数据库的设计原则:关联还是不关联? 设计网站数据库(确定使用Hibernate)的过程中,时常会有争论,争论的焦点主要还是集中在表与表之间的关联上面: 有的倾向于去掉表与表之间的任何关联;有的拿完整性说话,必须保留所有的关联性。 观点1: 我倾向于去掉
数据库的设计原则:关联还是不关联?
设计网站数据库(确定使用Hibernate)的过程中,时常会有争论,争论的焦点主要还是集中在表与表之间的关联上面:
有的倾向于去掉表与表之间的任何关联;有的拿完整性说话,必须保留所有的关联性。
观点1:我倾向于去掉所有的关联,为了开发的方便。然后写代码的时候自己留意完整性的问题。
观点2:
如果不采用外键关联的话,很多字段势必得集中在一个表里面,从而造成数据冗余。根据领域模型驱动的方式设计数据库表结构,领域模型中的每一个对象只有一项职责,所以对象中的数据项不存在传递依赖,这种思路的数据库表结构设计从一开始即满足第三范式:一个表应满足第二范式,且属性间不存在传递依赖。
如果是小项目的话,为了开发方便一点而不关联都问题不大,但要是大项目的话,感觉还是遵守规范的好
观点3:
看你做什么样一个压力的系统了, 如果的系统是每秒要上万个交易的话, 亲爱的, 我建议你少用join吧。少于1W/S的系统, 无所谓, 怎么搞都一样的。 完整性比任何都重要, 在压力过高的时候, 妥协而已! 我的策略就是对于主压力的表, 一般来说, 系统中总是有几个焦点表的, 数据访问压力高, 读写密集的, 这个几个表好好设计, 不要关联,把读写操作让能力好的, 经验丰富的程序员去做封装DAO API。 其他的小表, 要做关联, 防止程序员出问题。我们现在这个做了4年还在做,200m,50多万行的项目现在是倾向于完全不建关联了,新的数据模型一律不考虑关联
观点4:
具体情况具体分析
业务表 我认为关联要好
而有一些历史信息比如日志什么的,我基本都不关联,而且最大冗余~
我的观点:
db方面经验不足,暂不发表意见。

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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