SpringBoot整合消息队列工具kafka

一、前言

之前整理了kafka在windows下的安装过程，也通过shell命令进行了消息产生者和消息消费者的创建及消息发送，所以想到把kafka与最流行的SpringBoot的框架进行整合，与项目结合，进行消息的发送。

二、整合开始

1.SpringBoot工程搭建，此处不多讲，可以看之前的帖子，项目结构如下

2.在pom文件中加入kafka的依赖包

<!-- kafka依赖添加  -->
<dependency>
          <groupId>org.springframework.kafka</groupId>
          <artifactId>spring-kafka</artifactId>
          <version>1.1.1.RELEASE</version>
      </dependency>

3.在application中填写kafka相关配置

#服务器端口
server.port=8088
#配置kafka
#zk地址
kafka.consumer.zookeeper.connect=172.18.229.49:2181
#消费者服务提供配置
kafka.consumer.servers=172.18.229.49:9092
#是否自动提交
kafka.consumer.enable.auto.commit=true
#超时时间
kafka.consumer.session.timeout=6000
kafka.consumer.auto.commit.interval=100
kafka.consumer.auto.offset.reset=latest
#配置topics
kafka.consumer.topic=yangTest
kafka.consumer.group.id=yangTest
kafka.consumer.concurrency=10
#消息提供者地址
kafka.producer.servers=172.18.229.49:9092
kafka.producer.retries=0
kafka.producer.batch.size=4096
kafka.producer.linger=1
kafka.producer.buffer.memory=40960

4.在kafka包下创建消息提供者配置类KafkaProducerConfig

package com.yang.kafka;
import java.util.HashMap;
import java.util.Map;

import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.common.serialization.StringSerializer;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;

/**
 * kafka生产者配置
 * @author Java小白
 *
 */
@Configuration
@EnableKafka
public class KafkaProducerConfig {

    @Value("${kafka.producer.servers}")
    private String servers;
    @Value("${kafka.producer.retries}")
    private int retries;
    @Value("${kafka.producer.batch.size}")
    private int batchSize;
    @Value("${kafka.producer.linger}")
    private int linger;
    @Value("${kafka.producer.buffer.memory}")
    private int bufferMemory;


    /**
     * 配置生产者信息（消费提供者信息）
     * @return
     */
    public Map<String, Object> producerConfigs() {
        Map<String, Object> props = new HashMap<>();
        props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, servers);
        props.put(ProducerConfig.RETRIES_CONFIG, retries);
        props.put(ProducerConfig.BATCH_SIZE_CONFIG, batchSize);
        props.put(ProducerConfig.LINGER_MS_CONFIG, linger);
        props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, bufferMemory);
        props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        return props;
    }

    /**
     * 消费工厂
     * @return
     */
    public ProducerFactory<String, String> producerFactory() {
        return new DefaultKafkaProducerFactory<>(producerConfigs());
    }

    /**
     * 消息发送工具类
     * @return
     */
    @Bean
    public KafkaTemplate<String, String> kafkaTemplate() {
    	//需要指定消费工厂
        return new KafkaTemplate<String, String>(producerFactory());
    }
}

5.在kafka包下创建消费者配置类KafkaConsumerConfig

package com.yang.kafka;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;
import org.springframework.kafka.config.KafkaListenerContainerFactory;
import org.springframework.kafka.core.ConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
import org.springframework.kafka.listener.ConcurrentMessageListenerContainer;

import java.util.HashMap;
import java.util.Map;

@Configuration
@EnableKafka
public class KafkaConsumerConfig {

    @Value("${kafka.consumer.servers}")
    private String servers;
    @Value("${kafka.consumer.enable.auto.commit}")
    private boolean enableAutoCommit;
    @Value("${kafka.consumer.session.timeout}")
    private String sessionTimeout;
    @Value("${kafka.consumer.auto.commit.interval}")
    private String autoCommitInterval;
    @Value("${kafka.consumer.group.id}")
    private String groupId;
    @Value("${kafka.consumer.auto.offset.reset}")
    private String autoOffsetReset;
    @Value("${kafka.consumer.concurrency}")
    private int concurrency;
    @Bean
    public KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<String, String>> kafkaListenerContainerFactory() {
        ConcurrentKafkaListenerContainerFactory<String, String> factory = new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(consumerFactory());
        factory.setConcurrency(concurrency);
        factory.getContainerProperties().setPollTimeout(1500);
        return factory;
    }

    /**
     * 消费者工厂
     * @return
     */
    public ConsumerFactory<String, String> consumerFactory() {
        return new DefaultKafkaConsumerFactory<>(consumerConfigs());
    }


    /**
     * 消费者配置
     * @return
     */
    public Map<String, Object> consumerConfigs() {
        Map<String, Object> propsMap = new HashMap<>();
        propsMap.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, servers);
        propsMap.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, enableAutoCommit);
        propsMap.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, autoCommitInterval);
        propsMap.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, sessionTimeout);
        propsMap.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        propsMap.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        propsMap.put(ConsumerConfig.GROUP_ID_CONFIG, groupId);
        propsMap.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, autoOffsetReset);
        return propsMap;
    }
    /**
     * 配置接收消息的类-消息监听器
     * @return
     */
    @Bean
    public Listener listener() {
        return new Listener();
    }

}

6.配置KafkaConsumerConfig中指定消息监听器Listener

package com.yang.kafka;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.kafka.annotation.KafkaListener;

public class Listener {
    protected final Logger logger = LoggerFactory.getLogger(this.getClass());


    /**
     * 配置kafka消费监听者
     * @param record
     */
    @KafkaListener(topics = {"yangTest"}) //指定topics
    public void listen(ConsumerRecord<?, ?> record) {
        logger.info("kafka的key: " + record.key());
        logger.info("kafka的value: " + record.value().toString());
    }
}

7.在controller包创建一个controller，用来从浏览器输入消息源CollectController

package com.yang.controller;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.web.bind.annotation.*;


@RestController
@RequestMapping("/kafka")
public class CollectController {
    protected final Logger logger = LoggerFactory.getLogger(this.getClass());
    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;

    @RequestMapping(value = "/send", method = RequestMethod.GET)
    public String sendKafka(@RequestParam("message") String message) {
        try {
            logger.info("kafka的消息={}",message);
            //发送消息 指定topics和消息内容
            kafkaTemplate.send("yangTest", "key", message);
            logger.info("发送kafka成功.");
           return "发送kafka成功";
        } catch (Exception e) {
            logger.error("发送kafka失败", e);
            return "发送kafka失败";
        }
    }

}

8.在boot包下创建启动类StartApplication

package com.yang.boot;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.ComponentScan;

@SpringBootApplication //SpringBoot启动类注解
@EnableAutoConfiguration  //开启自动化配置
@ComponentScan("com.yang") //类似于Spring的基础类扫描包，用来扫描实体，接口和控制器
public class StartApplication {
    public static void main(String[] args) {
        SpringApplication.run(StartApplication.class, args);
    }
}

9.在本地的kafka包下执行shell脚本，启动kafka服务

.\bin\windows\kafka-server-start.bat .\config\server.properties

10.在启动类上右键启动服务，浏览器访问localhost:8088/kafka/send?message=hello kafka

11.观察控制台日志，查看日志输入，消息发送成功，Listener监听消息成功,此时kafka整合成功

2019-01-31 10:27:02.656  INFO 5236 --- [nio-8088-exec-4] com.yang.controller.CollectController    : kafka的消息=hello kafka
2019-01-31 10:27:02.657  INFO 5236 --- [nio-8088-exec-4] com.yang.controller.CollectController    : 发送kafka成功.
2019-01-31 10:27:02.661  INFO 5236 --- [afka-consumer-1] com.yang.kafka.Listener                  : kafka的key: key
2019-01-31 10:27:02.661  INFO 5236 --- [afka-consumer-1] com.yang.kafka.Listener                  : kafka的value: hello kafka

三、下载地址及问题描述

1.在整合的过程中，如果出现超时异常，请检查zk客户端是否启动，kafka客户端是否已经启动

org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 60000 ms.

2019-01-31 10:32:28.833  INFO 8448 --- [nio-8088-exec-4] com.yang.controller.CollectController    : 发送kafka成功.
2019-01-31 10:32:29.030 ERROR 8448 --- [nio-8088-exec-5] o.s.k.support.LoggingProducerListener    : Exception thrown when sending a message with key='key' and payload='hello kafka' to topic yangTest:

2.可通过命令来查看当前客户端下已经存在的topics

./kafka-topics.bat --list --zookeeper localhost:2181

3.项目源码下载地址

点我下载