diff --git a/README.md b/README.md index 3d0e61ccd99f06ada5675f6520de5b02f719fb3c..e1067e56ba45c5ea9ce49b4bded4d336941d9806 100644 --- a/README.md +++ b/README.md @@ -27,7 +27,7 @@ - 总结下来就是：规则引擎是可降低复杂业务逻辑组件复杂性、降低应用程序的维护和可扩展性成本的组件。 - 下面用一张图来表示`**输入输出**`关系 -![image.png](./static/img/rule_engin.png) +![输入输出](./static/img/rule_engin01.png) - 我们在`**业务节点**`触发规则引擎的判断，然后对`**规则引擎**`输入`**规则集合簇**`和`**输入参数**`，经过`**规则引擎计算**`，输入`**执行结果**`，然后根据执行结果进行相应的`业务逻辑处理`，这样的话，每个业务节点就可定制业务规则，交给规则引擎去执行判断，然后拿到结果之后判断是否需要执行。 - 那么通过上述的介绍，相信你就可以了解规则引擎的作用了，那么在实际的业务开发中，我们经常会遇到这种场景，就需要规则引擎进行规则定制执行，来满足业务的诉求。 @@ -82,55 +82,55 @@ - 域的作用主要是用来划分业务系统和原子系统，本质上是个聚合的分布式系统上下文的概念。在域中，可以配置场景，并且发布等，发布是通知客户端进行更新最新的数据 -![img.png](static/img/domian01.png) +![domain](static/img/domian01.png) -![img.png](static/img/domian02.png) +![domain](static/img/domian02.png) ### 场景配置 - 场景依托于域存在，场景指的是这个业务系统的某些需要动态配置的节点，比如物理系统中的消息通知等等，可在场景配置中配置 -![img.png](static/img/scene.png) +![scene](static/img/scene.png) ### 元数据配置 - 元数据是一类Key-Value的集合，对应映射到Java语言中，应是枚举，这些是一些不会经常变更、比较稳定的数据 -![img.png](static/img/metadata01.png) +![metadata](static/img/metadata01.png) -![img.png](static/img/metadata02.png) +![metadata](static/img/metadata02.png) ### 基础数据配置 - 基础数据是根据指定的入参或者无参进行取值，取值的方式通过脚本取值，这样就能满足动态的取值逻辑，但是也会有接入复杂度，可能脚本会写的比较复杂，并且有进程风险，因为脚本完全是动态的 -![img.png](static/img/basedata01.png) -![img.png](static/img/basedata02.png) -![img.png](static/img/basedata03.png) +![basedata](static/img/basedata01.png) +![basedata](static/img/basedata02.png) +![basedata](static/img/basedata03.png) ### 数据源配置 - 数据源指的是规则执行的前置数据，当然了，客户端也可以传入数据，系统会自动对数据进行聚合，优先以传入的数据为准，进行合并数据，然后将合并的数据交给规则引擎处理 - 获取值的方式支持HTTP、Groovy、Mvel2.0等 -![img.png](static/img/datasource01.png) -![img.png](static/img/datasource02.png) -![img.png](static/img/datasource03.png) +![datasource](static/img/datasource01.png) +![datasource](static/img/datasource02.png) +![datasource](static/img/datasource03.png) ### 策略组 - 策略组就是一些配置项目，真正进行规则判断的地方，现在只支持简单的配置类型，但是支持复杂规则模式，简单规则模式只会返回布尔值，复杂规则模式支持执行中断，并返回目标值 -![img.png](static/img/strategy01.png) -![img.png](static/img/strategy02.png) -![img.png](static/img/strategy02.png) +![strategy](static/img/strategy01.png) +![strategy](static/img/strategy02.png) +![strategy](static/img/strategy03.png) ## 规则引擎单节点执行逻辑 - 如下图所示 - 业务节点触发规则执行，执行的时候先判断一些数据的验证逻辑，通过之后才能将数据推到`Rule Engine Calculation`进行执行，在此过程中判断当前业务节点的决策树是否构建完毕，如果构建完毕，则从本地缓存中取出数据，否则重新构建决策树，然后存储到本地缓存执行，最终返回执行结果 -![image.png](./static/img/rule_engin_process.png) +![rule_engin_process](./static/img/rule_engin_process.png) ## 技术与架构选型 @@ -150,7 +150,7 @@ - 通过SDK的方式需要在当前JVM进程加载当前域所在的配置数据；而通过HTTP接口的方式，则会在HTTP服务端加载所有仓储的数据。当然在更新的时候也是按需更新 - 当配置触发发布的时候，会将数据推送到触发线程队列，然后由线程池消费队列，触发客户端的消息更新 -![image.png](./static/img/rule.png) +![rule](./static/img/rule.png) ## 数据表设计 @@ -249,7 +249,7 @@ | lastUpdateTime | Date | 上次注册更新时间 | | domain | String | 注册绑定的domain | -![image.png](./static/img/register.png) 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