springboot kafka集成(实现producer和consumer)

本文内容纲要：

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：Kafkaproducer

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

packagecom.kangaroo.sentinel.collect.configuration; importjava.util.HashMap; importjava.util.Map; importorg.apache.kafka.clients.producer.ProducerConfig; importorg.apache.kafka.common.serialization.StringSerializer; importorg.springframework.beans.factory.annotation.Value; importorg.springframework.context.annotation.Bean; importorg.springframework.context.annotation.Configuration; importorg.springframework.kafka.annotation.EnableKafka; importorg.springframework.kafka.core.DefaultKafkaProducerFactory; importorg.springframework.kafka.core.KafkaTemplate; importorg.springframework.kafka.core.ProducerFactory; @Configuration @EnableKafka publicclassKafkaProducerConfig{ @Value("${kafka.producer.servers}") privateStringservers; @Value("${kafka.producer.retries}") privateintretries; @Value("${kafka.producer.batch.size}") privateintbatchSize; @Value("${kafka.producer.linger}") privateintlinger; @Value("${kafka.producer.buffer.memory}") privateintbufferMemory; publicMap<String,Object>producerConfigs(){ Map<String,Object>props=newHashMap<>(); 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); returnprops; } publicProducerFactory<String,String>producerFactory(){ returnnewDefaultKafkaProducerFactory<>(producerConfigs()); } @Bean publicKafkaTemplate<String,String>kafkaTemplate(){ returnnewKafkaTemplate<String,String>(producerFactory()); } }

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

packagecom.kangaroo.sentinel.collect.controller; importcom.kangaroo.sentinel.common.response.Response; importcom.kangaroo.sentinel.common.response.ResultCode; importorg.slf4j.Logger; importorg.slf4j.LoggerFactory; importorg.springframework.beans.factory.annotation.Autowired; importorg.springframework.kafka.core.KafkaTemplate; importorg.springframework.web.bind.annotation.*; importjavax.servlet.http.HttpServletRequest; importjavax.servlet.http.HttpServletResponse; @RestController @RequestMapping("/kafka") publicclassCollectController{ protectedfinalLoggerlogger=LoggerFactory.getLogger(this.getClass()); @Autowired privateKafkaTemplatekafkaTemplate; @RequestMapping(value="/send",method=RequestMethod.GET) publicResponsesendKafka(HttpServletRequestrequest,HttpServletResponseresponse){ try{ Stringmessage=request.getParameter("message"); logger.info("kafka的消息={}"，message); kafkaTemplate.send("test","key",message); logger.info("发送kafka成功."); returnnewResponse(ResultCode.SUCCESS,"发送kafka成功",null); }catch(Exceptione){ logger.error("发送kafka失败",e); returnnewResponse(ResultCode.EXCEPTION,"发送kafka失败",null); } } }

3、configuration：kafkaconsumer

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

packagecom.kangaroo.sentinel.collect.configuration; importorg.apache.kafka.clients.consumer.ConsumerConfig; importorg.apache.kafka.common.serialization.StringDeserializer; importorg.springframework.beans.factory.annotation.Value; importorg.springframework.context.annotation.Bean; importorg.springframework.context.annotation.Configuration; importorg.springframework.kafka.annotation.EnableKafka; importorg.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory; importorg.springframework.kafka.config.KafkaListenerContainerFactory; importorg.springframework.kafka.core.ConsumerFactory; importorg.springframework.kafka.core.DefaultKafkaConsumerFactory; importorg.springframework.kafka.listener.ConcurrentMessageListenerContainer; importjava.util.HashMap; importjava.util.Map; @Configuration @EnableKafka publicclassKafkaConsumerConfig{ @Value("${kafka.consumer.servers}") privateStringservers; @Value("${kafka.consumer.enable.auto.commit}") privatebooleanenableAutoCommit; @Value("${kafka.consumer.session.timeout}") privateStringsessionTimeout; @Value("${kafka.consumer.auto.commit.interval}") privateStringautoCommitInterval; @Value("${kafka.consumer.group.id}") privateStringgroupId; @Value("${kafka.consumer.auto.offset.reset}") privateStringautoOffsetReset; @Value("${kafka.consumer.concurrency}") privateintconcurrency; @Bean publicKafkaListenerContainerFactory<ConcurrentMessageListenerContainer<String,String>>kafkaListenerContainerFactory(){ ConcurrentKafkaListenerContainerFactory<String,String>factory=newConcurrentKafkaListenerContainerFactory<>(); factory.setConsumerFactory(consumerFactory()); factory.setConcurrency(concurrency); factory.getContainerProperties().setPollTimeout(1500); returnfactory; } publicConsumerFactory<String,String>consumerFactory(){ returnnewDefaultKafkaConsumerFactory<>(consumerConfigs()); } publicMap<String,Object>consumerConfigs(){ Map<String,Object>propsMap=newHashMap<>(); 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); returnpropsMap; } @Bean publicListenerlistener(){ returnnewListener(); } }

newListener()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kafkatopic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。

packagecom.kangaroo.sentinel.collect.configuration; importorg.apache.kafka.clients.consumer.ConsumerRecord; importorg.slf4j.Logger; importorg.slf4j.LoggerFactory; importorg.springframework.kafka.annotation.KafkaListener; publicclassListener{ protectedfinalLoggerlogger=LoggerFactory.getLogger(this.getClass()); @KafkaListener(topics={"test"}) publicvoidlisten(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。

本文内容总结：

原文链接：https://www.cnblogs.com/kangoroo/p/7353330.html