Mysql Stored Programs

本文介绍了MySQL中的存储程序概念,包括存储过程、触发器和事件等。详细解释了存储过程的创建、查看及删除方法,并提供了具体的示例代码。
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[b]1.Stored programs include these objects:[/b]
a).Stored routines, that is, stored procedures and functions. A stored procedure is invoked using the CALL statement. A procedure does not have a return value but can modify its parameters for later inspection by the caller. It can also generate result sets to be returned to the client program. A stored function is used much like a built-in function. you invoke it in an expression and it returns a value during expression evaluation.

b).Triggers. A trigger is a named database object that is associated with a table and that is activated when a particular event occurs for the table, such as an insert or update.

c).Events. An event is a task that the server runs according to schedule.

[b]2.Defining Stored Programs[/b]
Each stored program contains a body that consists of an SQL statement. This statement may be a compound statement made up of several statements separated by semicolon (;) characters.
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CREATE PROCEDURE dorepeat(p1 INT)
BEGIN
SET @x = 0;
REPEAT SET @x = @x + 1; UNTIL @x > p1 END REPEAT;
END;


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Stored routines require the proc table in the mysql database.


[b]mysql stored procedure[/b]
[b]1.创建[/b]
delimiter //
create procedure calcal(actId int)
begin
#do something
end;
//
delimiter ;

[b]2.查看[/b]
方法一:
select `name` from mysql.proc where db = 'your_db_name' and `type` = 'PROCEDURE'

方法二:
show procedure status;

[b]3.删除[/b]
drop procedure db_name.sp_name;[/size]
根据原作 https://pan.quark.cn/s/459657bcfd45 的源码改编 Classic-ML-Methods-Algo 引言 建立这个项目,是为了梳理和总结传统机器学习(Machine Learning)方法(methods)或者算法(algo),和各位同仁相互学习交流. 现在的深度学习本质上来自于传统的神经网络模型,很大程度上是传统机器学习的延续,同时也在不少时候需要结合传统方法来实现. 任何机器学习方法基本的流程结构都是通用的;使用的评价方法也基本通用;使用的一些数学知识也是通用的. 本文在梳理传统机器学习方法算法的同时也会顺便补充这些流程,数学上的知识以供参考. 机器学习 机器学习是人工智能(Artificial Intelligence)的一个分支,也是实现人工智能最重要的手段.区别于传统的基于规则(rule-based)的算法,机器学习可以从数据中获取知识,从而实现规定的任务[Ian Goodfellow and Yoshua Bengio and Aaron Courville的Deep Learning].这些知识可以分为四种: 总结(summarization) 预测(prediction) 估计(estimation) 假想验证(hypothesis testing) 机器学习主要关心的是预测[Varian在Big Data : New Tricks for Econometrics],预测的可以是连续性的输出变量,分类,聚类或者物品之间的有趣关联. 机器学习分类 根据数据配置(setting,是否有标签,可以是连续的也可以是离散的)和任务目标,我们可以将机器学习方法分为四种: 无监督(unsupervised) 训练数据没有给定...
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