEFAULT '0' COMMENT '年龄',
  `position` varchar(20) NOT NULL DEFAULT '' COMMENT '职位',
  `hire_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '入职时间',
  PRIMARY KEY (`id`),
  KEY `idx_name_age_position` (`name`,`age`,`position`) USING BTREE
) ENGINE=InnoDB AUTO_INCREMENT=4 DEFAULT CHARSET=utf8 COMMENT='员工记录表';

INSERT INTO employees(name,age,position,hire_time) VALUES('LiLei',22,'manager',NOW());
INSERT INTO employees(name,age,position,hire_time) VALUES('HanMeimei', 23,'dev',NOW());
INSERT INTO employees(name,age,position,hire_time) VALUES('Lucy',23,'dev',NOW());

（4.1）全值匹配

# key_len = 74：表示只走name索引（3*24+2=74）
mysql> EXPLAIN SELECT * FROM employees WHERE name= 'LiLei';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
| id | select_type | table     | partitions | type | possible_keys         | key                   | key_len | ref   | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | employees | NULL       | ref  | idx_name_age_position | idx_name_age_position | 74      | const |    1 |   100.00 | NULL  |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

# key_len = 78：表示走了name索引74 + age索引4，74 + 4 = 78
mysql> EXPLAIN SELECT * FROM employees WHERE name= 'LiLei' AND age = 22;
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------+------+----------+-------+
| id | select_type | table     | partitions | type | possible_keys         | key                   | key_len | ref         | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------+------+----------+-------+
|  1 | SIMPLE      | employees | NULL       | ref  | idx_name_age_position | idx_name_age_position | 78      | const,const |    1 |   100.00 | NULL  |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

# key_len = 140：表示走了name索引74 + age索引4 + position索引62；
# 通过key_len也可以反推使用的索引，可在联合索引中计算出使用了哪些索引。key_len越长，使用的索引也越多，过滤数据越高效。
mysql> EXPLAIN SELECT * FROM employees WHERE name= 'LiLei' AND age = 22 AND position ='manager';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
| id | select_type | table     | partitions | type | possible_keys         | key                   | key_len | ref               | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
|  1 | SIMPLE      | employees | NULL       | ref  | idx_name_age_position | idx_name_age_position | 140     | const,const,const |    1 |   100.00 | NULL  |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

（4.2）最佳左前缀法则

如果索引了多列，要遵守最左前缀法则。指的是查询从索引的最左前列开始并且不跳过索引中的列。

mysql> EXPLAIN SELECT * FROM employees WHERE age = 22 AND position ='manager';
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |    33.33 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

mysql> EXPLAIN SELECT * FROM employees WHERE position = 'manager';
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |    33.33 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

mysql> EXPLAIN SELECT * FROM employees WHERE name = 'LiLei';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
| id | select_type | table     | partitions | type | possible_keys         | key                   | key_len | ref   | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | employees | NULL       | ref  | idx_name_age_position | idx_name_age_position | 74      | const |    1 |   100.00 | NULL  |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

note：结合联合索引的树结构来思考，如果只知道后面的两个索引，而不知道第1个索引，是无法定位到哪个节点的（因为索引树的排序是对第1个索引排序，然后再对第2个索引排序，以此类推），要进行全表扫描进行查找，即索引失效。

（4.3）不在索引列上做任何操作（计算、函数、（自动or手动）类型转换），会导致索引失效而转向全表扫描。

mysql> EXPLAIN SELECT * FROM employees WHERE name = 'LiLei';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
| id | select_type | table     | partitions | type | possible_keys         | key                   | key_len | ref   | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | employees | NULL       | ref  | idx_name_age_position | idx_name_age_position | 74      | const |    1 |   100.00 | NULL  |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

# 结合索引树来思考，对于第1个索引，只截取了3位，是没法进行定位的，只得扫描。
# 其实有时候是可以进行扫描的，比如left和like%一样，但是其他函数一般就不行，实际上mysql在设计的时候，只要加了函数，就不走索引。
mysql> EXPLAIN SELECT * FROM employees WHERE left(name,3) = 'LiLei';
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |   100.00 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

note：如何优化？假设业务场景是只想查看某一天入职的员工。

# 给hire_time增加一个普通索引
mysql> ALTER TABLE `employees` ADD INDEX `idx_hire_time` (`hire_time`) USING BTREE;
Query OK, 0 rows affected (0.01 sec)

# 使用了函数就不走索引
mysql> EXPLAIN select * from employees where date(hire_time) = '2018-09-30';
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |   100.00 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

# 转化为日期范围查询，会走索引
mysql> EXPLAIN select * from employees where hire_time >= '2018-09-30?00:00:00'and hire_time <= '2018-09-30?23:59:59';
+----+-------------+-----------+------------+-------+---------------+---------------+---------+------+------+----------+-----------------------+
| id | select_type | table     | partitions | type  | possible_keys | key           | key_len | ref  | rows | filtered | Extra                 |
+----+-------------+-----------+------------+-------+---------------+---------------+---------+------+------+----------+-----------------------+
|  1 | SIMPLE      | employees | NULL       | range | idx_hire_time | idx_hire_time | 4       | NULL |    1 |   100.00 | Using index condition |
+----+-------------+-----------+------------+-------+---------------+---------------+---------+------+------+----------+-----------------------+
1 row in set, 6 warnings (0.00 sec)

# 还原最初索引状态
mysql> ALTER TABLE `employees` DROP INDEX `idx_hire_time`;
Query OK, 0 rows affected (0.00 sec)

（4.4）存储引擎不能使用索引中范围条件右边的列

mysql> EXPLAIN SELECT * FROM employees WHERE name= 'LiLei' AND age = 22 AND position ='manager';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
| id | select_type | table     | partitions | type | possible_keys         | key                   | key_len | ref               | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
|  1 | SIMPLE      | employees | NULL       | ref  | idx_name_age_position | idx_name_age_position | 140     | const,const,const |    1 |   100.00 | NULL  |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

# key_len = 78：走了前面两个索引； 
# 结合索引树来分析：前面两个索引定位到一个范围，而第3个索引要在这个范围内进行扫描。（范围右边的列一律不走索引）
mysql> EXPLAIN SELECT * FROM employees WHERE name= 'LiLei' AND age > 22 AND position ='manager';
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
| id | select_type | table     | partitions | type  | possible_keys         | key                   | key_len | ref  | rows | filtered | Extra                 |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
|  1 | SIMPLE      | employees | NULL       | range | idx_name_age_position | idx_name_age_position | 78      | NULL |    1 |    33.33 | Using index condition |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)

（4.5）尽量使用覆盖索引（只访问索引的查询（索引列包含查询列）），减少select * 语句。

mysql> EXPLAIN SELECT name,age FROM employees WHERE name= 'LiLei' AND age = 23 AND position ='manager';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys         | key                   | key_len | ref               | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ref  | idx_name_age_position | idx_name_age_position | 140     | const,const,const |    1 |   100.00 | Using index |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

mysql> EXPLAIN SELECT * FROM employees WHERE name= 'LiLei' AND age = 23 AND position ='manager';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
| id | select_type | table     | partitions | type | possible_keys         | key                   | key_len | ref               | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
|  1 | SIMPLE      | employees | NULL       | ref  | idx_name_age_position | idx_name_age_position | 140     | const,const,const |    1 |   100.00 | NULL  |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

（4.6）mysql在使用不等于（!=或者<>）的时候无法使用索引会导致全表扫描。

mysql> EXPLAIN SELECT * FROM employees WHERE name != 'LiLei';
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys         | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | idx_name_age_position | NULL | NULL    | NULL |    3 |    66.67 | Using where |
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

（4.7）is null，is not null也无法使用索引。

note：所以在设计表的时候来个default值，不要设置为null。

mysql> EXPLAIN SELECT * FROM employees WHERE name is null;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra            |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------+
|  1 | SIMPLE      | NULL  | NULL       | NULL | NULL          | NULL | NULL    | NULL | NULL |     NULL | Impossible WHERE |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------+
1 row in set, 1 warning (0.00 sec)

（4.8）like以通配符开头（'$abc...'）mysql索引失效会变成全表扫描操作。

mysql> EXPLAIN SELECT * FROM employees WHERE name like '%Lei';
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |    33.33 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

Q：解决like'%字符串%'索引不被使用的方法？

a）使用覆盖索引，查询字段必须是建立覆盖索引字段。

mysql> EXPLAIN SELECT name,age,position FROM employees WHERE name like '%Lei%';
+----+-------------+-----------+------------+-------+---------------+-----------------------+---------+------+------+----------+--------------------------+
| id | select_type | table     | partitions | type  | possible_keys | key                   | key_len | ref  | rows | filtered | Extra                    |
+----+-------------+-----------+------------+-------+---------------+-----------------------+---------+------+------+----------+--------------------------+
|  1 | SIMPLE      | employees | NULL       | index | NULL          | idx_name_age_position | 140     | NULL |    3 |    33.33 | Using where; Using index |
+----+-------------+-----------+------------+-------+---------------+-----------------------+---------+------+------+----------+--------------------------+
1 row in set, 1 warning (0.00 sec)

b）当覆盖索引指向的字段是varchar(380)及380以上的字段时，覆盖索引会失效！

（4.9）字符串不加单引号索引失效。

mysql> EXPLAIN SELECT * FROM employees WHERE name = '1000';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
| id | select_type | table     | partitions | type | possible_keys         | key                   | key_len | ref   | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
|  1 | SIMPLE      | employees | NULL       | ref  | idx_name_age_position | idx_name_age_position | 74      | const |    1 |   100.00 | NULL  |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)

# 不加单引号，则mysql默认会在字段前面加一个函数将int转为字符串，加了函数就不走索引。
mysql> EXPLAIN SELECT * FROM employees WHERE name = 1000;
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys         | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | idx_name_age_position | NULL | NULL    | NULL |    3 |    33.33 | Using where |
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
1 row in set, 3 warnings (0.00 sec)

（4.10）少用or，用它连接时很多情况下索引会失效，主键索引有时生效，有时不生效，跟数据量有关，具体还得看mysql的查询优化结果。

mysql> EXPLAIN SELECT * FROM employees WHERE name = 'LiLei' or name = 'HanMeimei';
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys         | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | idx_name_age_position | NULL | NULL    | NULL |    3 |    66.67 | Using where |
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

(4.11) 范围查询优化

为了便于实验，利用以下脚本生成sql语句。

#!/bin/bash
echo "请输入创建sql语句的数量："
read number
for (( i=7;i<$number;i++ ))
        do
        age=`echo $RANDOM | cut -c 1-2`
        echo "insert into employees(id,name,age,position,hire_time)
		values('$i','user${i}','${age}','dev',now());" >>sql.txt
        done

# 40w数据量用于测试
mysql> select count(*) from employees;
+----------+
| count(*) |
+----------+
|   432825 |
+----------+
1 row in set (0.06 sec)

# 这里发现InnoDB查询行数的时候，走了联合索引，这解答了之前的一个疑惑。
mysql> explain select count(*) from employees;
+----+-------------+-----------+------------+-------+---------------+-----------------------+---------+------+--------+----------+-------------+
| id | select_type | table     | partitions | type  | possible_keys | key                   | key_len | ref  | rows   | filtered | Extra       |
+----+-------------+-----------+------------+-------+---------------+-----------------------+---------+------+--------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | index | NULL          | idx_name_age_position | 140     | NULL | 432390 |   100.00 | Using index |
+----+-------------+-----------+------------+-------+---------------+-----------------------+---------+------+--------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

# 给年龄值添加单值索引
mysql> alter table employees add index idx_age (age) using btree;
Query OK, 0 rows affected (1.01 sec)

# 范围查找，不走索引
mysql> explain select * from employees where age >=1 and age <= 2000;  
+----+-------------+-----------+------------+------+---------------+------+---------+------+--------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows   | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+--------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | idx_age       | NULL | NULL    | NULL | 432390 |    50.00 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+--------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

# age范围1~74，不走索引。
mysql> explain select * from employees where age >=1 and age <= 74;
+----+-------------+-----------+------------+------+---------------+------+---------+------+--------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows   | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+--------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | idx_age       | NULL | NULL    | NULL | 432390 |    50.00 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+--------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

# age范围74~2000，不走索引。
mysql> explain select * from employees where age >=74 and age <= 2000;
+----+-------------+-----------+------------+------+---------------+------+---------+------+--------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows   | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+--------+----------+-------------+
|  1 | SIMPLE      | employees | NULL       | ALL  | idx_age       | NULL | NULL    | NULL | 432390 |    17.54 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+--------+----------+-------------+
1 row in set, 1 warning (0.00 sec)

# age=75这是试出来的一个界限，这提供了一个优化的思路，对范围进行拆分。
mysql> explain select * from employees where age >=75 and age <= 2000;
+----+-------------+-----------+------------+-------+---------------+---------+---------+------+-------+----------+-----------------------+
| id | select_type | table     | partitions | type  | possible_keys | key     | key_len | ref  | rows  | filtered | Extra                 |
+----+-------------+-----------+------------+-------+---------------+---------+---------+------+-------+----------+-----------------------+
|  1 | SIMPLE      | employees | NULL       | range | idx_age       | idx_age | 4       | NULL | 71960 |   100.00 | Using index condition |
+----+-------------+-----------+------------+-------+---------------+---------+---------+------+-------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)

# 查询得到max(age)=99，这个并不是分界值。
mysql> select max(age) from employees;
+----------+
| max(age) |
+----------+
|       99 |
+----------+
1 row in set (0.08 sec)

# 删除索引，还原最初的索引状态
mysql> alter table employees drop index idx_age;
Query OK, 0 rows affected (0.01 sec)

没走索引原因：mysql内部优化器会根据检索比例、表大小等多个因素整体评估是否使用索引。比如这个例子，可能是由于单次数据量查询过大导致优化器最终选择不走索引。

优化方法：可以将大的范围拆分成多个小范围。

05 总结

note：like kk%相当于=常量，%kk和%kk%相当于范围。

posted @ 2020-12-13 21:56 ddhhdd 阅读(245) 评论(0) 收藏举报

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