MySQL多列索引的应用

多列索引

咱们常常听到一些人说"把WHERE条件里的列都加上索引"，其实这个建议很是错误。在多个列上创建单独的索引大部分状况下并不能提升MySQL的查询性能。MySQL在5.0以后引入了一种叫“索引合并”（index merge）的策略，必定程度上可使用表上的多个单列索引来定位指定的行。可是当服务器对多个索引作联合操做时，一般须要耗费大量CPU和内存资源在算法的缓存、排序和合并操做上，特别是当其中有些索引的选择性不高，须要合并扫描大量的数据的时候。
这个时候，咱们须要一个多列索引。

案例

建立一个测试数据库和数据表：

CREATE DATABASE IF NOT EXISTS db_test default charset utf8 COLLATE utf8_general_ci; 
use db_test;
CREATE TABLE payment (  
    id         INT UNSIGNED NOT NULL AUTO_INCREMENT,  
    staff_id  INT UNSIGNED NOT NULL,  
    customer_id INT UNSIGNED NOT NULL,  
    PRIMARY KEY (id)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

利用存储过程插入1000w行随机数据(表引擎能够先设置为MyISAM，而后改成InnoDB):

DROP PROCEDURE IF EXISTS add_payment;  
DELIMITER //
    create PROCEDURE add_payment(in num INT)
    BEGIN
        DECLARE rowid INT DEFAULT 0;
        SET @exesql = 'INSERT INTO payment(staff_id, customer_id) values (?, ?)';
        WHILE rowid < num DO
            SET @staff_id = (1 + FLOOR(5000*RAND()) ); 
            SET @customer_id = (1 + FLOOR(500000*RAND()));
            SET rowid = rowid + 1;
            prepare stmt FROM @exesql;
            EXECUTE stmt USING @staff_id, @customer_id;            
        END WHILE;
    END //
DELIMITER ;

或者你能够直接下载使用个人测试数据(也是利用上面的存储过程,可是我以后调整了数据):
测试数据

添加两个单列索引(执行过程要花点时间,建议分开一句一句执行):

ALTER TABLE `payment` ADD INDEX idx_customer_id(`customer_id`);
ALTER TABLE `payment` ADD INDEX idx_staff_id(`staff_id`);

查询一条数据利用到两个列的索引:

select count(*)  from payment  where staff_id =  2205  AND customer_id =  93112;

查看执行计划:

mysql> explain select count(*)  from payment  where staff_id =  2205  AND customer_id =  93112;
+----+-------------+---------+-------------+------------------------------+------------------------------+---------+------+-------+-------------------------------------------------------------------------+
| id | select_type | table   | type        | possible_keys                | key                          | key_len | ref  | rows  | Extra                                                                   |
+----+-------------+---------+-------------+------------------------------+------------------------------+---------+------+-------+-------------------------------------------------------------------------+
|  1 | SIMPLE      | payment | index_merge | idx_customer_id,idx_staff_id | idx_staff_id,idx_customer_id | 4,4     | NULL | 11711 | Using intersect(idx_staff_id,idx_customer_id); Using where; Using index |
+----+-------------+---------+-------------+------------------------------+------------------------------+---------+------+-------+-------------------------------------------------------------------------+
1 row in set (0.00 sec)

能够看到type是index_merge,Extra中提示Using intersect(idx_staff_id,idx_customer_id);
这即是索引合并,利用两个索引,而后合并两个结果(取交集或者并集或者二者都有)
查询结果:

mysql> select count(*)  from payment  where staff_id =  2205  AND customer_id =  93112 ;
+----------+
| count(*) |
+----------+
|   178770 |
+----------+
1 row in set (0.12 sec)

而后删除以上索引,添加多列索引:

ALTER TABLE payment DROP INDEX idx_customer_id;
ALTER TABLE payment DROP INDEX idx_staff_id;
ALTER TABLE `payment` ADD INDEX idx_customer_id_staff_id(`customer_id`, `staff_id`);

注意,多列索引很关注索引列的顺序(由于customer_id的选择性更大,因此把它放前面)
查询:

mysql> select count(*)  from payment  where staff_id =  2205  AND customer_id =  93112;
+----------+
| count(*) |
+----------+
|   178770 |
+----------+
1 row in set (0.05 sec)

发现多列索引加快的查询(这里数据量仍是较小,更大的时候比较更明显)

注意

多列索引的列顺序相当重要，如何选择索引的列顺序有一个经验法则:将选择性最高的列放到索引最前列（可是不是绝对的）。经验法则考虑全局的基数和选择性，而不是某个具体的查询：

mysql> select count(DISTINCT staff_id) / count(*) AS staff_id_selectivity, count(DISTINCT customer_id) / count(*) AS customer_id_selectivity, count(*) from payment\G;
*************************** 1. row ***************************
   staff_id_selectivity: 0.0005
customer_id_selectivity: 0.0500
               count(*): 10000000
1 row in set (6.29 sec)

customer_id的选择性更高，因此将它做为索引列的第一位。
多列索引只能匹配最左前缀，也就是说：

select * from payment  where staff_id =  2205  AND customer_id =  93112 ;
select count(*)  from payment  where  customer_id =  93112 ;

能够利用索引，可是

select * from payment  where staff_id =  2205 ;

不能利用索引。