MySQL索引与Index Condition Pushdown

时间：2018-12-26 00:33:23 阅读：235 评论：0 收藏：0 [点我收藏+]

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实验

先从一个简单的实验开始直观认识ICP的作用。

安装数据库

首先需要安装一个支持ICP的MariaDB或MySQL数据库。我使用的是MariaDB 5.5.34，如果是使用MySQL则需要5.6版本以上。

Mac环境下可以通过brew安装：

brew install mairadb

其它环境下的安装请参考MariaDB官网关于下载安装的文档。

导入示例数据

与前文一样，我们使用Employees Sample Database，作为示例数据库。完整示例数据库的下载地址为：https://launchpad.net/test-db/employees-db-1/1.0.6/+download/employees_db-full-1.0.6.tar.bz2。

将下载的压缩包解压后，会看到一系列的文件，其中employees.sql就是导入数据的命令文件。执行

mysql -h[host] -u[user] -p < employees.sql

就可以完成建库、建表和load数据等一系列操作。此时数据库中会多一个叫做employees的数据库。库中的表如下：

MariaDB [employees]> SHOW TABLES;
+---------------------+
| Tables_in_employees |
+---------------------+
| departments |
| dept_emp |
| dept_manager |
| employees |
| salaries |
| titles |
+---------------------+
6 rows in set (0.00 sec)

我们将使用employees表做实验。

建立联合索引

employees表包含雇员的基本信息，表结构如下：

MariaDB [employees]> DESC employees.employees;
+------------+---------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+------------+---------------+------+-----+---------+-------+
| emp_no | int(11) | NO | PRI | NULL | |
| birth_date | date | NO | | NULL | |
| first_name | varchar(14) | NO | | NULL | |
| last_name | varchar(16) | NO | | NULL | |
| gender | enum(‘M‘,‘F‘) | NO | | NULL | |
| hire_date | date | NO | | NULL | |
+------------+---------------+------+-----+---------+-------+
6 rows in set (0.01 sec)

这个表默认只有一个主索引，因为ICP只能作用于二级索引，所以我们建立一个二级索引：

ALTER TABLE employees.employees ADD INDEX first_name_last_name (first_name, last_name);

这样就建立了一个first_name和last_name的联合索引。

查询

为了明确看到查询性能，我们启用profiling并关闭query cache：

SET profiling = 1;
SET query_cache_type = 0;
SET GLOBAL query_cache_size = 0;

然后我们看下面这个查询：

MariaDB [employees]> SELECT * FROM employees WHERE first_name=‘Mary‘ AND last_name LIKE ‘%man‘;
+--------+------------+------------+-----------+--------+------------+
| emp_no | birth_date | first_name | last_name | gender | hire_date |
+--------+------------+------------+-----------+--------+------------+
| 254642 | 1959-01-17 | Mary | Botman | M | 1989-11-24 |
| 471495 | 1960-09-24 | Mary | Dymetman | M | 1988-06-09 |
| 211941 | 1962-08-11 | Mary | Hofman | M | 1993-12-30 |
| 217707 | 1962-09-05 | Mary | Lichtman | F | 1987-11-20 |
| 486361 | 1957-10-15 | Mary | Oberman | M | 1988-09-06 |
| 457469 | 1959-07-15 | Mary | Weedman | M | 1996-11-21 |
+--------+------------+------------+-----------+--------+------------+

根据MySQL索引的前缀匹配原则，两者对索引的使用是一致的，即只有first_name采用索引，last_name由于使用了模糊前缀，没法使用索引进行匹配。我将查询联系执行三次，结果如下：

+----------+------------+---------------------------------------------------------------------------+
| Query_ID | Duration | Query |
+----------+------------+---------------------------------------------------------------------------+
| 38 | 0.00084400 | SELECT * FROM employees WHERE first_name=‘Mary‘ AND last_name LIKE ‘%man‘ |
| 39 | 0.00071800 | SELECT * FROM employees WHERE first_name=‘Mary‘ AND last_name LIKE ‘%man‘ |
| 40 | 0.00089600 | SELECT * FROM employees WHERE first_name=‘Mary‘ AND last_name LIKE ‘%man‘ |
+----------+------------+---------------------------------------------------------------------------+

然后我们关闭ICP：

SET optimizer_switch=‘index_condition_pushdown=off‘;

在运行三次相同的查询，结果如下：

+----------+------------+---------------------------------------------------------------------------+
| Query_ID | Duration | Query |
+----------+------------+---------------------------------------------------------------------------+
| 42 | 0.00264400 | SELECT * FROM employees WHERE first_name=‘Mary‘ AND last_name LIKE ‘%man‘ |
| 43 | 0.01418900 | SELECT * FROM employees WHERE first_name=‘Mary‘ AND last_name LIKE ‘%man‘ |
| 44 | 0.00234200 | SELECT * FROM employees WHERE first_name=‘Mary‘ AND last_name LIKE ‘%man‘ |
+----------+------------+---------------------------------------------------------------------------+

有意思的事情发生了，关闭ICP后，同样的查询，耗时是之前的三倍以上。下面我们用explain看看两者有什么区别：

MariaDB [employees]> EXPLAIN SELECT * FROM employees WHERE first_name=‘Mary‘ AND last_name LIKE ‘%man‘;
+------+-------------+-----------+------+----------------------+----------------------+---------+-------+------+-----------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+------+-------------+-----------+------+----------------------+----------------------+---------+-------+------+-----------------------+
| 1 | SIMPLE | employees | ref | first_name_last_name | first_name_last_name | 44 | const | 224 | Using index condition |
+------+-------------+-----------+------+----------------------+----------------------+---------+-------+------+-----------------------+
1 row in set (0.00 sec)

MariaDB [employees]> EXPLAIN SELECT * FROM employees WHERE first_name=‘Mary‘ AND last_name LIKE ‘%man‘;
+------+-------------+-----------+------+----------------------+----------------------+---------+-------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+------+-------------+-----------+------+----------------------+----------------------+---------+-------+------+-------------+
| 1 | SIMPLE | employees | ref | first_name_last_name | first_name_last_name | 44 | const | 224 | Using where |
+------+-------------+-----------+------+----------------------+----------------------+---------+-------+------+-------------+
1 row in set (0.00 sec)

前者是开启ICP，后者是关闭ICP。可以看到区别在于Extra，开启ICP时，用的是Using index condition；关闭ICP时，是Using where。

其中Using index condition就是ICP提高查询性能的关键。下一节说明ICP提高查询性能的原理。

root@localhost:3306.sock [employees]> EXPLAIN format=json SELECT * FROM employees
-> WHERE first_name=‘Mary‘ AND last_name LIKE ‘%man‘\G;
*************************** 1. row ***************************
EXPLAIN: {
"query_block": {
"select_id": 1,
"cost_info": {
"query_cost": "268.80"
},
"table": {
"table_name": "employees",
"access_type": "ref",
"possible_keys": [
"first_name_last_name"
],
"key": "first_name_last_name",
"used_key_parts": [
"first_name"
],
"key_length": "58",
"ref": [
"const"
],
"rows_examined_per_scan": 224,
"rows_produced_per_join": 24,
"filtered": "11.11",
"index_condition": "(employees.employees.last_name like ‘%man‘)",
"cost_info": {
"read_cost": "224.00",
"eval_cost": "4.98",
"prefix_cost": "268.80",
"data_read_per_join": "3K"
},
"used_columns": [
"emp_no",
"birth_date",
"first_name",
"last_name",
"gender",
"hire_date"
]
}
}
}
1 row in set, 1 warning (0.00 sec)

原理

ICP的原理简单说来就是将可以利用索引筛选的where条件在存储引擎一侧进行筛选，而不是将所有index access的结果取出放在server端进行where筛选。

以上面的查询为例，在没有ICP时，首先通过索引前缀从存储引擎中读出224条first_name为Mary的记录，然后在server段用where筛选last_name的like条件；而启用ICP后，由于last_name的like筛选可以通过索引字段进行，那么存储引擎内部通过索引与where条件的对比来筛选掉不符合where条件的记录，这个过程不需要读出整条记录，同时只返回给server筛选后的6条记录，因此提高了查询性能。

下面通过图两种查询的原理详细解释。