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08、MySQL进阶：索引优化案例实操

分类：MySQL进阶教程    2024-03-09    阅读(229)

文章目录

  • 生猛干货
  • DB Version
  • Table
  • Case 1 : 联合索引第一个字段用范围不一定会走索引
    • 优化一 强制走索引 force index(idx_name_age_position)
  • 优化二 覆盖索引优化
  • Case 2 : in和or在表数据量比较大的情况会走索引，在表记录不多的情况下会选择全表扫描
  • Case 3 : like KK% 一般情况都会走索引
    • 特殊例子
  • 搞定MySQL

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生猛干货

带你搞定MySQL实战，轻松对应海量业务处理及高并发需求，从容应对大场面试

DB Version

mysql> select version();
+------------+
| version()  |
+------------+
| 5.7.29-log |
+------------+
1 row in set

默认隔离级别 RR 可重复读

Table

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=1 DEFAULT CHARSET=utf8 COMMENT='员工记录表';

重点

1、 主键idPRIMARYKEY(id)；
2、 联合索引KEYidx_name_age_position(name,age,position)USINGBTREE；

我们向表里写入10万来条数据

*

Case 1 : 联合索引第一个字段用范围不一定会走索引

*

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 | 74      | NULL |    1 |        5 | Using index condition |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
1 row in set

mysql> EXPLAIN SELECT * FROM employees WHERE name > 'Artisan' 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       | ALL  | idx_name_age_position | NULL | NULL    | NULL | 100175 |      0.5 | Using where |
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+--------+----------+-------------+
1 row in set

mysql>

当然了，也不是所有的情况都不走索引， MySQL会基于Cost选择一个合适的 ，如果没有走索引，可能mysql内部可能觉得第一个字段就用范围，结果集应该很大，回表效率不高，还不如就全表扫描

如果没有走索引想要去优化的话怎么办呢？

优化一 强制走索引 force index(idx_name_age_position)

mysql> EXPLAIN SELECT * FROM employees force index(idx_name_age_position) WHERE name > 'Artisan' 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 | 74      | NULL | 50087 |        1 | Using index condition |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+-------+----------+-----------------------+
1 row in set

*

优化二 覆盖索引优化

mysql> EXPLAIN SELECT name , age , position  FROM employees WHERE name > 'Artisan' 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 | 74      | NULL | 50087 |        1 | Using where; Using index |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+-------+----------+--------------------------+
1 row in set

mysql>

*

name , age , position 是联合索引，在索引树上，同时索引树上的叶子节点还会关联一个主键id , 如果查询 * 的话，还要根据id去主键索引上去查找其他字段，需要回表， 如果仅查询二级索引树idx_name_age_position上的字段，那就无需回表操作了，效率自然高一些。

Case 2 : in和or在表数据量比较大的情况会走索引，在表记录不多的情况下会选择全表扫描

mysql> EXPLAIN SELECT * FROM employees WHERE name in ('LiLei','HanMeimei','Lucy') 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 | 140     | NULL |    3 |      100 | Using index condition |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
1 row in set

mysql> EXPLAIN SELECT * FROM employees WHERE (name = 'LiLei' or name = 'HanMeimei') 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 | 140     | NULL |    2 |      100 | Using index condition |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
1 row in set

*

再搞个小表 ，和 employees 一模一样哈，连索引也得一样，插入3条数据 。

CREATE TABLE employees_2 (
  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=1 DEFAULT CHARSET=utf8 COMMENT='员工记录表';

INSERT INTO employees_2(name,age,position,hire_time) VALUES('LiLei',22,'manager',NOW());
INSERT INTO employees_2(name,age,position,hire_time) VALUES('HanMeimei', 23,'dev',NOW());
INSERT INTO employees_2(name,age,position,hire_time) VALUES('Lucy',23,'dev',NOW());

*

mysql> EXPLAIN SELECT * FROM employees_2 WHERE name in ('LiLei','HanMeimei','Lucy') AND age = 22 AND position ='manager';  
+----+-------------+-------------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
| id | select_type | table       | partitions | type | possible_keys         | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | employees_2 | NULL       | ALL  | idx_name_age_position | NULL | NULL    | NULL |    3 |      100 | Using where |
+----+-------------+-------------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
1 row in set

mysql>

为什么呢？ 就几条数据的话， 结合B+树的结构， MySQL认为从根节点开始向下找，还不如直接从叶子节点从头开始扫描快呢

Case 3 : like KK% 一般情况都会走索引

结合索引树 ， like KK% 可以理解为就是按照 = KK 查询

mysql> EXPLAIN SELECT * FROM employees WHERE name like '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 | 140     | NULL |    1 |        5 | Using index condition |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
1 row in set

mysql> EXPLAIN SELECT * FROM employees_2 WHERE name like '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_2 | NULL       | range | idx_name_age_position | idx_name_age_position | 140     | NULL |    1 |    33.33 | Using index condition |
+----+-------------+-------------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
1 row in set

原因：索引下推 MySQL -索引下推 Index Condition Pushdown 初探

特殊例子

一般情况 ，但也不绝对。看下面这个例子

假设你这个表 的name字段 是以Artisan开头的，从Artisan1 到Artisan100000

*

再去like的话 ，mysql会基于cost，自主选择 ，比如如下走了全表扫描。

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搞定MySQL

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