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mysql partition 分區功能使用詳解
目前分區規則有四種，分別是RANGE、LIST、HASH和KEY，另外通過DATA DIRECTORY和INDEX DIRECTORY選項可以把不同的分區數據文件分散到不同的磁盤上，從而進步一提高系統的IO吞吐量。因此按照業務邏輯設計好了分區，可以大大提高查詢效率，而且刪除數據可能也會很容易。但是分區也有一些限制：1、主鍵或者唯一索引必須包含分區字段；2、只能通過int類型的字段或者返回int類型的表達式來分區；3、單表最多只能有1024個分區。
默認mysql是開啟了分區功能的，可以通過下述查詢查看結果：
代碼如下 復制代碼show variables like '%partition%';
+-------------------+-------+
| Variable_name | Value |
+-------------------+-------+
| have_partitioning | YES |
+-------------------+-------+
//YES 表示開啟下面也range規則為例介紹一下分區常用的命令。
1、創建分區。可以在創建表的同時創建，也可以在表創建後追加分區。
代碼如下 復制代碼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命令查看分區是否創建成功
代碼如下 復制代碼explain partitions select * from netingcn_com where day = 20130412;
+----+-------------+--------------+------------+-------+
| id | select_type | table | partitions | type |
+----+-------------+--------------+------------+-------+
| 1 | SIMPLE | netingcn_com | p_2013 | index |
+----+-------------+--------------+------------+-------+
2、增加或刪除分區。注意：刪除分區的同時，該分區的所有數據也會別刪除。
增加分區
代碼如下 復制代碼alter table netingcn_com add partition (
partition p_2014 values less than (20150000)
);
刪除分區
代碼如下 復制代碼 alter table netingcn_com drop partition p_2012;3、重新分區。注意：hash和key分區規則不能用REORGANIZE
來重新分區
代碼如下 復制代碼alter table netingcn_com reorganize partition p_2013,p_2014 into (partition p_2014 values less than (20150000));
[分區表和未分區表試驗過程]
*創建分區表,按日期的年份拆分
代碼如下 復制代碼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 );
注意最後一行，考慮到可能的最大值
*創建未分區表
代碼如下 復制代碼 mysql> create table no_part_tab (c1 int(11) default NULL,c2 varchar(30) default NULL,c3 date default NULL) engine=myisam;*通過存儲過程灌入800萬條測試數據
代碼如下 復制代碼mysql> set sql_mode=''; /* 如果創建存儲過程失敗，則先需設置此變量, bug? */
mysql> delimiter // /* 設定語句終結符為 //，因存儲過程語句用;結束 */
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
* 測試SQL性能
代碼如下 復制代碼 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)
結果表明分區表比未分區表的執行時間少90%。
代碼如下 復制代碼* 通過explain語句來分析執行情況
mysql > explain select count(*) from no_part_tab where c3 > date '1995-01-01' and c3 < date '1995-12-31'G
/* 結尾的G使得mysql的輸出改為列模式 */
*************************** 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語句顯示了SQL查詢要處理的記錄數目
代碼如下 復制代碼* 試驗創建索引後情況
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
創建索引後的數據庫文件大小列表：
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
* 再次測試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) /* 為原來4.69 sec 的51%*/
重啟mysql ( net stop mysql, net start mysql)後，查詢時間降為0.89 sec,幾乎與分區表相同。
代碼如下 復制代碼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)
* 更進一步的試驗
** 增加日期范圍
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)
** 增加未索引字段查詢
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)
= 初步結論 =
* 分區和未分區占用文件空間大致相同 （數據和索引文件）
* 如果查詢語句中有未建立索引字段，分區時間遠遠優於未分區時間
* 如果查詢語句中字段建立了索引，分區和未分區的差別縮小，分區略優於未分區。
= 最終結論 =
* 對於大數據量，建議使用分區功能。
* 去除不必要的字段
* 根據手冊， 增加myisam_max_sort_file_size 會增加分區性能
[分區命令詳解]
代碼如下 復制代碼= 分區例子 =
* RANGE 類型
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'
);
在這裡，將用戶表分成4個分區，以每300萬條記錄為界限，每個分區都有自己獨立的數據、索引文件的存放目錄，與此同時，這些目錄所在的物理磁盤分區可能也都是完全獨立的，可以提高磁盤IO吞吐量。
* LIST 類型
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個區，數據文件和索引文件單獨存放。
* HASH 類型
代碼如下 復制代碼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個區，數據文件和索引文件單獨存放。
例子：
代碼如下 復制代碼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 類型
代碼如下 復制代碼 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個區，數據文件和索引文件單獨存放。
* 子分區
子分區是針對 RANGE/LIST 類型的分區表中每個分區的再次分割。再次分割可以是 HASH/KEY 等類型。例如：
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'
);
對 RANGE 分區再次進行子分區劃分，子分區采用 HASH 類型。
或者
代碼如下 復制代碼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'
);
對 RANGE 分區再次進行子分區劃分，子分區采用 KEY 類型。
= 分區管理 =
* 刪除分區
ALERT TABLE users DROP PARTITION p0;
刪除分區 p0。
* 重建分區
o RANGE 分區重建
ALTER TABLE users REORGANIZE PARTITION p0,p1 INTO (PARTITION p0 VALUES LESS THAN (6000000));
將原來的 p0,p1 分區合並起來，放到新的 p0 分區中。
o LIST 分區重建
ALTER TABLE users REORGANIZE PARTITION p0,p1 INTO (PARTITION p0 VALUES IN(0,1,4,5,8,9,12,13));
將原來的 p0,p1 分區合並起來，放到新的 p0 分區中。
o HASH/KEY 分區重建
ALTER TABLE users REORGANIZE PARTITION COALESCE PARTITION 2;
用 REORGANIZE 方式重建分區的數量變成2，在這裡數量只能減少不能增加。想要增加可以用 ADD PARTITION 方法。
* 新增分區
o 新增 RANGE 分區
ALTER TABLE category ADD PARTITION (PARTITION p4 VALUES IN (16,17,18,19)
DATA DIRECTORY = '/data8/data'
INDEX DIRECTORY = '/data9/idx');
新增一個RANGE分區。
o 新增 HASH/KEY 分區
ALTER TABLE users ADD PARTITION PARTITIONS 8;
將分區總數擴展到8個。
[ 給已有的表加上分區 ]
代碼如下 復制代碼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) );
默認分區限制分區字段必須是主鍵（PRIMARY KEY)的一部分，為了去除此
限制：
[方法1] 使用ID
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] 將原有PK去掉生成新PK
代碼如下 復制代碼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
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