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Spring Cloud Stream本质上就是整合了Spring Boot和Spring Integration,实现了一套轻量级的消息驱动的微服务框架。通过使用Spring Cloud Stream,可以有效地简化开发人员对消息中间件的使用复杂度,让系统开发人员可以有更多的精力关注于核心业务逻辑的处理。
在这里我先放一张官网的图:
应用程序通过Spring Cloud Stream注入到输入和输出通道与外界进行通信。根据此规则我们很容易的实现消息传递,订阅消息与消息中转。并且当需要切换消息中间件时,几乎不需要修改代码,只需要变更配置就行了。
在用例图中 Inputs代表了应用程序监听消息 、outputs代表发送消息、binder的话大家可以理解为将应用程序与消息中间件隔离的抽象,类似于三层架构下利用dao屏蔽service与数据库的实现的原理。
springcloud默认提供了rabbitmq与kafka的实现。
- dependencies{
- compile('org.springframework.cloud:spring-cloud-stream')
- compile('org.springframework.cloud:spring-cloud-stream-binder-kafka')
- compile('org.springframework.kafka:spring-kafka')
- }
spring-cloud-stream已经给我们定义了最基本的输入与输出接口,他们分别是 Source,Sink, Processor
Sink接口:
- package org.springframework.cloud.stream.messaging;
-
- import org.springframework.cloud.stream.annotation.Input;
- import org.springframework.messaging.SubscribableChannel;
-
- public interface Sink {
- String INPUT = "input";
-
- @Input("input")
- SubscribableChannel input();
- }
Source接口:
- package org.springframework.cloud.stream.messaging;
-
- import org.springframework.cloud.stream.annotation.Output;
- import org.springframework.messaging.MessageChannel;
-
- public interface Source {
- String OUTPUT = "output";
-
- @Output("output")
- MessageChannel output();
- }
Processor接口:
- package org.springframework.cloud.stream.messaging;
-
- public interface Processor extends Source, Sink {
- }
这里面Processor这个接口既定义输入通道又定义了输出通道。同时我们也可以自己定义通道接口,代码如下:
- package com.bdqn.lyrk.shop.channel;
-
- import org.springframework.cloud.stream.annotation.Input;
- import org.springframework.cloud.stream.annotation.Output;
- import org.springframework.messaging.MessageChannel;
- import org.springframework.messaging.SubscribableChannel;
-
- public interface ShopChannel {
-
- /**
- * 发消息的通道名称
- */
- String SHOP_OUTPUT = "shop_output";
-
- /**
- * 消息的订阅通道名称
- */
- String SHOP_INPUT = "shop_input";
-
- /**
- * 发消息的通道
- *
- * @return
- */
- @Output(SHOP_OUTPUT)
- MessageChannel sendShopMessage();
-
- /**
- * 收消息的通道
- *
- * @return
- */
- @Input(SHOP_INPUT)
- SubscribableChannel recieveShopMessage();
-
-
- }
- package com.bdqn.lyrk.shop.server;
-
- import com.bdqn.lyrk.shop.channel.ShopChannel;
- import org.springframework.cloud.stream.annotation.StreamListener;
- import org.springframework.messaging.Message;
- import org.springframework.messaging.MessageChannel;
- import org.springframework.messaging.support.MessageBuilder;
- import org.springframework.web.bind.annotation.GetMapping;
- import org.springframework.web.bind.annotation.RestController;
-
- import javax.annotation.Resource;
-
- @RestController
- public class ShopService {
-
- @Resource(name = ShopChannel.SHOP_OUTPUT)
- private MessageChannel sendShopMessageChannel;
-
- @GetMapping("/sendMsg")
- public String sendShopMessage(String content) {
- boolean isSendSuccess = sendShopMessageChannel.
- send(MessageBuilder.withPayload(content).build());
- return isSendSuccess ? "发送成功" : "发送失败";
- }
-
- @StreamListener(ShopChannel.SHOP_INPUT)
- public void receive(Message<String> message) {
- System.out.println(message.getPayload());
- }
- }
这里面大家注意 @StreamListener。这个注解可以监听输入通道里的消息内容,注解里面的属性指定我们刚才定义的输入通道名称,而MessageChannel则可以通过
输出通道发送消息。使用@Resource注入时需要指定我们刚才定义的输出通道名称
- package com.bdqn.lyrk.shop;
-
- import com.bdqn.lyrk.shop.channel.ShopChannel;
- import org.springframework.boot.SpringApplication;
- import org.springframework.boot.autoconfigure.SpringBootApplication;
- import org.springframework.cloud.stream.annotation.EnableBinding;
-
- @SpringBootApplication
- @EnableBinding(ShopChannel.class)
- public class ShopServerApplication {
-
- public static void main(String[] args) {
- SpringApplication.run(ShopServerApplication.class, args);
- }
- }
- spring:
- application:
- name: shop-server
- cloud:
- stream:
- bindings:
- #配置自己定义的通道与哪个中间件交互
- shop_input: #ShopChannel里Input和Output的值
- destination: zhibo #目标主题
- shop_output:
- destination: zhibo
- default-binder: kafka #默认的binder是kafka
- kafka:
- bootstrap-servers: localhost:9092 #kafka服务地址
- consumer:
- group-id: consumer1
- producer:
- key-serializer: org.apache.kafka.common.serialization.ByteArraySerializer
- value-serializer: org.apache.kafka.common.serialization.ByteArraySerializer
- client-id: producer1
- server:
- port: 8100
这里是重头戏,我们必须指定所有通道对应的消息主题,同时指定默认的binder为kafka,紧接着定义Spring-kafka的外部化配置,在这里指定producer的序列化类为ByteArraySerializer
启动程序成功后,我们访问 http://localhost:8100/sendMsg?content=2 即可得到如下结果
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