简单谈谈MySQL的loose index scan

(编辑：jimmy 日期: 2024/11/16 浏览：3 次 )

众所周知，InnoDB采用IOT（index organization table）即所谓的索引组织表，而叶子节点也就存放了所有的数据，这就意味着，数据总是按照某种顺序存储的。所以问题来了，如果是这样一个语句，执行起来应该是怎么样的呢？语句如下：

select count(distinct a) from table1;

列a上有一个索引，那么按照简单的想法来讲，如何扫描呢？很简单，一条一条的扫描，这样一来，其实做了一次索引全扫描，效率很差。这种扫描方式会扫描到很多很多的重复的索引，这样说的话优化的办法也是很容易想到的：跳过重复的索引就可以了。于是网上能搜到这样的一个优化的办法：

select count(*) from (select distinct a from table1) t;

从已经搜索到的资料看，这样的执行计划中的extra就从using index变成了using index for group-by。

但是，但是，但是，好在我们现在已经没有使用5.1的版本了，大家基本上都是5.5以上了，这些现代版本，已经实现了loose index scan：

很好很好，就不需要再用这种奇技淫巧去优化SQL了。

文档里关于group by这里写的有点意思，说是最大众化的办法就是进行全表扫描并且创建一个临时表，这样执行计划就会难看的要命了，肯定有ALL和using temporary table了。

5.0之后group by在特定条件下可能使用到loose index scan，

CREATE TABLE log_table (
id INT NOT NULL PRIMARY KEY,
log_machine VARCHAR(20) NOT NULL,
log_time DATETIME NOT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
CREATE INDEX ix_log_machine_time ON log_table (log_machine, log_time);

SELECT MAX(log_time) FROM log_table；
SELECT MAX(log_time) FROM log_table WHERE log_machine IN ('Machine 1')；

这两条sql都只需一次index seek便可返回，源于索引的有序排序，优化器意识到min/max位于最左/右块，从而避免范围扫描；
extra显示Select tables optimized away ；
2
复制代码代码如下:SELECT MAX(log_time) FROM log_table WHERE log_machine IN (‘Machine 1','Machine 2','Machine 3','Machine 4');

执行计划type 为range(extra显示using where; using index)，即执行索引范围扫描，先读取所有满足log_machine约束的记录，然后对其遍历找出max value；
改进
复制代码代码如下:SELECT MAX(log_time) FROM log_table WHERE log_machine IN (‘Machine 1','Machine 2','Machine 3','Machine 4') group by log_machine order by 1 desc limit 1;
这满足group by选择loose index scan的要求，执行计划的extra显示using index for group-by，执行效果等值于

SELECT MAX(log_time) FROM log_table WHERE log_machine IN (‘Machine 1')
Union
SELECT MAX(log_time) FROM log_table WHERE log_machine IN (‘Machine 2')
…..

即对每个log_machine执行loose index scan，rows从原来的82636下降为16(该表总共1,000,000条记录)。

Group by何时使用loose index scan"htmlcode">

SELECT c1, c2 FROM t1 GROUP BY c1, c2;
SELECT DISTINCT c1, c2 FROM t1;
SELECT c1, MIN(c2) FROM t1 GROUP BY c1;
SELECT c1, c2 FROM t1 WHERE c1 < const GROUP BY c1, c2;
SELECT MAX(c3), MIN(c3), c1, c2 FROM t1 WHERE c2 > const GROUP BY c1, c2;
SELECT c2 FROM t1 WHERE c1 < const GROUP BY c1, c2;
SELECT c1, c2 FROM t1 WHERE c3 = const GROUP BY c1, c2
SELECT c1, c3 FROM t1 GROUP BY c1, c2;--无法使用松散索引

而SELECT c1, c3 FROM t1 where c3= const GROUP BY c1, c2;则可以

紧凑索引扫描tight index scan
Group by在无法使用loose index scan，还可以选择tight，若两者都不可选，则只能借助临时表；
扫描索引时，须读取所有满足条件的索引键，要么是全索引扫描，要么是范围索引扫描；
Group by的索引列不连续；或者不是从最左前缀开始，但是where条件里出现最左列；

SELECT c1, c2, c3 FROM t1 WHERE c2 = 'a' GROUP BY c1, c3;
SELECT c1, c2, c3 FROM t1 WHERE c1 = 'a' GROUP BY c2, c3;

5.6的改进
事实上，5.6的index condition push down可以弥补loose index scan缺失带来的性能损失。
KEY(age,zip)

mysql> explain SELECT name FROM people WHERE age BETWEEN 18 AND 20 AND zip IN (12345,12346, 12347);
+----+-------------+--------+-------+---------------+------+---------+------+-------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra    |
+----+-------------+--------+-------+---------------+------+---------+------+-------+-------------+
| 1 | SIMPLE   | people | range | age      | age | 4    | NULL | 90556 | Using where |
+----+-------------+--------+-------+---------------+------+---------+------+-------+-------------+
1 row in set (0.01 sec)

根据key_len=4可以推测出sql只用到索引的第一列，即先通过索引查出满足age (18,20)的行记录，然后从server层筛选出满足zip约束的行；
pre-5.6，对于复合索引，只有当引导列使用"="时才有机会在索引扫描时使用到后面的索引列。

mysql> explain SELECT name FROM people WHERE age=18 AND zip IN (12345,12346, 12347);
+----+-------------+--------+-------+---------------+------+---------+------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra    |
+----+-------------+--------+-------+---------------+------+---------+------+------+-------------+
| 1 | SIMPLE   | people | range | age      | age | 8    | NULL |  3 | Using where |
+----+-------------+--------+-------+---------------+------+---------+------+------+-------------+
1 row in set (0.00 sec)

对比一下查询效率

mysql> SELECT sql_no_cache name FROM people WHERE age=19 AND zip IN (12345,12346, 12347);
+----------------------------------+
| name               |
+----------------------------------+
| 888ba838661aff00bbbce114a2a22423 |
+----------------------------------+
1 row in set (0.06 sec)
mysql> SELECT SQL_NO_CACHE name FROM people WHERE age BETWEEN 18 AND 22 AND zip IN (12345,12346, 12347);
+----------------------------------+
| name               |
+----------------------------------+
| ed4481336eb9adca222fd404fa15658e |
| 888ba838661aff00bbbce114a2a22423 |
+----------------------------------+
2 rows in set (1 min 56.09 sec)

对于第二条sql，可以使用union改写，

mysql> SELECT name FROM people WHERE age=18 AND zip IN (12345,12346, 12347)
  -> UNION ALL
  -> SELECT name FROM people WHERE age=19 AND zip IN (12345,12346, 12347)
  -> UNION ALL
  -> SELECT name FROM people WHERE age=20 AND zip IN (12345,12346, 12347)
  -> UNION ALL
  -> SELECT name FROM people WHERE age=21 AND zip IN (12345,12346, 12347)
  -> UNION ALL
-> SELECT name FROM people WHERE age=22 AND zip IN (12345,12346, 12347);

而mysql5.6引入了index condition pushdown，从优化器层面解决了此类问题。

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