MySQL多列索引的應用

多列索引

咱們常常聽到一些人說"把WHERE條件裏的列都加上索引"，其實這個建議很是錯誤。在多個列上創建單獨的索引大部分狀況下並不能提升MySQL的查詢性能。MySQL在5.0以後引入了一種叫「索引合併」（index merge）的策略，必定程度上可使用表上的多個單列索引來定位指定的行。可是當服務器對多個索引作聯合操做時，一般須要耗費大量CPU和內存資源在算法的緩存、排序和合並操做上，特別是當其中有些索引的選擇性不高，須要合併掃描大量的數據的時候。
這個時候，咱們須要一個多列索引。

案例

建立一個測試數據庫和數據表：

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;

利用存儲過程插入1000w行隨機數據(表引擎能夠先設置爲MyISAM，而後改成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 ;

或者你能夠直接下載使用個人測試數據(也是利用上面的存儲過程,可是我以後調整了數據):
測試數據

添加兩個單列索引(執行過程要花點時間,建議分開一句一句執行):

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

查詢一條數據利用到兩個列的索引:

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

查看執行計劃:

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)

能夠看到type是index_merge,Extra中提示Using intersect(idx_staff_id,idx_customer_id);
這即是索引合併,利用兩個索引,而後合併兩個結果(取交集或者並集或者二者都有)
查詢結果:

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

而後刪除以上索引,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,多列索引很關注索引列的順序(由於customer_id的選擇性更大,因此把它放前面)
查詢:

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

發現多列索引加快的查詢(這裏數據量仍是較小,更大的時候比較更明顯)

注意

多列索引的列順序相當重要，如何選擇索引的列順序有一個經驗法則:將選擇性最高的列放到索引最前列（可是不是絕對的）。經驗法則考慮全局的基數和選擇性，而不是某個具體的查詢：

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的選擇性更高，因此將它做爲索引列的第一位。
多列索引只能匹配最左前綴，也就是說：

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

能夠利用索引，可是

select * from payment  where staff_id =  2205 ;

不能利用索引。