mysql partition自mysql 5.1.3起开始支持分区功能。mysql表中存储的记录和表对应的索引信息，最后都是以文件的方式存储在计算机的硬盘上的，有了分区功能我们就可以做比以前更多优化了。
目前分区规则有四种，分别是RANGE、LIST、HASH和KEY，另外通过DATA DIRECTORY和INDEX DIRECTORY选项可以把不同的分区数据文件分散到不同的磁盘上，从而进步一提高系统的IO吞吐量。因此按照业务逻辑设计好了分区，可以大大提高查询效率，而且删除数据可能也会很容易。但是分区也有一些限制：1、主键或者唯一索引必须包含分区字段；2、只能通过int类型的字段或者返回int类型的表达式来分区；3、单表最多只能有1024个分区。
默认mysql是开启了分区功能的，可以通过下述查询查看结果：
| 代码如下 |
|
|
show variables like '%partition%';
+-------------------+-------+
| Variable_name | Value |
+-------------------+-------+
| have_partitioning | YES |
|
+-------------------+-------+
//YES 表示开启下面也range规则为例介绍一下分区常用的命令。
1、创建分区。可以在创建表的同时创建，也可以在表创建后追加分区。
| 代码如下 |
|
|
drop table if exists `netingcn_com`;
create table `netingcn_com` (
`id` int(11) unsigned not null auto_increment,
`day` int(11) not null default 0,
primary key (`id`, `day`)
) engine=innodb default charset=utf8 auto_increment=1;
alter table `netingcn_com` partition by range(`day`) (
partition p_2012 values less than (20130000),
partition p_2013 values less than (20140000)
);
或
drop table if exists `netingcn_com`;
create table `netingcn_com` (
`id` int(11) unsigned not null auto_increment,
`day` int(11) not null default 0,
primary key (`id`, `day`)
) engine=innodb default charset=utf8 auto_increment=1
partition by range(`day`) (
partition p_2012 values less than (20130000),
partition p_2013 values less than (20140000)
);
|
可以explain命令查看分区是否创建成功
| 代码如下 |
|
|
explain partitions select * from netingcn_com where day = 20130412;
+----+-------------+--------------+------------+-------+
| id | select_type | table | partitions | type |
+----+-------------+--------------+------------+-------+
| 1 | SIMPLE | netingcn_com | p_2013 | index |
+----+-------------+--------------+------------+-------+
|
2、增加或删除分区。注意：删除分区的同时，该分区的所有数据也会别删除。
增加分区
| 代码如下 |
|
|
alter table netingcn_com add partition (
partition p_2014 values less than (20150000)
);
|
删除分区
| 代码如下 |
|
| alter table netingcn_com drop partition p_2012; |
3、重新分区。注意：hash和key分区规则不能用REORGANIZE
来重新分区
| 代码如下 |
|
|
alter table netingcn_com reorganize partition p_2013,p_2014 into (partition p_2014 values less than (20150000));
|
[分区表和未分区表试验过程]
*创建分区表,按日期的年份拆分
| 代码如下 |
|
mysql> CREATE TABLE part_tab ( c1 int default NULL, c2 varchar(30) default NULL, c3 date default NULL) engine=myisam
PARTITION BY RANGE (year(c3)) (PARTITION p0 VALUES LESS THAN (1995),
PARTITION p1 VALUES LESS THAN (1996) , PARTITION p2 VALUES LESS THAN (1997) ,
PARTITION p3 VALUES LESS THAN (1998) , PARTITION p4 VALUES LESS THAN (1999) ,
PARTITION p5 VALUES LESS THAN (2000) , PARTITION p6 VALUES LESS THAN (2001) ,
PARTITION p7 VALUES LESS THAN (2002) , PARTITION p8 VALUES LESS THAN (2003) ,
PARTITION p9 VALUES LESS THAN (2004) , PARTITION p10 VALUES LESS THAN (2010),
PARTITION p11 VALUES LESS THAN MAXVALUE );
|
注意最后一行，考虑到可能的最大值
*创建未分区表
| 代码如下 |
|
| mysql> create table no_part_tab (c1 int(11) default NULL,c2 varchar(30) default NULL,c3 date default NULL) engine=myisam; |
*通过存储过程灌入800万条测试数据
| 代码如下 |
|
|
mysql> set sql_mode=''; /* 如果创建存储过程失败，则先需设置此变量, bug? */
mysql> delimiter // /* 设定语句终结符为 //，因存储过程语句用;结束 */
mysql> CREATE PROCEDURE load_part_tab()
begin
declare v int default 0;
while v < 8000000
do
insert into part_tab
values (v,'testing partitions',adddate('1995-01-01',(rand(v)*36520) mod 3652));
set v = v + 1;
end while;
end
//
mysql> delimiter ;
mysql> call load_part_tab();
Query OK, 1 row affected (8 min 17.75 sec)
mysql> insert into no_part_tab select * from part_tab;
Query OK, 8000000 rows affected (51.59 sec)
Records: 8000000 Duplicates: 0 Warnings: 0
|
* 测试SQL性能
| 代码如下 |
|
mysql> select count(*) from part_tab where c3 > date '1995-01-01' and c3 < date '1995-12-31';
+----------+
| count(*) |
+----------+
| 795181 |
+----------+
1 row in set (0.55 sec)
mysql> select count(*) from no_part_tab where c3 > date '1995-01-01' and c3 < date '1995-12-31';
+----------+
| count(*) |
+----------+
| 795181 |
+----------+
1 row in set (4.69 sec)
|
结果表明分区表比未分区表的执行时间少90%。
| 代码如下 |
|
|
* 通过explain语句来分析执行情况
mysql > explain select count(*) from no_part_tab where c3 > date '1995-01-01' and c3 < date '1995-12-31'G
/* 结尾的G使得mysql的输出改为列模式 */
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: no_part_tab
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 8000000
Extra: Using where
1 row in set (0.00 sec)
mysql> explain select count(*) from part_tab where c3 > date '1995-01-01' and c3 < date '1995-12-31'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: part_tab
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 798458
Extra: Using where
1 row in set (0.00 sec)
|
explain语句显示了SQL查询要处理的记录数目
| 代码如下 |
|
|
* 试验创建索引后情况
mysql> create index idx_of_c3 on no_part_tab (c3);
Query OK, 8000000 rows affected (1 min 18.08 sec)
Records: 8000000 Duplicates: 0 Warnings: 0
mysql> create index idx_of_c3 on part_tab (c3);
Query OK, 8000000 rows affected (1 min 19.19 sec)
Records: 8000000 Duplicates: 0 Warnings: 0
创建索引后的数据库文件大小列表：
2008-05-24 09:23 8,608 no_part_tab.frm
2008-05-24 09:24 255,999,996 no_part_tab.MYD
2008-05-24 09:24 81,611,776 no_part_tab.MYI
2008-05-24 09:25 0 part_tab#P#p0.MYD
2008-05-24 09:26 1,024 part_tab#P#p0.MYI
2008-05-24 09:26 25,550,656 part_tab#P#p1.MYD
2008-05-24 09:26 8,148,992 part_tab#P#p1.MYI
2008-05-24 09:26 25,620,192 part_tab#P#p10.MYD
2008-05-24 09:26 8,170,496 part_tab#P#p10.MYI
2008-05-24 09:25 0 part_tab#P#p11.MYD
2008-05-24 09:26 1,024 part_tab#P#p11.MYI
2008-05-24 09:26 25,656,512 part_tab#P#p2.MYD
2008-05-24 09:26 8,181,760 part_tab#P#p2.MYI
2008-05-24 09:26 25,586,880 part_tab#P#p3.MYD
2008-05-24 09:26 8,160,256 part_tab#P#p3.MYI
2008-05-24 09:26 25,585,696 part_tab#P#p4.MYD
2008-05-24 09:26 8,159,232 part_tab#P#p4.MYI
2008-05-24 09:26 25,585,216 part_tab#P#p5.MYD
2008-05-24 09:26 8,159,232 part_tab#P#p5.MYI
2008-05-24 09:26 25,655,740 part_tab#P#p6.MYD
2008-05-24 09:26 8,181,760 part_tab#P#p6.MYI
2008-05-24 09:26 25,586,528 part_tab#P#p7.MYD
2008-05-24 09:26 8,160,256 part_tab#P#p7.MYI
2008-05-24 09:26 25,586,752 part_tab#P#p8.MYD
2008-05-24 09:26 8,160,256 part_tab#P#p8.MYI
2008-05-24 09:26 25,585,824 part_tab#P#p9.MYD
2008-05-24 09:26 8,159,232 part_tab#P#p9.MYI
2008-05-24 09:25 8,608 part_tab.frm
2008-05-24 09:25 68 part_tab.par
* 再次测试SQL性能
mysql> select count(*) from no_part_tab where c3 > date '1995-01-01' and c3 < date '1995-12-31'; +----------+
| count(*) |
+----------+
| 795181 |
+----------+
1 row in set (2.42 sec) /* 为原来4.69 sec 的51%*/
|
重启mysql ( net stop mysql, net start mysql)后，查询时间降为0.89 sec,几乎与分区表相同。
| 代码如下 |
|
|
mysql> select count(*) from part_tab where c3 > date '1995-01-01' and c3 < date '1995-12-31';
+----------+
| count(*) |
+----------+
| 795181 |
+----------+
1 row in set (0.86 sec)
* 更进一步的试验
** 增加日期范围
mysql> select count(*) from no_part_tab where c3 > date '1995-01-01' and c3 < date '1997-12-31';
+----------+
| count(*) |
+----------+
| 2396524 |
+----------+
1 row in set (5.42 sec)
mysql> select count(*) from part_tab where c3 > date '1995-01-01' and c3 < date '1997-12-31';
+----------+
| count(*) |
+----------+
| 2396524 |
+----------+
1 row in set (2.63 sec)
** 增加未索引字段查询
mysql> select count(*) from part_tab where c3 > date '1995-01-01' and c3 < date
'1996-12-31' and c2='hello';
+----------+
| count(*) |
+----------+
| 0 |
+----------+
1 row in set (0.75 sec)
mysql> select count(*) from no_part_tab where c3 > date '1995-01-01' and c3 < da
te '1996-12-31' and c2='hello';
+----------+
| count(*) |
+----------+
| 0 |
+----------+
1 row in set (11.52 sec)
|
= 初步结论 =
* 分区和未分区占用文件空间大致相同 （数据和索引文件）
* 如果查询语句中有未建立索引字段，分区时间远远优于未分区时间
* 如果查询语句中字段建立了索引，分区和未分区的差别缩小，分区略优于未分区。
= 最终结论 =
* 对于大数据量，建议使用分区功能。
* 去除不必要的字段
* 根据手册， 增加myisam_max_sort_file_size 会增加分区性能
[分区命令详解]
| 代码如下 |
|
|
= 分区例子 =
* RANGE 类型
CREATE TABLE users (
uid INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(30) NOT NULL DEFAULT '',
email VARCHAR(30) NOT NULL DEFAULT ''
)
PARTITION BY RANGE (uid) (
PARTITION p0 VALUES LESS THAN (3000000)
DATA DIRECTORY = '/data0/data'
INDEX DIRECTORY = '/data1/idx',
PARTITION p1 VALUES LESS THAN (6000000)
DATA DIRECTORY = '/data2/data'
INDEX DIRECTORY = '/data3/idx',
PARTITION p2 VALUES LESS THAN (9000000)
DATA DIRECTORY = '/data4/data'
INDEX DIRECTORY = '/data5/idx',
PARTITION p3 VALUES LESS THAN MAXVALUE DATA DIRECTORY = '/data6/data'
INDEX DIRECTORY = '/data7/idx'
);
|
在这里，将用户表分成4个分区，以每300万条记录为界限，每个分区都有自己独立的数据、索引文件的存放目录，与此同时，这些目录所在的物理磁盘分区可能也都是完全独立的，可以提高磁盘IO吞吐量。
* LIST 类型
| 代码如下 |
|
|
CREATE TABLE category (
cid INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(30) NOT NULL DEFAULT ''
)
PARTITION BY LIST (cid) (
PARTITION p0 VALUES IN (0,4,8,12)
DATA DIRECTORY = '/data0/data'
INDEX DIRECTORY = '/data1/idx',
PARTITION p1 VALUES IN (1,5,9,13)
DATA DIRECTORY = '/data2/data'
INDEX DIRECTORY = '/data3/idx',
PARTITION p2 VALUES IN (2,6,10,14)
DATA DIRECTORY = '/data4/data'
INDEX DIRECTORY = '/data5/idx',
PARTITION p3 VALUES IN (3,7,11,15)
DATA DIRECTORY = '/data6/data'
INDEX DIRECTORY = '/data7/idx'
);
|
分成4个区，数据文件和索引文件单独存放。
* HASH 类型
| 代码如下 |
|
|
CREATE TABLE users (
uid INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(30) NOT NULL DEFAULT '',
email VARCHAR(30) NOT NULL DEFAULT ''
)
PARTITION BY HASH (uid) PARTITIONS 4 (
PARTITION p0
DATA DIRECTORY = '/data0/data'
INDEX DIRECTORY = '/data1/idx',
PARTITION p1
DATA DIRECTORY = '/data2/data'
INDEX DIRECTORY = '/data3/idx',
PARTITION p2
DATA DIRECTORY = '/data4/data'
INDEX DIRECTORY = '/data5/idx',
PARTITION p3
DATA DIRECTORY = '/data6/data'
INDEX DIRECTORY = '/data7/idx'
);
|
分成4个区，数据文件和索引文件单独存放。
例子：
| 代码如下 |
|
|
CREATE TABLE ti2 (id INT, amount DECIMAL(7,2), tr_date DATE)
ENGINE=myisam
PARTITION BY HASH( MONTH(tr_date) )
PARTITIONS 6;
CREATE PROCEDURE load_ti2()
begin
declare v int default 0;
while v < 80000
do
insert into ti2
values (v,'3.14',adddate('1995-01-01',(rand(v)*3652) mod 365));
set v = v + 1;
end while;
end
//
|
* KEY 类型
| 代码如下 |
|
CREATE TABLE users (
uid INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(30) NOT NULL DEFAULT '',
email VARCHAR(30) NOT NULL DEFAULT ''
)
PARTITION BY KEY (uid) PARTITIONS 4 (
PARTITION p0
DATA DIRECTORY = '/data0/data'
INDEX DIRECTORY = '/data1/idx',
PARTITION p1
DATA DIRECTORY = '/data2/data'
INDEX DIRECTORY = '/data3/idx',
PARTITION p2
DATA DIRECTORY = '/data4/data'
INDEX DIRECTORY = '/data5/idx',
PARTITION p3
DATA DIRECTORY = '/data6/data'
INDEX DIRECTORY = '/data7/idx'
);
|
分成4个区，数据文件和索引文件单独存放。
* 子分区
子分区是针对 RANGE/LIST 类型的分区表中每个分区的再次分割。再次分割可以是 HASH/KEY 等类型。例如：
| 代码如下 |
|
|
CREATE TABLE users (
uid INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(30) NOT NULL DEFAULT '',
email VARCHAR(30) NOT NULL DEFAULT ''
)
PARTITION BY RANGE (uid) SUBPARTITION BY HASH (uid % 4) SUBPARTITIONS 2(
PARTITION p0 VALUES LESS THAN (3000000)
DATA DIRECTORY = '/data0/data'
INDEX DIRECTORY = '/data1/idx',
PARTITION p1 VALUES LESS THAN (6000000)
DATA DIRECTORY = '/data2/data'
INDEX DIRECTORY = '/data3/idx'
);
|
对 RANGE 分区再次进行子分区划分，子分区采用 HASH 类型。
或者
| 代码如下 |
|
|
CREATE TABLE users (
uid INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(30) NOT NULL DEFAULT '',
email VARCHAR(30) NOT NULL DEFAULT ''
)
PARTITION BY RANGE (uid) SUBPARTITION BY KEY(uid) SUBPARTITIONS 2(
PARTITION p0 VALUES LESS THAN (3000000)
DATA DIRECTORY = '/data0/data'
INDEX DIRECTORY = '/data1/idx',
PARTITION p1 VALUES LESS THAN (6000000)
DATA DIRECTORY = '/data2/data'
INDEX DIRECTORY = '/data3/idx'
);
|
对 RANGE 分区再次进行子分区划分，子分区采用 KEY 类型。
= 分区管理 =
* 删除分区
ALERT TABLE users DROP PARTITION p0;
删除分区 p0。
* 重建分区
o RANGE 分区重建
ALTER TABLE users REORGANIZE PARTITION p0,p1 INTO (PARTITION p0 VALUES LESS THAN (6000000));
将原来的 p0,p1 分区合并起来，放到新的 p0 分区中。
o LIST 分区重建
ALTER TABLE users REORGANIZE PARTITION p0,p1 INTO (PARTITION p0 VALUES IN(0,1,4,5,8,9,12,13));
将原来的 p0,p1 分区合并起来，放到新的 p0 分区中。
o HASH/KEY 分区重建
ALTER TABLE users REORGANIZE PARTITION COALESCE PARTITION 2;
用 REORGANIZE 方式重建分区的数量变成2，在这里数量只能减少不能增加。想要增加可以用 ADD PARTITION 方法。
* 新增分区
o 新增 RANGE 分区
ALTER TABLE category ADD PARTITION (PARTITION p4 VALUES IN (16,17,18,19)
DATA DIRECTORY = '/data8/data'
INDEX DIRECTORY = '/data9/idx');
新增一个RANGE分区。
o 新增 HASH/KEY 分区
ALTER TABLE users ADD PARTITION PARTITIONS 8;
将分区总数扩展到8个。
[ 给已有的表加上分区 ]
| 代码如下 |
|
|
alter table results partition by RANGE (month(ttime))
(PARTITION p0 VALUES LESS THAN (1),
PARTITION p1 VALUES LESS THAN (2) , PARTITION p2 VALUES LESS THAN (3) ,
PARTITION p3 VALUES LESS THAN (4) , PARTITION p4 VALUES LESS THAN (5) ,
PARTITION p5 VALUES LESS THAN (6) , PARTITION p6 VALUES LESS THAN (7) ,
PARTITION p7 VALUES LESS THAN (8) , PARTITION p8 VALUES LESS THAN (9) ,
PARTITION p9 VALUES LESS THAN (10) , PARTITION p10 VALUES LESS THAN (11),
PARTITION p11 VALUES LESS THAN (12),
PARTITION P12 VALUES LESS THAN (13) );
|
默认分区限制分区字段必须是主键（PRIMARY KEY)的一部分，为了去除此
限制：
[方法1] 使用ID
| 代码如下 |
|
|
mysql> ALTER TABLE np_pk
-> PARTITION BY HASH( TO_DAYS(added) )
-> PARTITIONS 4;
ERROR 1503 (HY000): A PRIMARY KEY must include all columns in the table's partitioning function
However, this statement using the id column for the partitioning column is valid, as shown here:
mysql> ALTER TABLE np_pk
-> PARTITION BY HASH(id)
-> PARTITIONS 4;
Query OK, 0 rows affected (0.11 sec)
Records: 0 Duplicates: 0 Warnings: 0
|
[方法2] 将原有PK去掉生成新PK
| 代码如下 |
|
|
mysql> alter table results drop PRIMARY KEY;
Query OK, 5374850 rows affected (7 min 4.05 sec)
Records: 5374850 Duplicates: 0 Warnings: 0
mysql> alter table results add PRIMARY KEY(id, ttime);
Query OK, 5374850 rows affected (6 min 14.86 sec)
Records: 5374850 Duplicates: 0 Warnings: 0
|
