准备工作
- 安装kafka+zookeeper环境
- 利用命令创建好topic
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Pom文件,引入spring-kafka jar包这里需要注意2个地方:
- kafka-clients 包版本与服务器端kafka-clients版本保持一致(查看服务器kafka版本方法 在kafka安装目录下libs 中查找kafka-clients开头的jar文件)
- 引入的spring-kafka 版本在2.0或者2.X 时Spring版本在5.0才能支持
..........
<dependency> <groupId>org.springframework.kafka</groupId> <artifactId>spring-kafka</artifactId> <version>2.1.8.RELEASE</version> </dependency>
..........
参考官网 http://kafka.apache.org/documentation/
XML配置方式
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生产者
配置:
<?xml version="1.0" encoding="UTF-8"?> <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:context="http://www.springframework.org/schema/context" xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.0.xsd http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context.xsd"> <context:property-placeholder location="classpath*:config/application.properties" /> <!-- 定义producer的参数 --> <bean id="producerProperties" class="java.util.HashMap"> <constructor-arg> <map> <entry key="bootstrap.servers" value="${bootstrap.servers}" /> <entry key="group.id" value="${group.id}" /> <entry key="retries" value="${retries}" /> <entry key="batch.size" value="${batch.size}" /> <entry key="linger.ms" value="${linger.ms}" /> <entry key="buffer.memory" value="${buffer.memory}" /> <entry key="acks" value="${acks}" /> <entry key="key.serializer" value="org.apache.kafka.common.serialization.StringSerializer" /> <entry key="value.serializer" value="org.apache.kafka.common.serialization.StringSerializer" /> </map> </constructor-arg> </bean> <!-- 创建kafkatemplate需要使用的producerfactory bean --> <bean id="producerFactory" class="org.springframework.kafka.core.DefaultKafkaProducerFactory"> <constructor-arg> <ref bean="producerProperties" /> </constructor-arg> </bean> <!-- 创建kafkatemplate bean,使用的时候,只需要注入这个bean,即可使用template的send消息方法 --> <bean id="kafkaTemplate" class="org.springframework.kafka.core.KafkaTemplate"> <constructor-arg ref="producerFactory" /> <constructor-arg name="autoFlush" value="true" /> <property name="defaultTopic" value="default" /> </bean> </beans>
如上图,xml主要配置了KafkaTemplate的构造参数producerFactory和autoFlush,对应了一个KafkaTemplate源码中的2参构造函数。
- producerProperties:设置生产者工厂需要的配置
- producerFactory:定义了生产者工厂构造方法
- kafkaTemplate:定义了使用producerFactory和是否自动刷新,2个参数来构造kafka生产者模板类
发送消息:
ListenableFuture<SendResult<String, String>> listenableFuture = kafkaTemplate.send("topic", "partition","key","data");
//发送成功回调 SuccessCallback<SendResult<String, String>> successCallback = new SuccessCallback<SendResult<String, String>>() { @Override public void onSuccess(SendResult<String, String> result) { //成功业务逻辑 } }
//发送失败回调 FailureCallback failureCallback = new FailureCallback() { @Override public void onFailure(Throwable ex) { //失败业务逻辑 } } listenableFuture.addCallback(successCallback, failureCallback);
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消费者
配置:
<!-- 1.定义consumer的参数 --> <bean id="consumerProperties" class="java.util.HashMap"> <constructor-arg> <map> <entry key="bootstrap.servers" value="${bootstrap.servers}" /> <entry key="group.id" value="${group.id}" /> <entry key="enable.auto.commit" value="${enable.auto.commit}" /> <entry key="session.timeout.ms" value="${session.timeout.ms}" /> <entry key="key.deserializer" value="org.apache.kafka.common.serialization.StringDeserializer" /> <entry key="value.deserializer" value="org.apache.kafka.common.serialization.StringDeserializer" /> </map> </constructor-arg> </bean> <!-- 2.创建consumerFactory bean --> <bean id="consumerFactory" class="org.springframework.kafka.core.DefaultKafkaConsumerFactory" > <constructor-arg> <ref bean="consumerProperties" /> </constructor-arg> </bean> <!-- 3.定义消费实现类 --> <bean id="kafkaConsumerService" class="xxx.service.impl.KafkaConsumerSerivceImpl" /> <!-- 4.消费者容器配置信息 --> <bean id="containerProperties" class="org.springframework.kafka.listener.config.ContainerProperties"> <!-- topic --> <constructor-arg name="topics"> <list> <value>${kafka.consumer.topic.credit.for.lease}</value> <value>${loan.application.feedback.topic}</value> </list> </constructor-arg> <property name="messageListener" ref="kafkaConsumerService" /> </bean> <!-- 5.消费者并发消息监听容器,执行doStart()方法 --> <bean id="messageListenerContainer" class="org.springframework.kafka.listener.ConcurrentMessageListenerContainer" init-method="doStart" > <constructor-arg ref="consumerFactory" /> <constructor-arg ref="containerProperties" /> <property name="concurrency" value="${concurrency}" /> </bean>
- consumerProperties-》consumerFactory 载入配置构造消费者工厂
- messageListener-》containerProperties 载入容器配置(topics)
- consumerFactory+containerProperties-》messageListenerContainer 容器配置(topics)+消息监听器,构造一个并发消息监听容器,并执行初始化方法doStart
- 需要注意. KafkaConsumerSerivceImpl 此类 需要实现 MessageListener 接口
消费消息:
方案1:直接实现MessageListener接口,复写onMessage方法,实现自定义消费业务逻辑。
public class KafkaConsumerSerivceImpl implements MessageListener<String, String> { @Override public void onMessage(ConsumerRecord<String, String> data) { //根据不同主题,消费 if("主题1".equals(data.topic())){ //逻辑1 }else if("主题2".equals(data.topic())){ //逻辑2 } } }
方案2:使用@KafkaListener注解,并设置topic,支持SPEL表达式。这样方便拆分多个不同topic处理不同业务逻辑。(特别是有自己的事务的时候,尤其方便)
import org.springframework.kafka.annotation.KafkaListener; public class KafkaConsumerSerivceImpl { @KafkaListener(topics = "${templar.aggrement.agreementWithhold.topic}") void templarAgreementNoticewithhold(ConsumerRecord<String, String> data){ //消费业务逻辑 } }
Java注解方式
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生产者
配置:
/** * @description kafka 生产者配置 */ @Configuration @EnableKafka public class KafkaProducerConfig { public KafkaProducerConfig(){ System.out.println("kafka生产者配置"); }
@Bean public ProducerFactory<Integer, String> producerFactory() { return new DefaultKafkaProducerFactory(producerProperties()); } @Bean public Map<String, Object> producerProperties() { Map<String, Object> props = new HashMap<String, Object>(); props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, PropertiesUtil.getInstance().getString("kafka.producer.bootstrap.servers")); props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, PropertiesUtil.getInstance().getString("kafka.producer.key.serializer")); props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,PropertiesUtil.getInstance().getString("kafka.producer.value.serializer")); props.put(ProducerConfig.RETRIES_CONFIG,PropertiesUtil.getInstance().getInt("kafka.producer.retries")); props.put(ProducerConfig.BATCH_SIZE_CONFIG,PropertiesUtil.getInstance().getInt("kafka.producer.batch.size",1048576)); props.put(ProducerConfig.LINGER_MS_CONFIG,PropertiesUtil.getInstance().getInt("kafka.producer.linger.ms")); props.put(ProducerConfig.BUFFER_MEMORY_CONFIG,PropertiesUtil.getInstance().getLong("kafka.producer.buffer.memory",33554432L)); props.put(ProducerConfig.ACKS_CONFIG,PropertiesUtil.getInstance().getString("kafka.producer.acks","all")); return props; } @Bean public KafkaTemplate<Integer, String> kafkaTemplate() { KafkaTemplate kafkaTemplate = new KafkaTemplate<Integer, String>(producerFactory(),true); kafkaTemplate.setDefaultTopic(PropertiesUtil.getInstance().getString("kafka.producer.defaultTopic","default")); return kafkaTemplate; } }
发送消息:
跟xml配置一样。
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消费者
配置:
/** * @description kafka 消费者配置 */ @Configuration @EnableKafka public class KafkaConsumerConfig { public KafkaConsumerConfig(){ System.out.println("kafka消费者配置加载..."); }
@Bean KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<Integer, String>> kafkaListenerContainerFactory() { ConcurrentKafkaListenerContainerFactory<Integer, String> factory = new ConcurrentKafkaListenerContainerFactory(); factory.setConsumerFactory(consumerFactory()); factory.setConcurrency(3); factory.getContainerProperties().setPollTimeout(3000); return factory; } @Bean public ConsumerFactory<Integer, String> consumerFactory() { return new DefaultKafkaConsumerFactory(consumerProperties()); } @Bean public Map<String, Object> consumerProperties() { Map<String, Object> props= new HashMap<String, Object>(); props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, PropertiesUtil.getInstance().getString("kafka.consumer.bootstrap.servers")); props.put(ConsumerConfig.GROUP_ID_CONFIG, PropertiesUtil.getInstance().getString("kafka.consumer.group.id")); props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, PropertiesUtil.getInstance().getString("kafka.consumer.enable.auto.commit")); props.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, PropertiesUtil.getInstance().getString("kafka.consumer.auto.commit.interval.ms")); props.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, PropertiesUtil.getInstance().getString("kafka.consumer.session.timeout.ms")); props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, PropertiesUtil.getInstance().getString("kafka.consumer.key.deserializer")); props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, PropertiesUtil.getInstance().getString("kafka.consumer.value.deserializer")); return props; } @Bean public KafkaConsumerListener kafkaConsumerListener(){ return new KafkaConsumerListener(); } }
消费消息:
跟xml配置一样。
引用: