Home Database Mysql Tutorial MySQL 分表优化试验代码_MySQL

MySQL 分表优化试验代码_MySQL

Jun 01, 2016 pm 01:20 PM

bitsCN.com 这里的分表逻辑是根据t_group表的user_name组的个数来分的。
因为这种情况单独user_name字段上的索引就属于烂索引。起不了啥名明显的效果。

1、试验PROCEDURE.
DELIMITER $$
DROP PROCEDURE `t_girl`.`sp_split_table`$$
CREATE  PROCEDURE `t_girl`.`sp_split_table`()
BEGIN
  declare done int default 0;
  declare v_user_name varchar(20) default '';
  declare v_table_name varchar(64) default '';
  -- Get all users' name.
  declare cur1 cursor for select user_name from t_group group by user_name;
  -- Deal with error or warnings.
  declare continue handler for 1329 set done = 1;
  -- Open cursor.
  open cur1;
  while done 1
  do
    fetch cur1 into v_user_name;
    if not done then
      -- Get table name.
      set v_table_name = concat('t_group_',v_user_name);
      -- Create new extra table.
      set @stmt = concat('create table ',v_table_name,' like t_group');
      prepare s1 from @stmt;
      execute s1;
      drop prepare s1;
      -- Load data into it.
      set @stmt = concat('insert into ',v_table_name,' select * from t_group where user_name = ''',v_user_name,'''');
      prepare s1 from @stmt;
      execute s1;
      drop prepare s1;
    end if;
  end while;
  -- Close cursor.
  close cur1;
  -- Free variable from memory.
  set @stmt = NULL;
END$$

DELIMITER ;
2、试验表。
我们用一个有一千万条记录的表来做测试。


mysql> select count(*) from t_group;
+----------+
| count(*) |
+----------+
| 10388608 |
+----------+
1 row in set (0.00 sec)

表结构。
mysql> desc t_group;
+-------------+------------------+------+-----+-------------------+----------------+
| Field       | Type             | Null | Key | Default           | Extra          |
+-------------+------------------+------+-----+-------------------+----------------+
| id          | int(10) unsigned | NO   | PRI | NULL              | auto_increment |
| money       | decimal(10,2)    | NO   |     |                   |                |
| user_name   | varchar(20)      | NO   | MUL |                   |                |
| create_time | timestamp        | NO   |     | CURRENT_TIMESTAMP |                |
+-------------+------------------+------+-----+-------------------+----------------+
4 rows in set (0.00 sec)

索引情况。

mysql> show index from t_group;
+---------+------------+------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| Table   | Non_unique | Key_name         | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+---------+------------+------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| t_group |          0 | PRIMARY          |            1 | id          | A         |    10388608 |     NULL | NULL   |      | BTREE      |         |
| t_group |          1 | idx_user_name    |            1 | user_name   | A         |           8 |     NULL | NULL   |      | BTREE      |         |
| t_group |          1 | idx_combination1 |            1 | user_name   | A         |           8 |     NULL | NULL   |      | BTREE      |         |
| t_group |          1 | idx_combination1 |            2 | money       | A         |        3776 |     NULL | NULL   |      | BTREE      |         |
+---------+------------+------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
4 rows in set (0.00 sec)

PS:
idx_combination1 这个索引是必须的,因为要对user_name来GROUP BY。此时属于松散索引扫描!当然完了后你可以干掉她。
idx_user_name 这个索引是为了加快单独执行constant这种类型的查询。
我们要根据用户名来分表。


mysql> select user_name from t_group where 1 group by user_name;
+-----------+
| user_name |
+-----------+
| david     |
| leo       |
| livia     |
| lucy      |
| sarah     |
| simon     |
| sony      |
| sunny     |
+-----------+
8 rows in set (0.00 sec)

所以结果表应该是这样的。
mysql> show tables like 't_group_%';
+------------------------------+
| Tables_in_t_girl (t_group_%) |
+------------------------------+
| t_group_david                |
| t_group_leo                  |
| t_group_livia                |
| t_group_lucy                 |
| t_group_sarah                |
| t_group_simon                |
| t_group_sony                 |
| t_group_sunny                |
+------------------------------+
8 rows in set (0.00 sec)

3、对比结果。


mysql> select count(*) from t_group where user_name = 'david';
+----------+
| count(*) |
+----------+
|  1298576 |
+----------+
1 row in set (1.71 sec)

执行了将近2秒。

mysql> select count(*) from t_group_david;
+----------+
| count(*) |
+----------+
|  1298576 |
+----------+
1 row in set (0.00 sec)
几乎是瞬间的。

mysql> select count(*) from t_group where user_name 'david';
+----------+
| count(*) |
+----------+
|  9090032 |
+----------+
1 row in set (9.26 sec)
执行了将近10秒,可以想象,这个是实际的项目中是不能忍受的。
mysql> select (select count(*) from t_group) - (select count(*) from t_group_david) as total;
+---------+
| total   |
+---------+
| 9090032 |
+---------+
1 row in set (0.00 sec)
几乎是瞬间的。


我们来看看聚集函数。
对于原表的操作。

mysql> select min(money),max(money) from t_group where user_name = 'david';
+------------+------------+
| min(money) | max(money) |
+------------+------------+
|      -6.41 |     500.59 |
+------------+------------+
1 row in set (0.00 sec)
最小,最大值都是FULL INDEX SCAN。所以是瞬间的。
mysql> select sum(money),avg(money) from t_group where user_name = 'david';
+--------------+------------+
| sum(money)   | avg(money) |
+--------------+------------+
| 319992383.84 | 246.417910 |
+--------------+------------+
1 row in set (2.15 sec)
其他聚集函数的结果就不是FULL INDEX SCAN了。耗时2.15秒。

对于小表的操作。
mysql> select min(money),max(money) from t_group_david;
+------------+------------+
| min(money) | max(money) |
+------------+------------+
|      -6.41 |     500.59 |
+------------+------------+
1 row in set (1.50 sec)
最大最小值完全是FULL TABLE SCAN,耗时1.50秒,不划算。以此看来。
mysql> select sum(money),avg(money) from t_group_david;
+--------------+------------+
| sum(money)   | avg(money) |
+--------------+------------+
| 319992383.84 | 246.417910 |
+--------------+------------+
1 row in set (1.68 sec)

取得这两个结果也是花了快2秒,快了一点。

我们来看看这个小表的结构。
mysql> desc t_group_david;
+-------------+------------------+------+-----+-------------------+----------------+
| Field       | Type             | Null | Key | Default           | Extra          |
+-------------+------------------+------+-----+-------------------+----------------+
| id          | int(10) unsigned | NO   | PRI | NULL              | auto_increment |
| money       | decimal(10,2)    | NO   |     |                   |                |
| user_name   | varchar(20)      | NO   | MUL |                   |                |
| create_time | timestamp        | NO   |     | CURRENT_TIMESTAMP |                |
+-------------+------------------+------+-----+-------------------+----------------+
4 rows in set (0.00 sec)

明显的user_name属性是多余的。那么就干掉它。
mysql> alter table t_group_david drop user_name;
Query OK, 1298576 rows affected (7.58 sec)
Records: 1298576  Duplicates: 0  Warnings: 0

现在来重新对小表运行查询

mysql> select min(money),max(money) from t_group_david;
+------------+------------+
| min(money) | max(money) |
+------------+------------+
|      -6.41 |     500.59 |
+------------+------------+
1 row in set (0.00 sec)

此时是瞬间的。
mysql> select sum(money),avg(money) from t_group_david;
+--------------+------------+
| sum(money)   | avg(money) |
+--------------+------------+
| 319992383.84 | 246.417910 |
+--------------+------------+
1 row in set (0.94 sec)

这次算是控制在一秒以内了。

mysql> Aborted

小总结一下:分出的小表的属性尽量越少越好。大胆的去干吧。bitsCN.com

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

When might a full table scan be faster than using an index in MySQL? When might a full table scan be faster than using an index in MySQL? Apr 09, 2025 am 12:05 AM

Full table scanning may be faster in MySQL than using indexes. Specific cases include: 1) the data volume is small; 2) when the query returns a large amount of data; 3) when the index column is not highly selective; 4) when the complex query. By analyzing query plans, optimizing indexes, avoiding over-index and regularly maintaining tables, you can make the best choices in practical applications.

Can I install mysql on Windows 7 Can I install mysql on Windows 7 Apr 08, 2025 pm 03:21 PM

Yes, MySQL can be installed on Windows 7, and although Microsoft has stopped supporting Windows 7, MySQL is still compatible with it. However, the following points should be noted during the installation process: Download the MySQL installer for Windows. Select the appropriate version of MySQL (community or enterprise). Select the appropriate installation directory and character set during the installation process. Set the root user password and keep it properly. Connect to the database for testing. Note the compatibility and security issues on Windows 7, and it is recommended to upgrade to a supported operating system.

Explain InnoDB Full-Text Search capabilities. Explain InnoDB Full-Text Search capabilities. Apr 02, 2025 pm 06:09 PM

InnoDB's full-text search capabilities are very powerful, which can significantly improve database query efficiency and ability to process large amounts of text data. 1) InnoDB implements full-text search through inverted indexing, supporting basic and advanced search queries. 2) Use MATCH and AGAINST keywords to search, support Boolean mode and phrase search. 3) Optimization methods include using word segmentation technology, periodic rebuilding of indexes and adjusting cache size to improve performance and accuracy.

Difference between clustered index and non-clustered index (secondary index) in InnoDB. Difference between clustered index and non-clustered index (secondary index) in InnoDB. Apr 02, 2025 pm 06:25 PM

The difference between clustered index and non-clustered index is: 1. Clustered index stores data rows in the index structure, which is suitable for querying by primary key and range. 2. The non-clustered index stores index key values ​​and pointers to data rows, and is suitable for non-primary key column queries.

MySQL: Simple Concepts for Easy Learning MySQL: Simple Concepts for Easy Learning Apr 10, 2025 am 09:29 AM

MySQL is an open source relational database management system. 1) Create database and tables: Use the CREATEDATABASE and CREATETABLE commands. 2) Basic operations: INSERT, UPDATE, DELETE and SELECT. 3) Advanced operations: JOIN, subquery and transaction processing. 4) Debugging skills: Check syntax, data type and permissions. 5) Optimization suggestions: Use indexes, avoid SELECT* and use transactions.

Can mysql and mariadb coexist Can mysql and mariadb coexist Apr 08, 2025 pm 02:27 PM

MySQL and MariaDB can coexist, but need to be configured with caution. The key is to allocate different port numbers and data directories to each database, and adjust parameters such as memory allocation and cache size. Connection pooling, application configuration, and version differences also need to be considered and need to be carefully tested and planned to avoid pitfalls. Running two databases simultaneously can cause performance problems in situations where resources are limited.

The relationship between mysql user and database The relationship between mysql user and database Apr 08, 2025 pm 07:15 PM

In MySQL database, the relationship between the user and the database is defined by permissions and tables. The user has a username and password to access the database. Permissions are granted through the GRANT command, while the table is created by the CREATE TABLE command. To establish a relationship between a user and a database, you need to create a database, create a user, and then grant permissions.

Explain different types of MySQL indexes (B-Tree, Hash, Full-text, Spatial). Explain different types of MySQL indexes (B-Tree, Hash, Full-text, Spatial). Apr 02, 2025 pm 07:05 PM

MySQL supports four index types: B-Tree, Hash, Full-text, and Spatial. 1.B-Tree index is suitable for equal value search, range query and sorting. 2. Hash index is suitable for equal value searches, but does not support range query and sorting. 3. Full-text index is used for full-text search and is suitable for processing large amounts of text data. 4. Spatial index is used for geospatial data query and is suitable for GIS applications.

See all articles