springboot kafka集成(实现producer和consumer)

用户1225216

发布于 2018-03-05 14:32:57

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发布于 2018-03-05 14:32:57

文章被收录于专栏：扎心了老铁扎心了老铁

本文介绍如何在springboot项目中集成kafka收发message。

1、先解决依赖

springboot相关的依赖我们就不提了，和kafka相关的只依赖一个spring-kafka集成包

<dependency>
            <groupId>org.springframework.kafka</groupId>
            <artifactId>spring-kafka</artifactId>
            <version>1.1.1.RELEASE</version>
        </dependency>

这里我们先把配置文件展示一下

#============== kafka ===================
kafka.consumer.zookeeper.connect=10.93.21.21:2181
kafka.consumer.servers=10.93.21.21:9092
kafka.consumer.enable.auto.commit=true
kafka.consumer.session.timeout=6000
kafka.consumer.auto.commit.interval=100
kafka.consumer.auto.offset.reset=latest
kafka.consumer.topic=test
kafka.consumer.group.id=test
kafka.consumer.concurrency=10

kafka.producer.servers=10.93.21.21:9092
kafka.producer.retries=0
kafka.producer.batch.size=4096
kafka.producer.linger=1
kafka.producer.buffer.memory=40960

2、Configuration：Kafka producer

1）通过@Configuration、@EnableKafka，声明Config并且打开KafkaTemplate能力。

2）通过@Value注入application.properties配置文件中的kafka配置。

3）生成bean，@Bean

package com.kangaroo.sentinel.collect.configuration;

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;

@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;


    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;
    }

    public ProducerFactory<String, String> producerFactory() {
        return new DefaultKafkaProducerFactory<>(producerConfigs());
    }

    @Bean
    public KafkaTemplate<String, String> kafkaTemplate() {
        return new KafkaTemplate<String, String>(producerFactory());
    }
}

实验我们的producer，写一个Controller。想topic=test，key=key，发送消息message

package com.kangaroo.sentinel.collect.controller;

import com.kangaroo.sentinel.common.response.Response;
import com.kangaroo.sentinel.common.response.ResultCode;

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.*;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;


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

    @RequestMapping(value = "/send", method = RequestMethod.GET)
    public Response sendKafka(HttpServletRequest request, HttpServletResponse response) {
        try {
            String message = request.getParameter("message");
            logger.info("kafka的消息={}"， message);
            kafkaTemplate.send("test", "key", message);
            logger.info("发送kafka成功.");
            return new Response(ResultCode.SUCCESS, "发送kafka成功", null);
        } catch (Exception e) {
            logger.error("发送kafka失败", e);
            return new Response(ResultCode.EXCEPTION, "发送kafka失败", null);
        }
    }

}

3、configuration：kafka consumer

1）通过@Configuration、@EnableKafka，声明Config并且打开KafkaTemplate能力。

2）通过@Value注入application.properties配置文件中的kafka配置。

3）生成bean，@Bean

package com.kangaroo.sentinel.collect.configuration;

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;
    }

    public ConsumerFactory<String, String> consumerFactory() {
        return new DefaultKafkaConsumerFactory<>(consumerConfigs());
    }


    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;
    }

    @Bean
    public Listener listener() {
        return new Listener();
    }

}

new Listener()生成一个bean用来处理从kafka读取的数据。Listener简单的实现demo如下：只是简单的读取并打印key和message值

@KafkaListener中topics属性用于指定kafka topic名称，topic名称由消息生产者指定，也就是由kafkaTemplate在发送消息时指定。

package com.kangaroo.sentinel.collect.configuration;

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());


    @KafkaListener(topics = {"test"})
    public void listen(ConsumerRecord<?, ?> record) {
        logger.info("kafka的key: " + record.key());
        logger.info("kafka的value: " + record.value().toString());
    }
}

tips:

1）我没有介绍如何安装配置kafka，配置kafka时最好用完全bind网络ip的方式，而不是localhost或者127.0.0.1

2）最好不要使用kafka自带的zookeeper部署kafka，可能导致访问不通。

3）理论上consumer读取kafka应该是通过zookeeper，但是这里我们用的是kafkaserver的地址，为什么没有深究。

4）定义监听消息配置时，GROUP_ID_CONFIG配置项的值用于指定消费者组的名称，如果同组中存在多个监听器对象则只有一个监听器对象能收到消息。

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原始发表：2017-08-13 ，如有侵权请联系 cloudcommunity@tencent.com 删除

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