mysql中迅速插入百万条测试数据的方法
最近想到创建一个大量数据的测试环境,于是找了一下怎么插入100W条数据,我用的是20个字段
对比一下,首先是用 mysql 的存储过程弄的:代码如下:
mysql>delimiter $
mysql>SET AUTOCOMMIT = 0$$
mysql> create procedure test()
begin
declare i decimal (10) default 0 ;
dd:loop
INSERT INTO `million` (`categ_id`, `categ_fid`, `SortPath`, `address`, `p_identifier`, `pro_specification`, `name`, `add_date`, `picture_url`, `thumb_url`, `is_display_front`, `create_html_time`, `hit`, `buy_sum`, `athor`, `templete _style`, `is_hot`, `is_new`, `is_best`) VALUES
(268, 2, '0,262,268,', 0, '2342', '423423', '123123', '2012-01-09 09:55:43', 'upload/product/20111205153432_53211.jpg', 'upload/product/thumb_20111205153432_53211.jpg', 1, 0, 0, 0, 'admin', '0', 0, 0, 0);
commit;
set i = i+1;
if i= 1000000 then leave dd;
end if;
end loop dd ;
end;$
mysql>delimiter ;
mysql> call test;
结果
mysql> call test; Query OK, 0 rows affected (58 min 30.83 sec)
非常耗时。
于是我又找了一个方法
先用PHP代码生成数据,再导入:
代码如下:
$t=mktime();
set_time_limit(1000);
$myFile="e:/insert.sql";
$fhandler=fopen($myFile,'wb');
if($fhandler){
$sql="268\t2\t'0,262,268,'\t0\t '2342'\t'423423'\t'123123'\t'23423423'\t'2012-01-09 09:55:43'\t'upload/product/20111205153432_53211.jpg'\t'upload/product/thumb_20111205153432_53211.jpg'\tNULL\tNULL\t38\t'件'\t''\t123\t123\t0";
$i=0;
while($i{
$i++;
fwrite($fhandler,$sql."\r\n");
}
echo"写入成功,耗时:",mktime()-$t;
}
然后再导入
代码如下:
LOAD DATA local INFILE 'e:/insert.sql' INTO TABLE tenmillion(`categ_id`, `categ_fid`, `SortPath`, `address`, `p_identifier`, `pro_specification`, `name`, `description`, `add_date`, `picture_url`, `thumb_url`, `shop_url`, `shop_thumb_url`, `brand_id`, `unit`, `square_meters_unit`, `market_price`, `true_price`, `square_meters_price`);
注意字段不再以逗号分割,以\t分割,条记录以\r\n分割。结果我插入10次数据,100W平均只要1分钟搞定。
第二种方式mysql中间省略了很多中间步骤,导致插入速度远胜于第一种,具体的没有研究。
快速生成mysql上百万条测试数据
由于测试需要,原表中只有1万条数据,现在随机复制插入记录,快速达到100万条。
itemid是主键。
运行几次下面代码。随机取1000条插入,
insert into downitems (chid,catid,softid,....)
SELECT chid,catid,softid... FROM `downitems` WHERE itemid >= (SELECT floor(RAND() * (SELECT MAX(itemid) FROM `downitems`))) ORDER BY itemid LIMIT 1000;
然后可以修改1000的数字了。改为5000或者1万。很快可以达到100万的数据量了。

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

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

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











The main role of MySQL in web applications is to store and manage data. 1.MySQL efficiently processes user information, product catalogs, transaction records and other data. 2. Through SQL query, developers can extract information from the database to generate dynamic content. 3.MySQL works based on the client-server model to ensure acceptable query speed.

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL's position in databases and programming is very important. It is an open source relational database management system that is widely used in various application scenarios. 1) MySQL provides efficient data storage, organization and retrieval functions, supporting Web, mobile and enterprise-level systems. 2) It uses a client-server architecture, supports multiple storage engines and index optimization. 3) Basic usages include creating tables and inserting data, and advanced usages involve multi-table JOINs and complex queries. 4) Frequently asked questions such as SQL syntax errors and performance issues can be debugged through the EXPLAIN command and slow query log. 5) Performance optimization methods include rational use of indexes, optimized query and use of caches. Best practices include using transactions and PreparedStatemen

MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

Compared with other programming languages, MySQL is mainly used to store and manage data, while other languages such as Python, Java, and C are used for logical processing and application development. MySQL is known for its high performance, scalability and cross-platform support, suitable for data management needs, while other languages have advantages in their respective fields such as data analytics, enterprise applications, and system programming.

MySQL is suitable for small and large enterprises. 1) Small businesses can use MySQL for basic data management, such as storing customer information. 2) Large enterprises can use MySQL to process massive data and complex business logic to optimize query performance and transaction processing.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.
