Springboot集成Kafka实现producer和consumer的示例代码

本文介绍如何在springboot项目中集成kafka收发message。

kafka是一种高吞吐量的分布式发布订阅消息系统，有如下特性：通过o(1)的磁盘数据结构提供消息的持久化，这种结构对于即使数以tb的消息存储也能够保持长时间的稳定性能。高吞吐量：即使是非常普通的硬件kafka也可以支持每秒数百万的消息。支持通过kafka服务器和消费机集群来分区消息。支持hadoop并行数据加载。

安装kafka

因为安装kafka需要zookeeper的支持，所以windows安装时需要将zookeeper先安装上，然后将kafka安装好就可以了。下面我给出mac安装的步骤以及需要注意的点吧，windows的配置除了所在位置不太一样其他几乎没什么不同。

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									brew install kafka

对，就是这么简单，mac上一个命令就可以搞定了，这个安装过程可能需要等一会儿，应该是和网络状况有关系。安装提示信息可能有错误消息，如"error: could not link: /usr/local/share/doc/homebrew" 这个没关系，自动忽略掉了。最终我们看到下面的样子就成功咯。

==> summary ðŸº/usr/local/cellar/kafka/1.1.0: 157 files, 47.8mb

安装的配置文件位置如下，根据自己的需要修改端口号什么的就可以了。

安装的zoopeeper和kafka的位置 /usr/local/cellar/

配置文件 /usr/local/etc/kafka/server.properties /usr/local/etc/kafka/zookeeper.properties

启动zookeeper

复制代码代码如下:

./bin/zookeeper-server-start /usr/local/etc/kafka/zookeeper.properties &

启动kafka

./bin/kafka-server-start /usr/local/etc/kafka/server.properties &

为kafka创建topic,topic 名为test，可以配置成自己想要的名字，回头再代码中配置正确就可以了。

复制代码代码如下:

	./bin/kafka-topics --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic test

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

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									<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

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

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									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

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									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

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									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。

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									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());

									 }

									}