前些日子在开发一个舆情监测系统,需要在一个操作过程中往数据表里插入大量的数据,为了改变以往生硬地逐条数据插入的笨办法,也为了提高执行效率,决定用load data infile来执行数据插入。
LOAD DATA INFILE语句从一个文本文件中以很高的速度读入一个表中。如果指定LOCAL关键词,从客户主机读文件。如果LOCAL没指定,文件必须位于服务器上。(LOCAL在MySQL3.22.6或以后版本中可用。)为了安全原因,当读取位于服务器上的文本文件时,文件必须处于数据库目录或可被所有人读取。另外,为了对服务器上文件使用LOAD DATA INFILE,在服务器主机上你必须有file的权限。
头一回用load data infile,以为只是把插入语句写到一个文件里,然后用load data infile把文件传入数据库就OK了,于是生成了一个内容类似同n句 insert into table_name (`id`,`name`,`content`) values (1,"a","abc"),(2,"b","abc"),(3,"c","abc");组成的.sql文件。然后在PHP中执行 LOAD DATA INFILE 'file_name.sql' INTO TABLE table_name;发现总是执行出错,真晕,不知道怎么回事,只好去再详细地读一下mysql的应用手册:
如果你指定一个FIELDS子句,它的每一个子句(TERMINATED BY, [OPTIONALLY] ENCLOSED BY和ESCAPED BY)也是可选的,除了你必须至少指定他们之一。
如果你不指定一个FIELDS子句,缺省值与如果你这样写的相同:
FIELDS TERMINATED BY '\t' ENCLOSED BY '' ESCAPED BY '\\'
如果你不指定一个LINES子句,缺省值与如果你这样写的相同:
LINES TERMINATED BY '\n'
换句话说,缺省值导致读取输入时,LOAD DATA INFILE表现如下:
在换行符处寻找行边界
在定位符处将行分进字段
不要期望字段由任何引号字符封装
将由“\”开头的定位符、换行符或“\”解释是字段值的部分字面字符
才知道原来我的sql里的内容并不是按照 load data infile的缺省设置来写的, 例如缺省设置下,每一句插入语句里的字段是由制表符隔开且内容不以任何引号封装(也就是括起来)的,但我的是由逗号隔开且有双引号括起来的,难怪会执行出错。
于是,将sql执行语句写成mysql_query('load data local infile "file_name.sql" into table `table_name` FIELDS TERMINATED BY "," ENCLOSED BY \'"\' ESCAPED BY "\\\" LINES TERMINATED BY "\n" STARTING BY ""');
这会算是执行成功了,成功地往指定的数据表里插入了很多条记录,可是又发现了一个问题,插入的数据乱七八糟的,字段与要插入的内容不符合我的要求,而且有好多是把字段名给插入到字段里面去了,唉,只好再回头去又读了一遍mysql中的load data infile用法,终于搞明白了,原来file_name.sql里面只需要按一定格式把内容写进去就行了,不是把整个sql执行语句都写进去的,真笨!^_^
于是,把内容换成了
1,"a","abc"
2,"b","abc"
3,"c","abc"
而且内容要与数据表里的字段从数量上和顺序上都要严格对应
在本地服务器(我用的是WINDOW主机)上测试了一下,OK,操作成功!
然后把程序传到网络服务器上(LINUX主机),一执行,提示:
Can't get stat of ……'' (Errcode: 13)
开始还以为是sql文件权限或者是mysql的root用户权限的问题,后来想不对呀,mysql的root用户是超级用户,肯定有权限的,那问题就出在sql文件的权限上,后来把sql的权限改成777,执行操作后还是不行。
网上搜索了一下,有说把文件放在/var/lib/mysql里就行了,一试,果真可以,可是我又不可能在PHP网页中把sql文件生成放到/var/lib/mysql下,费尽了心思,最后终于在网上搜索到一个解决办法:
使用LOCAL将比让服务器直接存取文件慢些,因为文件的内容必须从客户主机传送到服务器主机。在另一方面,你不需要file权限装载本地文件。
你也可以使用mysqlimport实用程序装载数据文件;它由发送一个LOAD DATA INFILE命令到服务器来运作。 --local选项使得mysqlimport从客户主机上读取数据。如果客户和服务器支持压缩协议,你能指定--compress在较慢的网络上获得更好的性能。
其实办法简单得很,那就是把load data infile写成load data local infile 就OK啦。

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Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data 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.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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