MySQL分区(Partition)功能试验

[概述]
[分区表和未分区表试验过程]
[分区命令详解]

[概述]

自5.1开始对分区(Partition)有支持,6.0应比较稳定

= 水平分区(根据列属性按行分)=

举个简单例子:一个包含十年发票记录的表可以被分区为十个不同的分区,每个分区包含的是其中一年的记录。

=== 水平分区的几种模式:===

  • Range(范围) – 这种模式允许DBA将数据划分不同范围。例如DBA可以将一个表通过年份划分成三个分区,80年代(1980′s)的数据,90年代(1990′s)的数据以及任何在2000年(包括2000年)后的数据。

  • Hash(哈希) – 这中模式允许DBA通过对表的一个或多个列的Hash Key进行计算,最后通过这个Hash码不同数值对应的数据区域进行分区,。例如DBA可以建立一个对表主键进行分区的表。

  • Key(键值) – 上面Hash模式的一种延伸,这里的Hash Key是MySQL系统产生的。

  • List(预定义列表) – 这种模式允许系统通过DBA定义的列表的值所对应的行数据进行分割。例如:DBA建立了一个横跨三个分区的表,分别根据2004年2005年和2006年值所对应的数据。

  • Composite(复合模式) – 很神秘吧,哈哈,其实是以上模式的组合使用而已,就不解释了。举例:在初始化已经进行了Range范围分区的表上,我们可以对其中一个分区再进行hash哈希分区。

= 垂直分区(按列分)=

举个简单例子:一个包含了大text和BLOB列的表,这些text和BLOB列又不经常被访问,这时候就要把这些不经常使用的text和BLOB了划分到另一个分区,在保证它们数据相关性的同时还能提高访问速度。

[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
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    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

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    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

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    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

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    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%。

  • 通过explain语句来分析执行情况
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    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)
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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

  • 试验创建索引后情况
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    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
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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
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    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。

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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
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    ** 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]

= 分区例子 =

  • RANGE 类型

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    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

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    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

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    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:

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    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

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    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:

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    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

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    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
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    ALERT TABLE users DROP PARTITION p0;

删除分区 p0。

  • 重建分区

    • RANGE 分区重建
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      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。

* LIST 分区重建
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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。

* HASH/KEY 分区重建
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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

    • 新增 RANGE 分区
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      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。

* 新增 HASH/KEY 分区
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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 ]

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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

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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:

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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

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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