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MySQL分区字段列是否需要再单独建索引

下文主要给大家带来MySQL分区字段列是否需要再单独建索引,希望MySQL分区字段列是否需要再单独建索引能够带给大家实际用处,这也是我编辑这篇文章的主要目的。好了,废话不多说,大家直接看下文吧。                                                             

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1、新建表effect_new(以创建时间按月分区)

CREATE TABLE `effect_new` (
 `id` bigint(20) NOT NULL AUTO_INCREMENT,
 `type` tinyint(4) NOT NULL DEFAULT '0',
 `timezone` varchar(10) DEFAULT NULL,
 `date` varchar(10) NOT NULL,
 `hour` varchar(2) DEFAULT NULL,
 `position` varchar(200) DEFAULT NULL,
 `country` varchar(32) NOT NULL,
 `create_time` datetime NOT NULL DEFAULT '1970-01-01 00:00:00',
 PRIMARY KEY (`id`,`create_time`),
 KEY `index_date_hour_coun` (`date`,`hour`,`country`)
) ENGINE=InnoDB AUTO_INCREMENT=983041 DEFAULT CHARSET=utf8
PARTITION BY RANGE (TO_DAYS (`create_time`))
(PARTITION p0 VALUES LESS THAN (736754) ENGINE = InnoDB,
 PARTITION p1 VALUES LESS THAN (736785) ENGINE = InnoDB,
 PARTITION p2 VALUES LESS THAN (736815) ENGINE = InnoDB,
 PARTITION p3 VALUES LESS THAN (736846) ENGINE = InnoDB,
 PARTITION p4 VALUES LESS THAN (736876) ENGINE = InnoDB,
 PARTITION p5 VALUES LESS THAN (736907) ENGINE = InnoDB,
 PARTITION p6 VALUES LESS THAN (736938) ENGINE = InnoDB,
 PARTITION p7 VALUES LESS THAN (736968) ENGINE = InnoDB,
 PARTITION p8 VALUES LESS THAN (736999) ENGINE = InnoDB,
 PARTITION p9 VALUES LESS THAN (737029) ENGINE = InnoDB,
 PARTITION p10 VALUES LESS THAN (737060) ENGINE = InnoDB);

MySQL分区字段列是否需要再单独建索引

2、插入部分数据数据

INSERT INTO `effect_new` (`id`, `type`, `timezone`, `date`, `hour`, `position`, `country`, `create_time`) VALUES ('1', '0', 'GMT+8', '2017-07-01', '', 'M-NotiCleanFull-FamilyRecom-0026', '', '2017-07-02 00:07:02');
INSERT INTO `effect_new` (`id`, `type`, `timezone`, `date`, `hour`, `position`, `country`, `create_time`) VALUES ('2', '1', 'GMT+8', '2017-09-30', '23', 'Ma5dtJub', 'EG', '2017-10-01 00:00:00');
INSERT INTO `effect_new` (`id`, `type`, `timezone`, `date`, `hour`, `position`, `country`, `create_time`) VALUES ('3', '1', 'GMT+8', '2017-09-10', '10', '28', 'DZ', '2017-09-11 00:08:20');
INSERT INTO `effect_new` (`id`, `type`, `timezone`, `date`, `hour`, `position`, `country`, `create_time`) VALUES ('4', '1', 'GMT+8', '2017-02-03', '20', '32', 'AD', '2017-02-04 00:00:00');
INSERT INTO `effect_new` (`id`, `type`, `timezone`, `date`, `hour`, `position`, `country`, `create_time`) VALUES ('5', '0', 'GMT+8', '2017-03-05', '2', NULL, 'AI', '2017-03-06 02:10:00');
INSERT INTO `effect_new` (`id`, `type`, `timezone`, `date`, `hour`, `position`, `country`, `create_time`) VALUES ('6', '0', 'GMT+8', '2017-09-23', '13', 'M-BrandSplash-S-0038', 'AG', '2017-09-23 13:00:00');
INSERT INTO `effect_new` (`id`, `type`, `timezone`, `date`, `hour`, `position`, `country`, `create_time`) VALUES ('7', '1', NULL, '2017-10-13', '12', 'BB-Main-AppAd-0018', 'AF', '2017-10-14 12:00:00');
INSERT INTO `effect_new` (`id`, `type`, `timezone`, `date`, `hour`, `position`, `country`, `create_time`) VALUES ('8', '0', 'GMT+8', '2017-10-28', '2', 'M-ChargeReminder-S-0040', 'AE', '2017-10-29 00:00:00');
INSERT INTO `effect_new` (`id`, `type`, `timezone`, `date`, `hour`, `position`, `country`, `create_time`) VALUES ('9', '1', 'GMT+8', '2017-10-09', NULL, '30', 'AI', '2017-10-10 00:09:00');
INSERT INTO `effect_new` (`id`, `type`, `timezone`, `date`, `hour`, `position`, `country`, `create_time`) VALUES ('10', '0', 'GMT+8', '2017-10-05', '5', ' M-BrandSplash', 'LA', '2017-10-06 05:10:00');

3、分析语句

EXPLAIN PARTITIONS
select * from effect_new_index
where create_time = '2017-10-14 12:00:00'

结果为:

idselect_typetablepartitionstpyepossible_keyskeykey_lenrefrowsfilteredextra
1SIMPLEeffect_newp8ALLnullnullnullnull39151510Using where

4、给表effect_new添加索引idx_ctime

5、分析添加索引后的执行计划

结果为:

idselect_typetablepartitionstpyepossible_keyskeykey_lenrefrowsfilteredextra
1SIMPLEeffect_newp8refidx_ctimeidx_ctime5const60760100null

6、结论:

虽然表已经根据此字段分区,但这不能等同于索引。分了区,只能说该字段为某个值的记录会在某个分区里面,但不是索引,还要一顿好找。

有时候,主键不等于分区依据列,这时候主键又想建聚集索引的话,那么必须包含分区依据列,搞成复合主键。那么,这种情况下,分区依据列不就有索引了吗?是的,可是它不够快,如果在这个复合索引里面,分区依据列不排在第一位,就不够快,如果查找语句里常常用分区依据列作为过滤条件,就有必要为分区依据列额外单独建立一个索引。

对于以上关于MySQL分区字段列是否需要再单独建索引,大家是不是觉得非常有帮助。如果需要了解更多内容,请继续关注我们的行业资讯,相信你会喜欢上这些内容的。


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