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。
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