SQL Server迁移助手(SSMA)团队今天宣布推出针对MySQL的迁移助手Microsoft SQL Server Migration Assistant 2008 for MySQL。 阅读相关信息: 微软发布SQL Server迁移助手为MySQL 下载SSMA为MySQL : SQL Server迁移助手为MySQL 1.0 其实,微软同时发布了其他
SQL Server迁移助手(SSMA)团队今天宣布推出针对MySQL的迁移助手Microsoft SQL Server Migration Assistant 2008 for MySQL。
阅读相关信息: 微软发布SQL Server迁移助手为MySQL
下载SSMA为MySQL : SQL Server迁移助手为MySQL 1.0
其实,微软同时发布了其他三个迁移助手: SSMA for Access, SSMA for Oracle, and SSMA for Sybase (all v4.2) 。它也可以将一个MySQL数据库迁移到 SQL Azure的云上。
下载文件中包含的工具的使用帮助文件,下面我会使用SSMA将一个MySQL的WordPress数据库导入到SQL Server中。
注:我只是以WordPress为例展示如何迁移数据库,如果你真的想在SQL Server中运行WordPress,请参阅此文章 WordPress的微软
1.下载SQL Server迁移助手
安装完成后,双击您的桌面上的快捷方式启动应用程序:
注意在安装SSMA 的时候确认您已经安装了MySQL客户端, 如果没有安装,助手将提示您下载 MySQL的ODBC连接器。
2.获取一个注册码
当您第一次使用SSMA时,需要从微软的官方网站获取一个注册码,文件名 ??为mysql-ssma.license,下载并将其保存在硬盘的某个文件夹中:
3.创建一个新的项目
启动程序后,单击左上角 新建项目 图标:
然后选择你要迁移到SQL Server还是SQL Azure中(我们选择SQL服务器):
4。连接到MySQL
点击左上角的连接到MySQL 图标(你必须 确认已安装MySQL的ODBC连接器 ),这时你的MySQL数据库信息将以树视图显示
5.创建一个模式迁移报告
选择要迁移的数据库,然后用鼠标右键单击数据库名称,并选择创建报告 :
生成的报告将让你看到任何在架构迁移中可能出现的问题。如果有问题,您可以通过改变一些默认的模式映射设置(编辑选项卡中的信息,在第4步中提到的)来解决这些问题。
6.连接到SQL Server(或SQL Azure,这取决于你在第3步中选择)
点击“连接到SQL Server图标的左上角。您可以提供的凭据连接到SQL Server或SQL Azure。如果您在步骤4中选择的MySQL数据库的数据库具有相同的名称不存在,你会被询问是否要创建一个。
注意 :如果你不想SSMA为您创建数据库时,您应该在连接对话框中指定你要迁移到的数据库。默认情况下,SSMA转换MySQL数据库DB1中的所有对象到SQL Server架构DB1.dbo的SQL Server数据库DB1之前,必须同步创建(见第8步)。这样做的最简单的方法是在建立连接到SQL Server数据库时,在SQL Server连接对话框中指定数据库名称。
您现在应该可以看到SQL Server的SQL Server数据 在SQL Server资源管理器中的树视图,选择您要迁移的模式。
7.转换模式(即表) 在MySQL的元数据资源管理器中 ,右键单击要迁移的数据库,然后选择 " 转换模式 " :
在这一点上,你可能需要在转换的模式中作出一些改变,例如,我选择了link_updated列,它是一个可为空的列,因为此列MySQL设置了默认值,而0000-00-00 00:00:00,是一个特殊值,将被视为一个空值数据来迁移,当数据迁移的时候如果不做改变,,这种变化可能会导致错误。
8.SQL Server数据库的同步
在SQL Server中选择要同步到的数据库,右键单击选择 与数据库同步
在打开的 ” 与数据库同步 ” 对话框中,点击 ” 确定 ” 。
9.迁移数据
在MySQL元数据资源管理器中,右键单击要迁移的数据库,并选择迁移数据, 输入MySQL和SQL Server数据库的连接凭据。
现在你的数据库架构和数据就进行了迁移。

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 is an open source relational database management system suitable for data storage, management, query and security. 1. It supports a variety of operating systems and is widely used in Web applications and other fields. 2. Through the client-server architecture and different storage engines, MySQL processes data efficiently. 3. Basic usage includes creating databases and tables, inserting, querying and updating data. 4. Advanced usage involves complex queries and stored procedures. 5. Common errors can be debugged through the EXPLAIN statement. 6. Performance optimization includes the rational use of indexes and optimized query statements.

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.

InnoDB's lock mechanisms include shared locks, exclusive locks, intention locks, record locks, gap locks and next key locks. 1. Shared lock allows transactions to read data without preventing other transactions from reading. 2. Exclusive lock prevents other transactions from reading and modifying data. 3. Intention lock optimizes lock efficiency. 4. Record lock lock index record. 5. Gap lock locks index recording gap. 6. The next key lock is a combination of record lock and gap lock to ensure data consistency.

The main reasons for poor MySQL query performance include not using indexes, wrong execution plan selection by the query optimizer, unreasonable table design, excessive data volume and lock competition. 1. No index causes slow querying, and adding indexes can significantly improve performance. 2. Use the EXPLAIN command to analyze the query plan and find out the optimizer error. 3. Reconstructing the table structure and optimizing JOIN conditions can improve table design problems. 4. When the data volume is large, partitioning and table division strategies are adopted. 5. In a high concurrency environment, optimizing transactions and locking strategies can reduce lock competition.

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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