bitsCN.com
MySQL不同存储引擎和不同分区字段对于查询的影响
前提:每种表类型准备了200万条相同的数据。
表一 InnoDB & PARTITION BY RANGE (id)
Sql代码
CREATE TABLE `customer_innodb_id` (
`id` int(11) NOT NULL,
`email` varchar(64) NOT NULL,
`name` varchar(32) NOT NULL,
`password` varchar(32) NOT NULL,
`phone` varchar(13) DEFAULT NULL,
`birth` date DEFAULT NULL,
`sex` int(1) DEFAULT NULL,
`avatar` blob,
`address` varchar(64) DEFAULT NULL,
`regtime` datetime DEFAULT NULL,
`lastip` varchar(15) DEFAULT NULL,
`modifytime` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8
/*!50100 PARTITION BY RANGE (id)
(PARTITION p0 VALUES LESS THAN (100000) ENGINE = InnoDB,
PARTITION p1 VALUES LESS THAN (500000) ENGINE = InnoDB,
PARTITION p2 VALUES LESS THAN (1000000) ENGINE = InnoDB,
PARTITION p3 VALUES LESS THAN (1500000) ENGINE = InnoDB,
PARTITION p4 VALUES LESS THAN (2000000) ENGINE = InnoDB,
PARTITION p5 VALUES LESS THAN MAXVALUE ENGINE = InnoDB) */;
查询结果:
Sql代码
mysql> select count(*) from customer_innodb_id where id > 50000 and id
+----------+
| count(*) |
+----------+
| 449999 |
+----------+
1 row in set (1.19 sec)
mysql> select count(*) from customer_innodb_id where id > 50000 and id
+----------+
| count(*) |
+----------+
| 449999 |
+----------+
1 row in set (0.28 sec)
mysql> select count(*) from customer_innodb_id where regtime > '1995-01-01 00:00
:00' and regtime
+----------+
| count(*) |
+----------+
| 199349 |
+----------+
1 row in set (4.74 sec)
mysql> select count(*) from customer_innodb_id where regtime > '1995-01-01 00:00
:00' and regtime
+----------+
| count(*) |
+----------+
| 199349 |
+----------+
1 row in set (5.28 sec)
表二 InnoDB & PARTITION BY RANGE (year)
Sql代码
CREATE TABLE `customer_innodb_year` (
`id` int(11) NOT NULL,
`email` varchar(64) NOT NULL,
`name` varchar(32) NOT NULL,
`password` varchar(32) NOT NULL,
`phone` varchar(13) DEFAULT NULL,
`birth` date DEFAULT NULL,
`sex` int(1) DEFAULT NULL,
`avatar` blob,
`address` varchar(64) DEFAULT NULL,
`regtime` datetime NOT NULL DEFAULT '0000-00-00 00:00:00',
`lastip` varchar(15) DEFAULT NULL,
`modifytime` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
PRIMARY KEY (`id`,`regtime`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8
/*!50100 PARTITION BY RANGE (YEAR(regtime ))
(PARTITION p0 VALUES LESS THAN (1996) ENGINE = InnoDB,
PARTITION p1 VALUES LESS THAN (1997) ENGINE = InnoDB,
PARTITION p2 VALUES LESS THAN (1998) ENGINE = InnoDB,
PARTITION p3 VALUES LESS THAN (1999) ENGINE = InnoDB,
PARTITION p4 VALUES LESS THAN (2000) ENGINE = InnoDB,
PARTITION p5 VALUES LESS THAN (2001) ENGINE = InnoDB,
PARTITION p6 VALUES LESS THAN (2002) ENGINE = InnoDB,
PARTITION p7 VALUES LESS THAN (2003) ENGINE = InnoDB,
PARTITION p8 VALUES LESS THAN (2004) ENGINE = InnoDB,
PARTITION p9 VALUES LESS THAN (2005) ENGINE = InnoDB,
PARTITION p10 VALUES LESS THAN (2006) ENGINE = InnoDB,
PARTITION p11 VALUES LESS THAN (2007) ENGINE = InnoDB,
PARTITION p12 VALUES LESS THAN (2008) ENGINE = InnoDB,
PARTITION p13 VALUES LESS THAN (2009) ENGINE = InnoDB,
PARTITION p14 VALUES LESS THAN (2010) ENGINE = InnoDB,
PARTITION p15 VALUES LESS THAN (2011) ENGINE = InnoDB,
PARTITION p16 VALUES LESS THAN (2012) ENGINE = InnoDB,
PARTITION p17 VALUES LESS THAN (2013) ENGINE = InnoDB,
PARTITION p18 VALUES LESS THAN (2014) ENGINE = InnoDB,
PARTITION p19 VALUES LESS THAN MAXVALUE ENGINE = InnoDB) */;
查询结果:
Sql代码
mysql> select count(*) from customer_innodb_year where id > 50000 and id
0;
+----------+
| count(*) |
+----------+
| 449999 |
+----------+
1 row in set (5.31 sec)
mysql> select count(*) from customer_innodb_year where id > 50000 and id
0;
+----------+
| count(*) |
+----------+
| 449999 |
+----------+
1 row in set (0.31 sec)
mysql> select count(*) from customer_innodb_year where regtime > '1995-01-01 00:
00:00' and regtime
+----------+
| count(*) |
+----------+
| 199349 |
+----------+
1 row in set (0.47 sec)
mysql> select count(*) from customer_innodb_year where regtime > '1995-01-01 00:
00:00' and regtime
+----------+
| count(*) |
+----------+
| 199349 |
+----------+
1 row in set (0.19 sec)
表三 MyISAM & PARTITION BY RANGE (id)
Sql代码
CREATE TABLE `customer_myisam_id` (
`id` int(11) NOT NULL,
`email` varchar(64) NOT NULL,
`name` varchar(32) NOT NULL,
`password` varchar(32) NOT NULL,
`phone` varchar(13) DEFAULT NULL,
`birth` date DEFAULT NULL,
`sex` int(1) DEFAULT NULL,
`avatar` blob,
`address` varchar(64) DEFAULT NULL,
`regtime` datetime DEFAULT NULL,
`lastip` varchar(15) DEFAULT NULL,
`modifytime` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
PRIMARY KEY (`id`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8
/*!50100 PARTITION BY RANGE (id)
(PARTITION p0 VALUES LESS THAN (100000) ENGINE = MyISAM,
PARTITION p1 VALUES LESS THAN (500000) ENGINE = MyISAM,
PARTITION p2 VALUES LESS THAN (1000000) ENGINE = MyISAM,
PARTITION p3 VALUES LESS THAN (1500000) ENGINE = MyISAM,
PARTITION p4 VALUES LESS THAN (2000000) ENGINE = MyISAM,
PARTITION p5 VALUES LESS THAN MAXVALUE ENGINE = MyISAM) */;
查询结果:
Sql代码
mysql> select count(*) from customer_myisam_id where id > 50000 and id
+----------+
| count(*) |
+----------+
| 449999 |
+----------+
1 row in set (0.59 sec)
mysql> select count(*) from customer_myisam_id where id > 50000 and id
+----------+
| count(*) |
+----------+
| 449999 |
+----------+
1 row in set (0.16 sec)
mysql> select count(*) from customer_myisam_id where regtime > '1995-01-01 00:00
:00' and regtime
+----------+
| count(*) |
+----------+
| 199349 |
+----------+
1 row in set (34.17 sec)
mysql> select count(*) from customer_myisam_id where regtime > '1995-01-01 00:00
:00' and regtime
+----------+
| count(*) |
+----------+
| 199349 |
+----------+
1 row in set (34.06 sec)
表四 MyISAM & PARTITION BY RANGE (year)
Sql代码
CREATE TABLE `customer_myisam_year` (
`id` int(11) NOT NULL,
`email` varchar(64) NOT NULL,
`name` varchar(32) NOT NULL,
`password` varchar(32) NOT NULL,
`phone` varchar(13) DEFAULT NULL,
`birth` date DEFAULT NULL,
`sex` int(1) DEFAULT NULL,
`avatar` blob,
`address` varchar(64) DEFAULT NULL,
`regtime` datetime NOT NULL DEFAULT '0000-00-00 00:00:00',
`lastip` varchar(15) DEFAULT NULL,
`modifytime` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
PRIMARY KEY (`id`,`regtime`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8
/*!50100 PARTITION BY RANGE (YEAR(regtime ))
(PARTITION p0 VALUES LESS THAN (1996) ENGINE = MyISAM,
PARTITION p1 VALUES LESS THAN (1997) ENGINE = MyISAM,
PARTITION p2 VALUES LESS THAN (1998) ENGINE = MyISAM,
PARTITION p3 VALUES LESS THAN (1999) ENGINE = MyISAM,
PARTITION p4 VALUES LESS THAN (2000) ENGINE = MyISAM,
PARTITION p5 VALUES LESS THAN (2001) ENGINE = MyISAM,
PARTITION p6 VALUES LESS THAN (2002) ENGINE = MyISAM,
PARTITION p7 VALUES LESS THAN (2003) ENGINE = MyISAM,
PARTITION p8 VALUES LESS THAN (2004) ENGINE = MyISAM,
PARTITION p9 VALUES LESS THAN (2005) ENGINE = MyISAM,
PARTITION p10 VALUES LESS THAN (2006) ENGINE = MyISAM,
PARTITION p11 VALUES LESS THAN (2007) ENGINE = MyISAM,
PARTITION p12 VALUES LESS THAN (2008) ENGINE = MyISAM,
PARTITION p13 VALUES LESS THAN (2009) ENGINE = MyISAM,
PARTITION p14 VALUES LESS THAN (2010) ENGINE = MyISAM,
PARTITION p15 VALUES LESS THAN (2011) ENGINE = MyISAM,
PARTITION p16 VALUES LESS THAN (2012) ENGINE = MyISAM,
PARTITION p17 VALUES LESS THAN (2013) ENGINE = MyISAM,
PARTITION p18 VALUES LESS THAN (2014) ENGINE = MyISAM,
PARTITION p19 VALUES LESS THAN MAXVALUE ENGINE = MyISAM) */;
查询结果:
Sql代码
mysql> select count(*) from customer_myisam_year where id > 50000 and id
0;
+----------+
| count(*) |
+----------+
| 449999 |
+----------+
1 row in set (2.08 sec)
mysql> select count(*) from customer_myisam_year where id > 50000 and id
0;
+----------+
| count(*) |
+----------+
| 449999 |
+----------+
1 row in set (0.17 sec)
mysql> select count(*) from customer_myisam_year where regtime > '1995-01-01 00:
00:00' and regtime
+----------+
| count(*) |
+----------+
| 199349 |
+----------+
1 row in set (0.56 sec)
mysql> select count(*) from customer_myisam_year where regtime > '1995-01-01 00:
00:00' and regtime
+----------+
| count(*) |
+----------+
| 199349 |
+----------+
1 row in set (0.13 sec)
结果汇总
序号 存储引擎 分区函数 查询条件 一次查询(sec) 二次查询(sec)
1 InnoDB id id 1.19 0.28
2 InnoDB id regtime 4.74 5.28
3 InnoDB year id 5.31 0.31
4 InnoDB year regtime 0.47 0.19
5 MyISAM id id 0.59 0.16
6 MyISAM id regtime 34.17 34.06
7 MyISAM year id 2.08 0.17
8 MyISAM year regtime 0.56 0.13
总结
1、对于按照时间区间来查询的,建议采用按照时间来分区,减少查询范围。
2、MyISAM性能总体占优,但是不支持事务处理、外键约束等。
bitsCN.com

InnoDB使用redologs和undologs确保数据一致性和可靠性。1.redologs记录数据页修改,确保崩溃恢复和事务持久性。2.undologs记录数据原始值,支持事务回滚和MVCC。

EXPLAIN命令的关键指标包括type、key、rows和Extra。1)type反映查询的访问类型,值越高效率越高,如const优于ALL。2)key显示使用的索引,NULL表示无索引。3)rows预估扫描行数,影响查询性能。4)Extra提供额外信息,如Usingfilesort提示需要优化。

Usingtemporary在MySQL查询中表示需要创建临时表,常见于使用DISTINCT、GROUPBY或非索引列的ORDERBY。可以通过优化索引和重写查询避免其出现,提升查询性能。具体来说,Usingtemporary出现在EXPLAIN输出中时,意味着MySQL需要创建临时表来处理查询。这通常发生在以下情况:1)使用DISTINCT或GROUPBY时进行去重或分组;2)ORDERBY包含非索引列时进行排序;3)使用复杂的子查询或联接操作。优化方法包括:1)为ORDERBY和GROUPB

MySQL/InnoDB支持四种事务隔离级别:ReadUncommitted、ReadCommitted、RepeatableRead和Serializable。1.ReadUncommitted允许读取未提交数据,可能导致脏读。2.ReadCommitted避免脏读,但可能发生不可重复读。3.RepeatableRead是默认级别,避免脏读和不可重复读,但可能发生幻读。4.Serializable避免所有并发问题,但降低并发性。选择合适的隔离级别需平衡数据一致性和性能需求。

MySQL适合Web应用和内容管理系统,因其开源、高性能和易用性而受欢迎。1)与PostgreSQL相比,MySQL在简单查询和高并发读操作上表现更好。2)相较Oracle,MySQL因开源和低成本更受中小企业青睐。3)对比MicrosoftSQLServer,MySQL更适合跨平台应用。4)与MongoDB不同,MySQL更适用于结构化数据和事务处理。

MySQL索引基数对查询性能有显着影响:1.高基数索引能更有效地缩小数据范围,提高查询效率;2.低基数索引可能导致全表扫描,降低查询性能;3.在联合索引中,应将高基数列放在前面以优化查询。

MySQL学习路径包括基础知识、核心概念、使用示例和优化技巧。1)了解表、行、列、SQL查询等基础概念。2)学习MySQL的定义、工作原理和优势。3)掌握基本CRUD操作和高级用法,如索引和存储过程。4)熟悉常见错误调试和性能优化建议,如合理使用索引和优化查询。通过这些步骤,你将全面掌握MySQL的使用和优化。

MySQL在现实世界的应用包括基础数据库设计和复杂查询优化。1)基本用法:用于存储和管理用户数据,如插入、查询、更新和删除用户信息。2)高级用法:处理复杂业务逻辑,如电子商务平台的订单和库存管理。3)性能优化:通过合理使用索引、分区表和查询缓存来提升性能。


热AI工具

Undresser.AI Undress
人工智能驱动的应用程序,用于创建逼真的裸体照片

AI Clothes Remover
用于从照片中去除衣服的在线人工智能工具。

Undress AI Tool
免费脱衣服图片

Clothoff.io
AI脱衣机

AI Hentai Generator
免费生成ai无尽的。

热门文章

热工具

禅工作室 13.0.1
功能强大的PHP集成开发环境

DVWA
Damn Vulnerable Web App (DVWA) 是一个PHP/MySQL的Web应用程序,非常容易受到攻击。它的主要目标是成为安全专业人员在合法环境中测试自己的技能和工具的辅助工具,帮助Web开发人员更好地理解保护Web应用程序的过程,并帮助教师/学生在课堂环境中教授/学习Web应用程序安全。DVWA的目标是通过简单直接的界面练习一些最常见的Web漏洞,难度各不相同。请注意,该软件中

EditPlus 中文破解版
体积小,语法高亮,不支持代码提示功能

SublimeText3 Mac版
神级代码编辑软件(SublimeText3)

安全考试浏览器
Safe Exam Browser是一个安全的浏览器环境,用于安全地进行在线考试。该软件将任何计算机变成一个安全的工作站。它控制对任何实用工具的访问,并防止学生使用未经授权的资源。