在springboot项目中集成kafka收发message

朱雀 2022-04-18 02:51 238阅读 0赞

from：[https://www.cnblogs.com/kangoroo/p/7353330.html][https_www.cnblogs.com_kangoroo_p_7353330.html]

***、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

![复制代码][copycode.gif]

#============== 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

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***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

![复制代码][copycode.gif]

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());
        }
    }

![复制代码][copycode.gif]

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

![复制代码][copycode.gif]

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);
            }
        }
    
    }

![复制代码][copycode.gif]

***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

![复制代码][copycode.gif]

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();
        }
    
    }

![复制代码][copycode.gif]

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。

![复制代码][copycode.gif]

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());
        }
    }

![复制代码][copycode.gif]

***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。

[https_www.cnblogs.com_kangoroo_p_7353330.html]: https://www.cnblogs.com/kangoroo/p/7353330.html
[copycode.gif]: /images/20220418/e0792b21eecb4bd79dd0614edd79f63d.png