10分钟学会如何在SpringBoot程序中使用Kafka作为消息队列

x33g5p2x  于2020-09-08 发布在 Kafka  
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Step1:创建项目

直接通过Spring 官方提供的 Spring Initializr 创建或者直接使用 IDEA 创建皆可。

Step2: 配置 Kafka

通过 application.yml 配置文件配置 Kafka 基本信息

server:
  port: 9090

spring:
  kafka:
    consumer:
      bootstrap-servers: localhost:9092
      # 配置消费者消息offset是否自动重置(消费者重连会能够接收最开始的消息)
      auto-offset-reset: earliest
    producer:
      bootstrap-servers: localhost:9092
      # 发送的对象信息变为json格式
      value-serializer: org.springframework.kafka.support.serializer.JsonSerializer
kafka:
  topic:
    my-topic: my-topic
    my-topic2: my-topic2

Kafka 额外配置类：

package cn.javaguide.springbootkafka01sendobjects.config;

import org.apache.kafka.clients.admin.NewTopic;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.support.converter.RecordMessageConverter;
import org.springframework.kafka.support.converter.StringJsonMessageConverter;

/**
 * @author shuang.kou
 */
@Configuration
public class KafkaConfig {

    @Value("${kafka.topic.my-topic}")
    String myTopic;
    @Value("${kafka.topic.my-topic2}")
    String myTopic2;

    /**
     * JSON消息转换器
     */
    @Bean
    public RecordMessageConverter jsonConverter() {
        return new StringJsonMessageConverter();
    }

    /**
     * 通过注入一个 NewTopic 类型的 Bean 来创建 topic，如果 topic 已存在，则会忽略。
     */
    @Bean
    public NewTopic myTopic() {
        return new NewTopic(myTopic, 2, (short) 1);
    }

    @Bean
    public NewTopic myTopic2() {
        return new NewTopic(myTopic2, 1, (short) 1);
    }
}

当我们到了这一步之后，你就可以试着运行项目了，运行成功后你会发现 Spring Boot 会为你创建两个topic:

  1. my-topic: partition 数为 2, replica 数为 1
  2. my-topic2:partition 数为 1, replica 数为 1

通过上一节说的：kafka-topics --describe --zookeeper zoo1:2181 命令查看或者直接通过IDEA 提供的 Kafka 可视化管理插件-Kafkalytic 来查看

Step3:创建要发送的消息实体类

package cn.javaguide.springbootkafka01sendobjects.entity;

public class Book {
    private Long id;
    private String name;

    public Book() {
    }

    public Book(Long id, String name) {
        this.id = id;
        this.name = name;
    }

    省略 getter/setter以及 toString方法
}

Step4:创建发送消息的生产者

这一步内容比较长，会一步一步优化生产者的代码。

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Service;

@Service
public class BookProducerService {

    private static final Logger logger = LoggerFactory.getLogger(BookProducerService.class);

    private final KafkaTemplate<String, Object> kafkaTemplate;

    public BookProducerService(KafkaTemplate<String, Object> kafkaTemplate) {
        this.kafkaTemplate = kafkaTemplate;
    }

    public void sendMessage(String topic, Object o) {
        kafkaTemplate.send(topic, o);
    }
}

我们使用Kafka 提供的 KafkaTemplate 调用 send()方法出入要发往的topic和消息内容即可很方便的完成消息的发送:

  kafkaTemplate.send(topic, o);

如果我们想要知道消息发送的结果的话，sendMessage方法这样写：

    public void sendMessage(String topic, Object o) {
        try {
            SendResult<String, Object> sendResult = kafkaTemplate.send(topic, o).get();
            if (sendResult.getRecordMetadata() != null) {
                logger.info("生产者成功发送消息到" + sendResult.getProducerRecord().topic() + "-> " + sendResult.getProducerRecord().value().toString());
            }
        } catch (InterruptedException | ExecutionException e) {
            e.printStackTrace();
        }
    }

但是这种属于同步的发送方式并不推荐，没有利用到 Future对象的特性。

KafkaTemplate 调用 send()方法实际上返回的是ListenableFuture 对象。

send()方法源码如下：

	@Override
	public ListenableFuture<SendResult<K, V>> send(String topic, @Nullable V data) {
		ProducerRecord<K, V> producerRecord = new ProducerRecord<>(topic, data);
		return doSend(producerRecord);
	}

ListenableFuture 是Spring提供了继承自Future 的接口。

ListenableFuture方法源码如下：

public interface ListenableFuture<T> extends Future<T> {
    void addCallback(ListenableFutureCallback<? super T> var1);

    void addCallback(SuccessCallback<? super T> var1, FailureCallback var2);

    default CompletableFuture<T> completable() {
        CompletableFuture<T> completable = new DelegatingCompletableFuture(this);
        this.addCallback(completable::complete, completable::completeExceptionally);
        return completable;
    }
}

继续优化sendMessage方法

    public void sendMessage(String topic, Object o) {

        ListenableFuture<SendResult<String, Object>> future = kafkaTemplate.send(topic, o);
        future.addCallback(new ListenableFutureCallback<SendResult<String, Object>>() {

            @Override
            public void onSuccess(SendResult<String, Object> sendResult) {
                logger.info("生产者成功发送消息到" + topic + "-> " + sendResult.getProducerRecord().value().toString());
            }
            @Override
            public void onFailure(Throwable throwable) {
                logger.error("生产者发送消息：{} 失败，原因：{}", o.toString(), throwable.getMessage());
            }
        });
    }

使用lambda表达式再继续优化：

    public void sendMessage(String topic, Object o) {

        ListenableFuture<SendResult<String, Object>> future = kafkaTemplate.send(topic, o);
        future.addCallback(result -> logger.info("生产者成功发送消息到topic:{} partition:{}的消息", result.getRecordMetadata().topic(), result.getRecordMetadata().partition()),
                ex -> logger.error("生产者发送消失败，原因：{}", ex.getMessage()));
    }

再来简单研究一下 send(String topic, @Nullable V data) 方法。

我们使用send(String topic, @Nullable V data)方法的时候实际会new 一个ProducerRecord对象发送，

	@Override
	public ListenableFuture<SendResult<K, V>> send(String topic, @Nullable V data) {
		ProducerRecord<K, V> producerRecord = new ProducerRecord<>(topic, data);
		return doSend(producerRecord);
	}

ProducerRecord类中有多个构造方法:

   public ProducerRecord(String topic, V value) {
        this(topic, null, null, null, value, null);
    }
    public ProducerRecord(String topic, Integer partition, Long timestamp, K key, V 
        ......
    }

如果我们想在发送的时候带上timestamp（时间戳）、key等信息的话，sendMessage()方法可以这样写：

    public void sendMessage(String topic, Object o) {
      // 分区编号最好为 null，交给 kafka 自己去分配
        ProducerRecord<String, Object> producerRecord = new ProducerRecord<>(topic, null, System.currentTimeMillis(), String.valueOf(o.hashCode()), o);
      
        ListenableFuture<SendResult<String, Object>> future = kafkaTemplate.send(producerRecord);
        future.addCallback(result -> logger.info("生产者成功发送消息到topic:{} partition:{}的消息", result.getRecordMetadata().topic(), result.getRecordMetadata().partition()),
                ex -> logger.error("生产者发送消失败，原因：{}", ex.getMessage()));
    }

Step5:创建消费消息的消费者

通过在方法上使用 @KafkaListener 注解监听消息，当有消息的时候就会通过 poll 下来消费。

import cn.javaguide.springbootkafka01sendobjects.entity.Book;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Service;

@Service
public class BookConsumerService {

    @Value("${kafka.topic.my-topic}")
    private String myTopic;
    @Value("${kafka.topic.my-topic2}")
    private String myTopic2;
    private final Logger logger = LoggerFactory.getLogger(BookProducerService.class);
    private final ObjectMapper objectMapper = new ObjectMapper();


    @KafkaListener(topics = {"${kafka.topic.my-topic}"}, groupId = "group1")
    public void consumeMessage(ConsumerRecord<String, String> bookConsumerRecord) {
        try {
            Book book = objectMapper.readValue(bookConsumerRecord.value(), Book.class);
            logger.info("消费者消费topic:{} partition:{}的消息 -> {}", bookConsumerRecord.topic(), bookConsumerRecord.partition(), book.toString());
        } catch (JsonProcessingException e) {
            e.printStackTrace();
        }
    }

    @KafkaListener(topics = {"${kafka.topic.my-topic2}"}, groupId = "group2")
    public void consumeMessage2(Book book) {
        logger.info("消费者消费{}的消息 -> {}", myTopic2, book.toString());
    }
}

Step6:创建一个 Rest Controller

import cn.javaguide.springbootkafka01sendobjects.entity.Book;
import cn.javaguide.springbootkafka01sendobjects.service.BookProducerService;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;

import java.util.concurrent.atomic.AtomicLong;

/**
 * @author shuang.kou
 */
@RestController
@RequestMapping(value = "/book")
public class BookController {
    @Value("${kafka.topic.my-topic}")
    String myTopic;
    @Value("${kafka.topic.my-topic2}")
    String myTopic2;
    private final BookProducerService producer;
    private AtomicLong atomicLong = new AtomicLong();

    BookController(BookProducerService producer) {
        this.producer = producer;
    }

    @PostMapping
    public void sendMessageToKafkaTopic(@RequestParam("name") String name) {
        this.producer.sendMessage(myTopic, new Book(atomicLong.addAndGet(1), name));
        this.producer.sendMessage(myTopic2, new Book(atomicLong.addAndGet(1), name));
    }
}

Step7:测试

输入命令：

curl -X POST -F 'name=Java' http://localhost:9090/book

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