bitsCN.com
创建2张用户表user、user2,表结构相同,但user表使用InnoDB存储引擎,而user2表则使用 MyISAM存储引擎。
-- Table "user" DDL
CREATE TABLE `user` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`name` varchar(50) DEFAULT NULL,
`email` varchar(100) DEFAULT NULL,
`age` tinyint(4) DEFAULT NULL,
`nickname` varchar(50) DEFAULT NULL,
PRIMARY KEY (`id`),
UNIQUE KEY `email` (`email`),
KEY `name` (`name`),
KEY `age` (`age`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
-- Table "user2" DDL
CREATE TABLE `user2` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`name` varchar(50) DEFAULT NULL,
`email` varchar(100) DEFAULT NULL,
`age` tinyint(4) DEFAULT NULL,
`nickname` varchar(50) DEFAULT NULL,
PRIMARY KEY (`id`),
UNIQUE KEY `email` (`email`),
KEY `name` (`name`),
KEY `age` (`age`)
) ENGINE=MyISAM AUTO_INCREMENT=131610 DEFAULT CHARSET=utf8;
分别插入10W条测试数据到表user & user2。
$example = array(
'@qq.com',
'@sina.com.cn',
'@163.com',
'@126.com',
'@gmail.com',
'@yahoo.com',
'@live.com',
'@msn.com',
'@cisco.com',
'@microsoft.com',
'@ibm.com',
'@apple.com');
$con = mysql_connect("localhost", "root", "your_mysql_password");
mysql_select_db("index_test", $con);
//添加10W测试数据到表 user & user2
for($i=0; $i{
$temp = md5(uniqid());
$name = substr($temp, 0, 16);
$email = substr($temp, 8, 12).$example[array_rand($example, 1)];
$age = rand(18, 99);
$nickname = substr($temp, 16, 16);
mysql_query("INSERT INTO user(name,email,age,nickname) VALUES('$name','$email',$age,'$nickname')");
mysql_query("INSERT INTO user2(name,email,age,nickname) VALUES('$name','$email',$age,'$nickname')");
}
mysql_close($con);
echo 'success';
?>
对索引的使用分析
Explain Select * from user where id>100 /G;
图1
Explain Select * from user2 where id>100 /G;
图2
User 表中的数据和 User2 表中的数据是一样的,索引结构也是一样的,只不过它们的存储引擎不同。在图1中,查询用到了PRIMARY主键索引,而查询优化器预估的结果大概在65954行左右(实际是131513);在图2中,查询却没有使用索引,而是全表扫描了,返回的预估结果在131608行(实际是131509)。
Explain Select * from user where id>100 and age>50 /G;
图3
Explain Select * from user where id>100 and age=50 /G;
图4
Explain Select * from user2 where id>100 and age>50 /G;
图5
Explain Select * from user2 where id>100 and age=50 /G;
图6bitsCN.com

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

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MySQL is suitable for beginners because it is simple to install, powerful and easy to manage data. 1. Simple installation and configuration, suitable for a variety of operating systems. 2. Support basic operations such as creating databases and tables, inserting, querying, updating and deleting data. 3. Provide advanced functions such as JOIN operations and subqueries. 4. Performance can be improved through indexing, query optimization and table partitioning. 5. Support backup, recovery and security measures to ensure data security and consistency.


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