最优质网--最有指望<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/dbaasKafkaConfig.properties" /> -->
<!-- 1、定义consumer参数 -->
<!-- 采用原始xml生成bean方式 -->
<bean id="consumerProperties" class="java.util.HashMap">
<constructor-arg>
<map>
<entry key="bootstrap.servers" value="${kafka.consumer.bootstrap.servers}"></entry>
<entry key="group.id" value="${kafka.consumer.group.id}"></entry>
<entry key="enable.auto.commit" value="${kafka.consumer.enable.auto.commit}"></entry>
<entry key="session.timeout.ms" value="${kafka.consumer.session.timeout.ms}"></entry>
<entry key="auto.commit.interval.ms" value="${kafka.consumer.auto.commit.interval.ms}"></entry>
<entry key="retry.backoff.ms" value="100"></entry>
<entry key="key.deserializer"
value="org.apache.kafka.common.serialization.StringDeserializer" />
<entry key="value.deserializer"
value="org.apache.kafka.common.serialization.StringDeserializer" />
</map>
</constructor-arg>
</bean>
<!--2 创建consumerFactory bean -->
<bean id="consumerFactory" class="org.springframework.kafka.core.DefaultKafkaConsumerFactory">
<constructor-arg>
<ref bean="consumerProperties"></ref>
</constructor-arg>
</bean>
<!--3 定义消费实现 -->
<bean id="kafkaConsumerService" class="...service.kafka.KafkaConsumerSerivce"/>
<!--4 消费者容器配置信息 -->
<bean id="containerProperties" class="org.springframework.kafka.listener.ContainerProperties">
<constructor-arg name="topics">
<list>
<value>${kafka.consumer.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() -->
<bean id="messageListenerContainer" class="org.springframework.kafka.listener.KafkaMessageListenerContainer" init-method="doStart">
<constructor-arg ref="consumerFactory"></constructor-arg>
<constructor-arg ref="containerProperties"></constructor-arg>
</bean>
<!--6 定义producer参数 -->
<bean id="producerProperties" class="java.util.HashMap">
<constructor-arg>
<map>
<entry key="bootstrap.servers" value="${kafka.producer.bootstrap.servers}"></entry>
<entry key="retries" value="${kafka.producer.retries}"></entry>
<entry key="batch.size" value="${kafka.producer.batch.size}"></entry>
<entry key="linger.ms" value="${kafka.producer.linger.ms}"></entry>
<entry key="buffer.memory" value="${kafka.producer.buffer.memory}"></entry>
<entry key="acks" value="${kafka.producer.acks}"></entry>
<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 使用时候需要注入bean即可 -->
<bean id="kafkaTemplate" class="org.springframework.kafka.core.KafkaTemplate">
<constructor-arg ref="producerFactory" />
<constructor-arg name="autoFlush" value="true" />
<property name="defaultTopic" value="${kafka.producer.defaultTopic}"></property>
</bean>
<bean id="kafkaProducerSerivce" class="...service.kafka.KafkaProducerSerivce"></bean>
</beans>
public class KafkaConsumerSerivce implements MessageListener<Integer, String> {
private Logger log=LoggerFactory.getLogger(this.getClass());
@Autowired
KafkaProducerSerivce kafkaProducerService;
@Autowired
IEdbCommonService commService;
/* (non-Javadoc)
* @see org.springframework.kafka.listener.GenericMessageListener#onMessage(java.lang.Object)
*/
@Override
public void onMessage(ConsumerRecord<Integer, String> record) {
...
}
}
public class KafkaProducerSerivce{
@Autowired
KafkaTemplate<String, String> kafkaTemplate;
private Logger log=LoggerFactory.getLogger(this.getClass());
public <K,T>void sendMessage(String topic, String data) {
ListenableFuture<SendResult<String, String>> listenableFuture = null;
listenableFuture = kafkaTemplate.send(topic, data);
/*if (kafkaTemplate.getDefaultTopic().equals(topic)) {
kafkaTemplate.send(topic, data);
}else {
listenableFuture = kafkaTemplate.send(topic, partition, timestamp, key, data);
}*/
//发送成功回调
SuccessCallback<SendResult<String, String>> successCallback = new SuccessCallback<SendResult<String, String>>() {
public void onSuccess(SendResult<String, String> result) {
//成功业务逻辑
log.info("KafkaProducterSerivce send success");
}
};
//发送失败回调
FailureCallback failureCallback = new FailureCallback() {
public void onFailure(Throwable ex) {
//失败重试
throw new RuntimeException(ex);
}
};
listenableFuture.addCallback(successCallback, failureCallback);
}
}
配置文件：
#####################kafka consumer ###################### kafka.consumer.bootstrap.servers= #如何设置自动提交#如果为true，消费者的偏移量将在后台定期提交 kafka.consumer.enable.auto.commit=true kafka.consumer.auto.commit.interval.ms=1000 #消费者群组ID，发布-订阅模式，即如果一个生产者，多个消费者都要消费，那么需要定义自己的群组，同一群组内的消费者只有一个能消费到消息 kafka.consumer.group.id=groupName kafka.consumer.topic=topicName #消费监听器容器并发数 kafka.consumer.concurrency=1 #在使用Kafka的组管理时，用于检铡消费者故障的起时 kafka.consumer.session.timeout.ms=30000 kafka.consumer.key.deserializer=org.apache.kafka.common.serialization.StringDeserializer kafka.consumer.value.deserializer=org.apache.kafka.common.serialization.StringDeserializer #brokers集群 kafka.producer.bootstrap.servers= #即所有副本都同步到数据时send方法才返回, 以此来完全判断数据是否发送成功, 理论上来讲数据不会丢失. kafka.producer.acks=all #发送失败重试次数 kafka.producer.retries=3 #批处理延迟时间上限：即1ms过后，不管是否达到批处理数，都直接发送一次请求 kafka.producer.linger.ms=10 #33554432即32MB的批处理缓冲区 kafka.producer.buffer.memory=40960 #批处理条数：当多个记录被发送到同一个分区时，生产者会尝试将记录合并到更少的请求中◊这有助于客户端和服务器的性能 kafka.producer.batch.size=4096 kafka.producer.defaultTopic=producerTopicName kafka.producer.key.serializer=org.apache.kafka.common.serialization.StringSerializer kafka.producer.value.serializer=org.apache.kafka.common.serialization.StringSerializer
需要的jar包：
spring-kafka 2.2.1
spring-message 4.1.6
kafka-client 2.1.0
版本号供参考，可以是其他版本的，具体也可参考spring-kafka官网。
https://spring.io/projects/spring-kafka
xml方式有个弊端，就是如果没有安装kafka服务是无法启动程序的。
可使用其他方式，比如注解，或者显式调用。
未经允许不得转载：最优质网--最有指望 » spring-kafka xml 方式 spring-kafka xml
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