mysql 存储过程例子 (1)循环遍历值 drop procedure if exists doit ;/* *delimiter表示以//结束编译 * */delimiter //create procedure doit (in parameter integer)begindeclare v1 int ;set v1 = parameter ;set parameter = 90 ;while v10 doselect now(
mysql 存储过程例子(1)循环遍历值
drop procedure if exists doit ; /* *delimiter表示以//结束编译 * */ delimiter // create procedure doit (in parameter integer) begin declare v1 int ; set v1 = parameter ; set parameter = 90 ; while v1>0 do select now(); set v1 = v1 - 1 ; end while ; select parameter ; end; // delimiter ;
(2)动态执行sql并注入参数
drop procedure if exists test_insert ; -- delimiter表示以//结束编译 delimiter // create procedure test_insert(in num int) begin -- 使用变量时不能使用declare 只能用set @id = .. 模式 -- declare v1 int(11); set @v1=num ; -- declare sql varchar(200); -- declare name varchar(20); set @name='wxlan' ; set @sql='insert into test values(?,?,now())' ; prepare state_ from @sql ; while @v1 > 0 do execute state_ using @v1,@name ; set @v1 = @v1 -1 ; end while ; end; // delimiter ;
(3)游标是使用
drop procedure if exists test_cursor ; -- delimiter表示以//结束编译 delimiter // create procedure test_cursor(out result varchar(128)) begin -- 游标所使用变量需要在定义游标之前申明 declare id int(11); declare name varchar(20); -- 遍历数据结束标志 注意位置顺序 DECLARE done INT DEFAULT FALSE; -- 注意用别名 因为id在上面已经有定义所以需要使用表的别名区别 declare cur_test CURSOR for select t.id,t.name from test t; -- 将结束标志绑定到游标 DECLARE CONTINUE HANDLER FOR NOT FOUND SET done = TRUE; open cur_test; repeat fetch cur_test into id, name; select id ; -- concat_ws函数用逗号后面的参数隔开 concat_ws(',','12','33','332') --> 12,33,332 select concat_ws(',',result,id,name) into result ; until done end repeat; close cur_test; select result ; end; // delimiter ;

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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