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Spring Cloud Stream实现数据流处理

作者：HBLOG

Spring Cloud Stream的核心是Stream,准确来讲Spring Cloud Stream提供了一整套数据流走向（流向）的API, 它的最终目的是使我们不关心数据的流入和写出,而只关心对数据的业务处理,本文给大家介绍了Spring Cloud Stream实现数据流处理,需要的朋友可以参考下

1.什么是Spring Cloud Stream？

我看很多回答都是“为了屏蔽消息队列的差异，使我们在使用消息队列的时候能够用统一的一套API，无需关心具体的消息队列实现”。 这样理解是有些不全面的，Spring Cloud Stream的核心是Stream，准确来讲Spring Cloud Stream提供了一整套数据流走向（流向）的API， 它的最终目的是使我们不关心数据的流入和写出，而只关心对数据的业务处理 我们举一个例子：你们公司有一套系统，这套系统由多个模块组成，你负责其中一个模块。数据会从第一个模块流入，处理完后再交给下一个模块。对于你负责的这个模块来说，它的功能就是接收上一个模块处理完成的数据，自己再加工加工，扔给下一个模块。

我们很容易总结出每个模块的流程：

其中流程1和3代表两个模块间的数据交互，这种数据交互往往会采用一些中间件（middleware）。比如模块1和模块2间数据可能使用的是kafka，模块1向kafka中push数据，模块2向kafka中poll数据。而模块2和模块3可能使用的是rabbitMQ。很明显，它们的功能都是一样的：**提供数据的流向，让数据可以流入自己同时又可以从自己流出发给别人。**但由于中间件的不同，需要使用不同的API。 为了消除这种数据流入（输入）和数据流出（输出）实现上的差异性，因此便出现了Spring Cloud Stream。

2.环境准备

采用docker-compose搭建kafaka环境

version: '3'

networks:
  kafka:
    ipam:
      driver: default
      config:
        - subnet: "172.22.6.0/24"

services:
  zookepper:
    image: registry.cn-hangzhou.aliyuncs.com/zhengqing/zookeeper:latest
    container_name: zookeeper-server
    restart: unless-stopped
    volumes:
      - "/etc/localtime:/etc/localtime"
    environment:
      ALLOW_ANONYMOUS_LOGIN: yes
    ports:
      - "2181:2181"
    networks:
      kafka:
        ipv4_address: 172.22.6.11

  kafka:
    image: registry.cn-hangzhou.aliyuncs.com/zhengqing/kafka:3.4.1
    container_name: kafka
    restart: unless-stopped
    volumes:
      - "/etc/localtime:/etc/localtime"
    environment:
      ALLOW_PLAINTEXT_LISTENER: yes
      KAFKA_CFG_ZOOKEEPER_CONNECT: zookepper:2181
      KAFKA_CFG_ADVERTISED_LISTENERS: PLAINTEXT://10.11.68.77:9092
    ports:
      - "9092:9092"
    depends_on:
      - zookepper
    networks:
      kafka:
        ipv4_address: 172.22.6.12

  kafka-map:
    image: registry.cn-hangzhou.aliyuncs.com/zhengqing/kafka-map
    container_name: kafka-map
    restart: unless-stopped
    volumes:
      - "./kafka/kafka-map/data:/usr/local/kafka-map/data"
    environment:
      DEFAULT_USERNAME: admin
      DEFAULT_PASSWORD: 123456
    ports:
      - "9080:8080"
    depends_on:                         
      - kafka
    networks:
      kafka:
        ipv4_address: 172.22.6.13

run

docker-compose -f docker-compose-kafka.yml -p kafka up -d

kafka-map

https://github.com/dushixiang/kafka-map

3.代码工程

实验目标

pom.xml

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <parent>
        <artifactId>springcloud-demo</artifactId>
        <groupId>com.et</groupId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <modelVersion>4.0.0</modelVersion>

    <artifactId>spring-cloud-stream-kafaka</artifactId>

    <properties>
        <maven.compiler.source>17</maven.compiler.source>
        <maven.compiler.target>17</maven.compiler.target>
    </properties>
    <dependencies>
        <!-- Spring Boot Starter Web -->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!-- Spring Boot Starter Test -->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.springframework.cloud</groupId>
            <artifactId>spring-cloud-starter-stream-kafka</artifactId>
        </dependency>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter</artifactId>
        </dependency>
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
        </dependency>

    </dependencies>

</project>

处理流

/*
 * Copyright 2023 the original author or authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      https://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.et;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.messaging.Message;
import org.springframework.messaging.support.MessageBuilder;

import java.util.List;
import java.util.UUID;
import java.util.function.Function;
import java.util.function.Supplier;

/**
 * @author Steven Gantz
 */
@SpringBootApplication
public class CloudStreamsFunctionBatch {

   public static void main(String[] args) {
      SpringApplication.run(CloudStreamsFunctionBatch.class, args);
   }

   @Bean
   public Supplier<UUID> stringSupplier() {
      return () -> {
         var uuid = UUID.randomUUID();
         System.out.println(uuid + " -> batch-in");
         return uuid;
      };
   }

   @Bean
   public Function<List<UUID>, List<Message<String>>> digitRemovingConsumer() {
      return idBatch -> {
         System.out.println("Removed digits from batch of " + idBatch.size());
         return idBatch.stream()
            .map(UUID::toString)
            // Remove all digits from the UUID
            .map(uuid -> uuid.replaceAll("\\d",""))
            .map(noDigitString -> MessageBuilder.withPayload(noDigitString).build())
            .toList();
      };
   }

   @KafkaListener(id = "batch-out", topics = "batch-out")
   public void listen(String in) {
      System.out.println("batch-out -> " + in);
   }

}

配置文件

spring:
  cloud:
    function:
      definition: stringSupplier;digitRemovingConsumer
    stream:
      bindings:
        stringSupplier-out-0:
          destination: batch-in
        digitRemovingConsumer-in-0:
          destination: batch-in
          group: batch-in
          consumer:
            batch-mode: true
        digitRemovingConsumer-out-0:
          destination: batch-out
      kafka:
        binder:
          brokers: localhost:9092
        bindings:
          digitRemovingConsumer-in-0:
            consumer:
              configuration:
                # Forces consumer to wait 5 seconds before polling for messages
                fetch.max.wait.ms: 5000
                fetch.min.bytes: 1000000000
                max.poll.records: 10000000

参数解释

spring:
  cloud:
    function:
      definition: stringSupplier;digitRemovingConsumer

spring.cloud.function.definition：定义了两个函数，stringSupplier和digitRemovingConsumer。这两个函数将在应用程序中被使用。

stream:
  bindings:
    stringSupplier-out-0:
      destination: batch-in

stream.bindings.stringSupplier-out-0.destination：将stringSupplier函数的输出绑定到Kafka主题batch-in。

    digitRemovingConsumer-in-0:
      destination: batch-in
      group: batch-in
      consumer:
        batch-mode: true

    digitRemovingConsumer-out-0:
      destination: batch-out

以上只是一些关键代码

4.测试

启动弄Spring Boot应用，可以看到控制台输出日志如下：

291ea6cc-1e5e-4dfb-92b6-5d5ea43d4277 -> batch-in
c746ba4e-835e-4f66-91c5-7a5cf8b01068 -> batch-in
a661145b-2dd9-4927-8806-919ad258ade5 -> batch-in
db150918-0f0b-49f6-b7bb-77b0f580de4c -> batch-in
b0d4917b-6777-4d96-a6d0-bb96715b5b20 -> batch-in
Removed digits from batch of 5
batch-out -> eacc-ee-dfb-b-dead
batch-out -> cbae-e-f-c-acfb
batch-out -> ab-dd---adade
batch-out -> db-fb-f-bbb-bfdec
batch-out -> bdb--d-ad-bbbb

以上就是Spring Cloud Stream实现数据流处理的详细内容，更多关于Spring Cloud Stream数据流处理的资料请关注脚本之家其它相关文章！

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