把ACCESS转成SQL2005 数据库 这里我给大家提供以下参考---将ACCESS转化成SQL2005的方法和注意事项: 一、 首先,我说的是在ACCESS,SQL2005之间转换,其他的转换我也有尝试过,也能转化成功。 如:Excel SQL2005 、OracleSQL2005 二、 转换的方法 1. 打开控
把ACCESS转成SQL2005数据库
这里我给大家提供以下参考---将ACCESS转化成SQL2005的方法和注意事项:
一、 首先,我说的是在ACCESS,SQL2005之间转换,其他的转换我也有尝试过,也能转化成功。
如:Excelà SQL2005 、OracleàSQL2005
二、 转换的方法
1. 打开”控制面板“下”管理工具“中的”数据库源“;
2. 按”添加“添加一个新的数据源,在选择栏里选”Driver do microsoft Access(*.mdb)”,完成后将出现一个框,
3. 在”数据库源“里面输入你想写的名称,我取名叫“AAAA”,“说明”不需要填,接着,按下面的“选择”,寻找你的数据库地址和选中(注意,请先备份自己的ACCESS数据库),然后“确定”。
数据源在这里建好了,剩下转换了。
4. 打开SQL2005,进入数据库,新建一个空的数据库“ABC”;
4,选择新建立的数据库,按鼠标右键,选择“所有任务”下“导入数据”,按“下一步”继续;
5. 在数据库源下拉但中选择”Microsoft Access“,
在”文件名”中浏览你电脑中的Access的一个数据库文件。按“下一步”继续;
6在“目标“中选择”Microsoft OLE DB Provider For SQL Server“。在“身份验证”中根据你自己安装的SQL的方式选择“Windows身份验证”还是“SQL身份验证”,点击“下一步”
6. 选中“复制一个或多个表或视图的数据”,点击“下一步”
7. 选中“全选”,点击“下一步”
8. 点击“完成”,等到“执行完毕”,转化就结束了。
然后到你的SQL数据库中就可以看到你刚刚建立的那个“ABC”数据库了,并且可以去查看里面的数据
先看转换前ACCESS中的数据表结构:
转换后的SQL2005中的数据结构:
两者相同,说明转换成功!

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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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