有时候,不希望存储过程抛出错误中止执行,而是希望返回一个错误码。 Mysql 支持异常处理,通过定义 CONTINUE/EXIT 异常处理的 HANDLER 来捕获 SQLWARNING/NOT FOUND/SQLEXCEPTION (警告 / 无数据 / 其他异常)。其中, FOR 后面可以改为 SQLWARNING, NOT FOUND, SQLEXCEPTION 来指示所有异常都处理,相当于 oracle 中的 others 。例如,当不进行异常处理时,以下代码将直接抛出一个 ERROR 1062 (23000) 错误:
CREATE PROCEDURE test_proc_ins1( IN i_id INT, IN i_name VARCHAR(100) ) BEGIN INSERT INTO testproc VALUES (i_id,i_name); INSERT INTO testproc VALUES (i_id,i_name); END;
经过异常处理后,可以避免抛出错误,而是定义一个返回参数 o_ret 赋予特殊值来表示失败,这样,比如在 java 代码中,可以通过获取返回值而不是捕获异常的方式来处理业务逻辑。例如将返回值设置为 -1:
CREATE PROCEDURE test_proc_ins1( IN i_id INT, IN i_name VARCHAR(100), OUT o_ret INT) BEGIN DECLARE EXIT HANDLER FOR SQLSTATE '23000' set o_ret = -1; -- 也可以这样使用: -- DECLARE EXIT HANDLER FOR SQLWARNING,NOT FOUND,SQLEXCEPTION set o_ret=-1; INSERT INTO testproc VALUES (i_id,i_name); INSERT INTO testproc VALUES (i_id,i_name); set o_ret = 1; END;
当然,对于特定的SQL语句,也可以指定比如主键冲突,就rollback;
DECLARE exit HANDLER FOR SQLSTATE '23000' delimiter // CREATE PROCEDURE TEST() BEGIN DECLARE exit HANDLER FOR SQLEXCEPTION,SQLWARNING,NOT FOUND begin rollback; insert into bb values('error'); end; START TRANSACTION; INSERT INTO aa VALUES (1); INSERT INTO aa VALUES (2); COMMIT; END; // CALL test()//

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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