springboot kafka集成(实现producer和consumer)

时间：2022-10-15 06:38:16

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。

相关文章