MySQL的JOIN（四）：JOIN優化實踐之快速匹配

這篇博文講述如何優化掃描速度。我們通過MySQL的JOIN（二）：JOIN原理得知了兩張表的JOIN操作就是不斷從驅動表中取出記錄，然后查找出被驅動表中與之匹配的記錄並連接。這個過程的實質就是查詢操作，想要優化查詢操作，建索引是最常用的方式。那索引怎么建呢？我們來討論下，首先插入測試數據。

    CREATE TABLE t1 (
        id INT PRIMARY KEY AUTO_INCREMENT,
        type INT
    );
    SELECT COUNT(*) FROM t1;
    +----------+
    | COUNT(*) |
    +----------+
    |   110000 |
    +----------+
    CREATE TABLE t2 (
        id INT PRIMARY KEY AUTO_INCREMENT,
        type INT
    );
    SELECT COUNT(*) FROM t2;
    +----------+
    | COUNT(*) |
    +----------+
    |      100 |
    +----------+

左連接

左連接中，左表是驅動表，右表是被驅動表。想要快速查找被驅動表中匹配的記錄，所以我們可以在右表建索引，從而提高連接性能。

    -- 首先兩個表都沒建索引
    EXPLAIN SELECT * FROM t1 LEFT JOIN t2 ON t1.type=t2.type;
    +----+-------+------+------+--------+----------------------------------------------------+
    | id | table | type | key  | rows   | Extra                                              |
    +----+-------+------+------+--------+----------------------------------------------------+
    |  1 | t1    | ALL  | NULL | 110428 | NULL                                               |
    |  1 | t2    | ALL  | NULL |    100 | Using where; Using join buffer (Block Nested Loop) |
    +----+-------+------+------+--------+----------------------------------------------------+

    -- 嘗試在左表建立索引，改進不大
    CREATE INDEX idx_type ON t1(type);
    EXPLAIN SELECT * FROM t1 LEFT JOIN t2 ON t1.type=t2.type;
    +----+-------+-------+----------+--------+----------------------------------------------------+
    | id | table | type  | key      | rows   | Extra                                              |
    +----+-------+-------+----------+--------+----------------------------------------------------+
    |  1 | t1    | index | idx_type | 110428 | Using index                                        |
    |  1 | t2    | ALL   | NULL     |    100 | Using where; Using join buffer (Block Nested Loop) |
    +----+-------+-------+----------+--------+----------------------------------------------------+


    -- 嘗試在右表建立索引，效果拔群，Using index!!!
    DROP INDEX idx_type ON t1;
    CREATE INDEX idx_type ON t2(type);
    EXPLAIN SELECT * FROM t1 LEFT JOIN t2 ON t1.type=t2.type;
    +----+-------+------+---------------+----------+--------+-------------+
    | id | table | type | possible_keys | key      | rows   | Extra       |
    +----+-------+------+---------------+----------+--------+-------------+
    |  1 | t1    | ALL  | NULL          | NULL     | 110428 | NULL        |
    |  1 | t2    | ref  | idx_type      | idx_type |      1 | Using index |
    +----+-------+------+---------------+----------+--------+-------------+

右連接

右連接中，右表是驅動表，左表是被驅動表，想要快速查找被驅動表中匹配的記錄，所以我們可以在左表建索引，從而提高連接性能。

    DROP INDEX idx_type ON t2;
    -- 兩個表都沒有索引
    EXPLAIN SELECT * FROM t1 RIGHT JOIN t2 ON t1.type=t2.type;
    +----+-------+------+------+--------+----------------------------------------------------+
    | id | table | type | key  | rows   | Extra                                              |
    +----+-------+------+------+--------+----------------------------------------------------+
    |  1 | t2    | ALL  | NULL |    100 | NULL                                               |
    |  1 | t1    | ALL  | NULL | 110428 | Using where; Using join buffer (Block Nested Loop) |
    +----+-------+------+------+--------+----------------------------------------------------+


    -- 在右邊建立索引，改進不大
    CREATE INDEX idx_type ON t2(type);
    EXPLAIN SELECT * FROM t1 RIGHT JOIN t2 ON t1.type=t2.type;
    +----+-------+-------+---------------+----------+--------+----------------------------------------------------+
    | id | table | type  | possible_keys | key      | rows   | Extra                                              |
    +----+-------+-------+---------------+----------+--------+----------------------------------------------------+
    |  1 | t2    | index | NULL          | idx_type |    100 | Using index                                        |
    |  1 | t1    | ALL   | NULL          | NULL     | 110428 | Using where; Using join buffer (Block Nested Loop) |
    +----+-------+-------+---------------+----------+--------+----------------------------------------------------+


    -- 嘗試在左邊建立索引，效果拔群！
    DROP INDEX idx_type ON t2;
    CREATE INDEX idx_type ON t1(type);
    EXPLAIN SELECT * FROM t1 RIGHT JOIN t2 ON t1.type=t2.type;
    +----+-------+------+---------------+--------------+------+-------------+
    | id | table | type | possible_keys | ref          | rows | Extra       |
    +----+-------+------+---------------+--------------+------+-------------+
    |  1 | t2    | ALL  | NULL          | NULL         |  100 | NULL        |
    |  1 | t1    | ref  | idx_type      | test.t2.type |    5 | Using index |
    +----+-------+------+---------------+--------------+------+-------------+

內連接

我們知道，MySQL Optimizer會對內連接做優化，不管誰內連接誰，都是用小表驅動大表，所以如果要優化內連接，可以在大表上建立索引，以提高連接性能。

另外注意一點，在小表上建立索引時，MySQL Optimizer會認為用大表驅動小表效率更快，轉而用大表驅動小表。

對內連接小表驅動大表的優化策略不清楚的話，可以看MySQL的JOIN（三）：JOIN優化實踐之內循環的次數

    DROP INDEX idx_type ON t1;
    -- 兩個表都沒有索引，t2驅動t1
    EXPLAIN SELECT * FROM t1 INNER JOIN t2 ON t1.type=t2.type;
    +----+-------+------+------+--------+----------------------------------------------------+
    | id | table | type | key  | rows   | Extra                                              |
    +----+-------+------+------+--------+----------------------------------------------------+
    |  1 | t2    | ALL  | NULL |    100 | NULL                                               |
    |  1 | t1    | ALL  | NULL | 110428 | Using where; Using join buffer (Block Nested Loop) |
    +----+-------+------+------+--------+----------------------------------------------------+

    -- 在t2表上建立索引，MySQL的Optimizer發現后，用大表驅動了小表
    CREATE INDEX idx_type ON t2(type);
    EXPLAIN SELECT * FROM t1 INNER JOIN t2 ON t1.type=t2.type;
    +----+-------+------+----------+--------+-------------+
    | id | table | type | key      | rows   | Extra       |
    +----+-------+------+----------+--------+-------------+
    |  1 | t1    | ALL  | NULL     | 110428 | Using where |
    |  1 | t2    | ref  | idx_type |      1 | Using index |
    +----+-------+------+----------+--------+-------------+


    -- 在t1表上建立索引，再加上t1是大表，符合“小表驅動大表”的原則，性能比上面的語句要好
    DROP INDEX idx_type ON t2;
    CREATE INDEX idx_type ON t1(type);
    EXPLAIN SELECT * FROM t1 INNER JOIN t2 ON t1.type=t2.type;
    +----+-------+------+---------------+----------+------+-------------+
    | id | table | type | possible_keys | key      | rows | Extra       |
    +----+-------+------+---------------+----------+------+-------------+
    |  1 | t2    | ALL  | NULL          | NULL     |  100 | Using where |
    |  1 | t1    | ref  | idx_type      | idx_type |    5 | Using index |
    +----+-------+------+---------------+----------+------+-------------+

三表連接

上面都是兩表連接，三表連接也是一樣的，找出驅動表和被驅動表，在被驅動表上建立索引，即可提高連接性能。

總結

想要從快速匹配的角度優化JOIN，首先就是找出誰是驅動表，誰是被驅動表，然后在被驅動表上建立索引即可。