Oracle过程和函数相信大家都比较了解,下面就为您详细介绍Oracle过程和函数二者之间的区别,希望可以让您对Oracle过程和函数有更
Oracle过程和函数相信大家都比较了解,下面就为您详细介绍Oracle过程和函数二者之间的区别,,希望可以让您对Oracle过程和函数有更深的认识。
Oracle过程和函数都以编译后的形式存放在数据库中,函数可以没有参数也可以有多个参数并有一个返回值。过程有零个或多个参数,没有返回值。函数和过程都可以通过参数列表接收或返回零个或多个值,函数和过程的主要区别不在于返回值,而在于他们的调用方式。Oracle过程是作为一个独立执行语句调用的:
函数以合法的表达式的方式调用:
创建过程的语法如下:
每个参数的语法如下:
mode有三种形式:IN、OUT、INOUT。
IN表示在调用过程的时候,实际参数的取值被传递给该过程,形式参数被认为是只读的,当过程结束时,控制会返回控制环境,实际参数的值不会改变。
OUT在调用过程时实际参数的取值都将被忽略,在过程内部形式参数只能是被赋值,而不能从中读取数据,在过程结束后形式参数的内容将被赋予实际参数。
INOUT这种模式是IN和OUT的组合;在Oracle过程内部实际参数的值会传递给形式参数,形势参数的值可读也可写,过程结束后,形势参数的值将赋予实际参数。
创建函数的语法和过程的语法基本相同,唯一的区别在于函数有RETUREN子句
在执行部分函数必须有哟个或多个return语句。
在创建函数中可以调用单行函数和组函数,例如:

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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