由于需要,要将Admodfy导出来的ldf文件内容做修改,样例如下 dn:CN = 蔡妮 , OU = ADImportOU , DC = myDomain , DC = com , DC = cn changetype:add objectClass:contact cn:蔡妮 sn:蔡妮 mailNickname:lily . cai targetAddress:lily . cai@myDomain . com
由于需要,要将Admodfy导出来的ldf文件内容做修改,样例如下
dn: CN=蔡妮,OU=AD Import OU,DC=myDomain,DC=com,DC=cn
changetype: add
objectClass: contact
cn: 蔡妮
sn: 蔡妮
mailNickname: lily.cai
targetAddress: lily.cai@myDomain.com.cn
proxyAddresses: X400:c=us;a= ;p=myDomain;o=Exchange;s=lily.cai;
proxyAddresses: SMTP:lily.cai@myDomain.com.cn
mail: lilycai@myDomain.com.cn
company: 总部
department: 财务
DisplayName: 蔡妮[Lily]
name: 蔡妮
profilePath: /ServerNameUserConf$lily.cai
要将含有X400邮件地址的行和profilePath的行删除掉,修改为
dn: CN=蔡妮,OU=AD Import OU,DC=myDomain,DC=com,DC=cn
changetype: add
objectClass: contact
cn: 蔡妮
sn: 蔡妮
mailNickname: lily.cai
targetAddress: SMTP:lily.cai@myDomain.com.cn
proxyAddresses: SMTP:lily.cai@myDomain.com.cn
mail: lily.cai@myDomain.com.cn
company: 总部
department: 财务
DisplayName: 蔡妮[Lily]
name: 蔡妮
由于文本中有大量的用户,手工删除很不现实,于是使用UltraEdit的正则表达式搜索删除,问题很快解决,用UltraEdit打开文本,首先到菜单中选择正则表达式引擎,正则表达式引擎分支位于“配置 - 搜索”之下,有如下选项:
Perl 兼容正则表达式
如果选中该选项,则编辑器将基于 Boost C++ 库使用 Perl 样式的正则表达式(当在查找/替换对话框里选中正则表达式时)。
UltraEdit 样式正则表达式
如果选中该选项,则编辑器将在查找/替换对话框里选中正则表达式时使用 UltraEdit 样式的正则表达式。
UNIX 样式正则表达式
如果选中该选项,则编辑器将在查找/替换对话框里选中正则表达式时使用 UNIX 样式的正则表达式。
选择自己喜好的正则表达式类型,不同的引擎语法不同,比如Perl兼容的正则表达式,回车是/r,而在UltraEdit风格的以及Unix兼容的回车则分别是^p和/n,下面以UltraEdit风格来说明。
选好风格后开始搜索,使用Ctrl+R弹出替换对话框,钩选“正则表达式”,搜索内容中输入 *X400*^p ,替换为空即可,点击全部替换后,则所有包含X400字样的行都被删除。
附:
正则表达式 (UltraEdit 语法):
% 匹配行首 - 表示搜索字符串必须在行首,但不包括任何选定的结果字符中的行终止字符。
$ 匹配行尾 - 表示搜索字符串必须在行尾,但不包括任何选定的结果字符中的行终止字符。
? 匹配任何除换行符的字符。
* 匹配任何除换行符外所出现的任意数量的字符。
+ 匹配一个或多个前面的字符/表达式。必须找到至少一个出现的字符。不匹配重复的换行符。
++ 0 次或多次匹配前面的字符/表达式。不匹配重复的换行符。
^b 匹配一个分页符。
^p 匹配一个换行符 (CR/LF) (段落) (DOS 文件)
^r 匹配一个换行符 (仅 CR) (段落) (MAC 文件)
^n 匹配一个换行符 (仅 LF) (段落) (UNIX 文件)
^t 匹配一个制表符
[ ] 匹配任何括号中的单个字符或范围
^{A^}^{B^} 匹配表达式 A 或 B
^ 忽略其后的正则表达式字符
相应的替换表达式是 ^x,x 的范围是 1-9。例如: 如果 ^(h*o^) ^(f*s^) 匹配“hello folks”,那么^2 ^1 表示将用“folks hello”替换它。

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.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

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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