批处理是一个逻辑单元的一组T-sql语句。 为了将一个脚本分为多个批处理,可以使用GO语句。 1. GO语句必须自成一行。 2. GO语句使得每个批处理是单独发送到服务器的,与其他的批处理器无关。(这里面的执行方案很可能是并发的,所以在很多的情况下,可能需要考
批处理是一个逻辑单元的一组T-sql语句。
为了将一个脚本分为多个批处理,可以使用GO语句。
1. GO语句必须自成一行。
2. GO语句使得每个批处理是单独发送到服务器的,与其他的批处理器无关。(这里面的执行方案很可能是并发的,所以在很多的情况下,可能需要考虑顺序问题)
3. GO语句不是T-sql命令,,而是由各种SQLServer命令适用成型的识别命令。
批处理中的错误:
1. 语法错误,在执行之前就会被检测。
2. 运行时错误,只能在运行之后(或者之中)被检测到,一般是违反了完整性等错误。
要求有自己批处理的语句:
1. Create Default
2. Create Procedure
3. Create Rule
4. Create Trigger
5. Create View
注:如果想在单独的脚本中将这些语句组合,则需要通过使用GO语句来将它们分散到各自的批处理中。
EXEC的陷阱:
1. Exec和调用它的代码都在单独的作用域下运行——也就是说,调用代码不能引用EXEC语句中的变量,并且在调用代码中的变量被解析为用于EXEC语句的字符串之后,EXEC不能引用这些变量。如果需要在动态SQL和调用它的例程间传递值,考虑使用SQL-executeSQL。
2. 默认情况下,EXEC在当前用户的安全上下文下运行——而不是调用对象的安全上下文。(对象经常在对象所有者的上下文运行,而不是当前用户)
3. EXEC与调用对象运行在相同的连接和事务环境下。
4. 对EXEC字符串执行的要求函数调用的串联必须先于实际调用的EXEC的语句——不能在执行EXEC调用的相同语句中执行函数串联。
5. EXEC不能再用户自定义函数内使用。

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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