[Introduction] In the development process of database, we often encounter complex business logic and operations on the database. At this time, SP will be used to encapsulate the database operations. If there are many SPs in the project and there are no certain standards for writing, it will make it difficult to maintain the system in the future and make it difficult to understand the logic of the large SPs. In addition, during the development process of the database, complex problems will often be encountered. For business logic and database operations, SP will be used to encapsulate database operations at this time. If the project has many SPs and the writing is not standardized, it will make it difficult to maintain the system in the future and make it difficult to understand the logic of the large SPs. In addition, if the amount of data in the database is large or the project has high performance requirements for the SPs, you will encounter It is a problem of optimization, otherwise the speed may be very slow. Through personal experience, an optimized SP is even hundreds of times more efficient than a SP with poor performance.
Details:
1. If developers use Tables or Views from other libraries, they must create Views in the current library to implement cross-library operations. It is best not to use them directly. "databse.dbo.table_name", because sp_depends cannot display the cross-database table or view used by the SP, which is inconvenient for verification.
2. Before submitting SP, developers must have used set showplan on to analyze the query plan and conduct their own query optimization check.
3. To improve program operation efficiency and optimize applications, you should pay attention to the following points during the SP writing process:(a) SQL usage specifications :
(b) Index usage specifications:
(c) Tempdb usage specifications:
(d) Reasonable algorithm use: The above is the content of writing and optimization measures for SQL Server stored procedures. For more related content, please pay attention to the PHP Chinese website (www.php.cn)!
Based on the SQL optimization technology mentioned above and the SQL optimization content in the ASE Tuning manual, combined with practical applications, multiple algorithms are used for comparison to obtain the method that consumes the least resources and is the most efficient. Specific ASE tuning commands are available: set statistics io on, set statistics time on, set showplan on, etc.

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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