今天实践下mysql百万级数据分区的影响，首先是产生百万级别的数据量

//创建带分区的数据表

CREATE TABLE `part_person` (

`id` bigint(20) unsigned NOT NULL,

`username` varchar(100) NOT NULL,

`born` date NOT NULL DEFAULT '1970-01-01',

`sex` tinyint(1) unsigned NOT NULL,

PRIMARY KEY (`id`,`born`)

) ENGINE=MyISAM DEFAULT CHARSET=utf8

PARTITION BY RANGE (year(born))

(PARTITION p0 VALUES LESS THAN (1980) ENGINE = MyISAM,

PARTITION p1 VALUES LESS THAN (1990) ENGINE = MyISAM,

PARTITION p2 VALUES LESS THAN (2000) ENGINE = MyISAM,

PARTITION p3 VALUES LESS THAN (2010) ENGINE = MyISAM,

PARTITION p4 VALUES LESS THAN (2020) ENGINE = MyISAM,

PARTITION p5 VALUES LESS THAN MAXVALUE ENGINE = MyISAM);

//创建不带分区的数据表

CREATE TABLE `no_part_person` (

`id` bigint(20) unsigned NOT NULL,

`username` varchar(100) NOT NULL,

`born` date NOT NULL DEFAULT '1970-01-01',

`sex` tinyint(1) unsigned NOT NULL,

PRIMARY KEY (`id`,`born`)

) ENGINE=MyISAM DEFAULT CHARSET=utf8;

//填充数据，创建procedure向数据表插入数据

CREATE PROCEDURE `part_generate`(IN num INT)

BEGIN

DECLARE char_str varchar(100) DEFAULT 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789';

DECLARE username VARCHAR(25) DEFAULT '';

DECLARE id int UNSIGNED;

DECLARE len int;

set id=1;

DELETE from person;

WHILE id <= num DO

set len = FLOOR(1 + RAND()*25);

set username = '';

WHILE len > 0 DO

SET username = CONCAT(username,substring(char_str,FLOOR(1 + RAND()*62),1));

SET len = len - 1;

END WHILE;

INSERT into part_person VALUES (id,username, ADDDATE('1970-01-01',INTERVAL RAND()*365*60 DAY), FLOOR(RAND()*2));

set id = id + 1;

END WHILE;

END

//执行procedure插入600万数据

call part_generate(6000000)

//向未分区表插入数据

insert into no_part_person select * from part_person;

现在有了数据，对比一下有没有分区对查询的影响

查询不是按照该列分区的数据时分区反而更慢一些，查询born数据时不跨区时分区效果提升显著，当数据跨区时提升效果没那么显著，但也有提升。