从以上的介绍中我们可以看出触发器具有强大的功能,那么MS SQL Server 是如何管理触发器来完成这些任务呢?下面我们将对其工作原理及实现做较为详细的介绍。
每个触发器有两个特殊的表:插入表和删除表。这两个表是逻辑表,并且这两个表是 由系统管理的,存储在内存中,不是存储在数据库中,因此不允许用户直接对其修改。这 两个表的结构总是与被该触发器作用的表有相同的表结构。这两个表是动态驻留在内存中 的,当触发器工作完成,这两个表也被删除。这两个表主要保存因用户操作而被影响到的 原数据值或新数据值。另外,这两个表是只读的,即用户不能向这两个表写入内容,但可 以引用表中的数据。例如可用如下语句查看DELETED 表中的信息:
select * from deleted
下面详细介绍这两个表的功能:
12.7.1 插入表的功能
对一个定义了插入类型触发器的表来讲,一旦对该表执行了插入操作,那么对向该表插入的所有行来说,都有一个相应的副本存放到插入表中。即插入表就是用来存储向原表插入的内容。
12.7.2 删除表的功能
对一个定义了删除类型触发器的表来讲,一旦对该表执行了删除操作,则将所有的删 除行存放至删除表中。这样做的目的是,一旦触发器遇到了强迫它中止的语句被执行时, 删除的那些行可以从删除表中得以恢复。
需要强调的是,更新操作包括两个部分,即先将更新的内容去掉,然后将新值插入。 因此对一个定义了更新类型触发器的表来讲,当报告会更新操作时,在删除表中存放了旧 值,然后在插入表中存放新值。
由于触发器仅当被定义的操作被执行时才被激活,即仅当在执行插入、删除、和更新 操作时,触发器将执行。每条SQL 语句仅能激活触发器一次,可能存在一条语句影响多 条记录的情况。在这种情况下就需要变量@@rowcount 的值,该变量存储了一条SQL 语 句执行后所影响的记录数,可以使用该值对触发器的SQL 语句执行后所影响的记录求合 计值。一般来说,首先要用IF 语句测试@@rowcount 的值以确定后面的语句是否执行。

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.

SQL commands in MySQL can be divided into categories such as DDL, DML, DQL, DCL, etc., and are used to create, modify, delete databases and tables, insert, update, delete data, and perform complex query operations. 1. Basic usage includes CREATETABLE creation table, INSERTINTO insert data, and SELECT query data. 2. Advanced usage involves JOIN for table joins, subqueries and GROUPBY for data aggregation. 3. Common errors such as syntax errors, data type mismatch and permission problems can be debugged through syntax checking, data type conversion and permission management. 4. Performance optimization suggestions include using indexes, avoiding full table scanning, optimizing JOIN operations and using transactions to ensure data consistency.

InnoDB achieves atomicity through undolog, consistency and isolation through locking mechanism and MVCC, and persistence through redolog. 1) Atomicity: Use undolog to record the original data to ensure that the transaction can be rolled back. 2) Consistency: Ensure the data consistency through row-level locking and MVCC. 3) Isolation: Supports multiple isolation levels, and REPEATABLEREAD is used by default. 4) Persistence: Use redolog to record modifications to ensure that data is saved for a long time.

MySQL's position in databases and programming is very important. It is an open source relational database management system that is widely used in various application scenarios. 1) MySQL provides efficient data storage, organization and retrieval functions, supporting Web, mobile and enterprise-level systems. 2) It uses a client-server architecture, supports multiple storage engines and index optimization. 3) Basic usages include creating tables and inserting data, and advanced usages involve multi-table JOINs and complex queries. 4) Frequently asked questions such as SQL syntax errors and performance issues can be debugged through the EXPLAIN command and slow query log. 5) Performance optimization methods include rational use of indexes, optimized query and use of caches. Best practices include using transactions and PreparedStatemen

MySQL is suitable for small and large enterprises. 1) Small businesses can use MySQL for basic data management, such as storing customer information. 2) Large enterprises can use MySQL to process massive data and complex business logic to optimize query performance and transaction processing.

InnoDB effectively prevents phantom reading through Next-KeyLocking mechanism. 1) Next-KeyLocking combines row lock and gap lock to lock records and their gaps to prevent new records from being inserted. 2) In practical applications, by optimizing query and adjusting isolation levels, lock competition can be reduced and concurrency performance can be improved.


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