用spring初始化器创建一个项目把kafka选上去。
我这里用的版本是2.1.15。
首先看一下目录结构,我这里是一个父工程下的子模块。
配置文件如下:
父工程:
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.haogenmin.springcloud</groupId>
<artifactId>parent</artifactId>
<version>1.0-SNAPSHOT</version>
<modules>
<module>websocket</module>
<module>webtest</module>
<module>fileUploadAndDown</module>
<module>excelOperate</module>
<module>model</module>
<module>redis</module>
<module>kafka</module>
</modules>
<packaging>pom</packaging>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>2.1.15.RELEASE</version>
<relativePath/>
</parent>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
<maven.compiler.source>1.8</maven.compiler.source>
<maven.compiler.target>1.8</maven.compiler.target>
<!-- spring cloud 采用 Finchley.SR2 版本 -->
<spring-cloud.version>Greenwich.SR6</spring-cloud.version>
</properties>
<!--依赖声明-->
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-dependencies</artifactId>
<version>${spring-cloud.version}</version>
<type>pom</type>
<!--maven不支持多继承,使用import来依赖管理配置-->
<scope>import</scope>
</dependency>
<!--导入 mybatis 启动器-->
<dependency>
<groupId>org.mybatis.spring.boot</groupId>
<artifactId>mybatis-spring-boot-starter</artifactId>
<version>2.1.3</version>
</dependency>
<!--druid数据源-->
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>druid</artifactId>
<version>1.1.22</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>8.0.13</version>
</dependency>
</dependencies>
</dependencyManagement>
<dependencies>
<!--json-->
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>1.2.58</version>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
</project>
kafka模块:
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<parent>
<artifactId>parent</artifactId>
<groupId>com.haogenmin.springcloud</groupId>
<version>1.0-SNAPSHOT</version>
</parent>
<modelVersion>4.0.0</modelVersion>
<artifactId>kafka</artifactId>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-streams</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.kafka</groupId>
<artifactId>spring-kafka</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.kafka</groupId>
<artifactId>spring-kafka-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>
启动类:(什么都没有)
package com.haogenmin.kafka;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
/**
* @author :HaoGenmin
* @Title :KafkaApplication
* @date :Created in 2020/9/29 19:29
* @description:
*/
@SpringBootApplication
public class KafkaApplication {
public static void main(String[] args) {
SpringApplication.run(KafkaApplication.class,args);
}
}
生产者:
package com.haogenmin.kafka.demo;
import com.alibaba.fastjson.JSONObject;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.support.SendResult;
import org.springframework.stereotype.Component;
import org.springframework.util.concurrent.ListenableFuture;
import org.springframework.util.concurrent.ListenableFutureCallback;
import javax.annotation.Resource;
/**
* @author :HaoGenmin
* @Title :KafkaProducer
* @date :Created in 2020/9/29 19:45
* @description:
*/
@Component
public class KafkaProducer {
Logger logger = LoggerFactory.getLogger(KafkaProducer.class);
@Resource
private KafkaTemplate<String, Object> kafkaTemplate;
//自定义topic
public static final String TOPIC_TEST = "topic.test";
//
public static final String TOPIC_GROUP1 = "topic.group1";
//
public static final String TOPIC_GROUP2 = "topic.group2";
public void send(Object obj) {
String obj2String = JSONObject.toJSONString(obj);
logger.info("准备发送消息为:{}", obj2String);
//发送消息
ListenableFuture<SendResult<String, Object>> future = kafkaTemplate.send(TOPIC_TEST, obj);
future.addCallback(new ListenableFutureCallback<SendResult<String, Object>>() {
@Override
public void onFailure(Throwable throwable) {
//发送失败的处理
logger.info(TOPIC_TEST + " - 生产者 发送消息失败:" + throwable.getMessage());
}
@Override
public void onSuccess(SendResult<String, Object> stringObjectSendResult) {
//成功的处理
logger.info(TOPIC_TEST + " - 生产者 发送消息成功:" + stringObjectSendResult.toString());
}
});
}
}
消费者:
package com.haogenmin.kafka.demo;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.kafka.support.Acknowledgment;
import org.springframework.kafka.support.KafkaHeaders;
import org.springframework.messaging.handler.annotation.Header;
import org.springframework.stereotype.Component;
import java.util.Optional;
/**
* @author :HaoGenmin
* @Title :KafkaConsumer
* @date :Created in 2020/9/29 19:40
* @description:
*/
@Component
public class KafkaConsumer {
Logger logger = LoggerFactory.getLogger(KafkaConsumer.class);
@KafkaListener(topics = KafkaProducer.TOPIC_TEST, groupId = KafkaProducer.TOPIC_GROUP1)
public void topic_test(ConsumerRecord<?, ?> record, Acknowledgment ack, @Header(KafkaHeaders.RECEIVED_TOPIC) String topic) {
Optional message = Optional.ofNullable(record.value());
if (message.isPresent()) {
Object msg = message.get();
logger.info("topic_test 消费了: Topic:" + topic + ",Message:" + msg);
ack.acknowledge();
}
}
@KafkaListener(topics = KafkaProducer.TOPIC_TEST, groupId = KafkaProducer.TOPIC_GROUP2)
public void topic_test1(ConsumerRecord<?, ?> record, Acknowledgment ack, @Header(KafkaHeaders.RECEIVED_TOPIC) String topic) {
Optional message = Optional.ofNullable(record.value());
if (message.isPresent()) {
Object msg = message.get();
logger.info("topic_test1 消费了: Topic:" + topic + ",Message:" + msg);
ack.acknowledge();
}
}
}
配置文件:
server:
port: 8001
spring:
kafka:
bootstrap-servers: 192.168.10.12:9092,192.168.10.13:9092,192.168.10.14:9092
producer:
# 发生错误后,消息重发的次数。
retries: 0
#当有多个消息需要被发送到同一个分区时,生产者会把它们放在同一个批次里。该参数指定了一个批次可以使用的内存大小,按照字节数计算。
batch-size: 16384
# 设置生产者内存缓冲区的大小。
buffer-memory: 33554432
# 键的序列化方式
key-serializer: org.apache.kafka.common.serialization.StringSerializer
# 值的序列化方式
value-serializer: org.apache.kafka.common.serialization.StringSerializer
# acks=0 : 生产者在成功写入消息之前不会等待任何来自服务器的响应。
# acks=1 : 只要集群的首领节点收到消息,生产者就会收到一个来自服务器成功响应。
# acks=all :只有当所有参与复制的节点全部收到消息时,生产者才会收到一个来自服务器的成功响应。
acks: 1
consumer:
# 自动提交的时间间隔 在spring boot 2.X 版本中这里采用的是值的类型为Duration 需要符合特定的格式,如1S,1M,2H,5D
auto-commit-interval: 1S
# 该属性指定了消费者在读取一个没有偏移量的分区或者偏移量无效的情况下该作何处理:
# latest(默认值)在偏移量无效的情况下,消费者将从最新的记录开始读取数据(在消费者启动之后生成的记录)
# earliest :在偏移量无效的情况下,消费者将从起始位置读取分区的记录
auto-offset-reset: earliest
# 是否自动提交偏移量,默认值是true,为了避免出现重复数据和数据丢失,可以把它设置为false,然后手动提交偏移量
enable-auto-commit: false
# 键的反序列化方式
key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
# 值的反序列化方式
value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
listener:
# 在侦听器容器中运行的线程数。
concurrency: 2
#listner负责ack,每调用一次,就立即commit
ack-mode: manual_immediate
missing-topics-fatal: false
启动:
因为我们创建了两个消费者组,所以这里会出现两个消费者组的配置。
配置文件里面可以看到,消费者开两个线程,我们这个topic有三个分区,从之前的博客我们知道,线程数大于分区数的话,会有一些线程分不到分区一直处于闲置状态。上图中此时两个线程
可以看到组1中消费者实例是5和6,5分配的是0和1分区,6分配的是2分区,这两个实例只消费分配给自己的分区的消息。组2同理。
我们以上用的是配置文件形式,用配置类的形式可能更能会有更清晰的结构。
@Configuration
@EnableKafka
public class KafkaConfiguration {
//ConcurrentKafkaListenerContainerFactory为创建Kafka监听器的工程类,这里只配置了消费者
@Bean
public ConcurrentKafkaListenerContainerFactory<Integer, String> kafkaListenerContainerFactory() {
ConcurrentKafkaListenerContainerFactory<Integer, String> factory = new ConcurrentKafkaListenerContainerFactory<>();
factory.setConsumerFactory(consumerFactory());
return factory;
}
//根据consumerProps填写的参数创建消费者工厂
@Bean
public ConsumerFactory<Integer, String> consumerFactory() {
return new DefaultKafkaConsumerFactory<>(consumerProps());
}
//根据senderProps填写的参数创建生产者工厂
@Bean
public ProducerFactory<Integer, String> producerFactory() {
return new DefaultKafkaProducerFactory<>(senderProps());
}
//kafkaTemplate实现了Kafka发送接收等功能
@Bean
public KafkaTemplate<Integer, String> kafkaTemplate() {
KafkaTemplate template = new KafkaTemplate<Integer, String>(producerFactory());
return template;
}
//消费者配置参数
private Map<String, Object> consumerProps() {
Map<String, Object> props = new HashMap<>();
//连接地址
props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
//GroupID
props.put(ConsumerConfig.GROUP_ID_CONFIG, "bootKafka");
//是否自动提交
props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, true);
//自动提交的频率
props.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, "100");
//Session超时设置
props.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, "15000");
//键的反序列化方式
props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, IntegerDeserializer.class);
//值的反序列化方式
props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
return props;
}
//生产者配置
private Map<String, Object> senderProps (){
Map<String, Object> props = new HashMap<>();
//连接地址
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
//重试,0为不启用重试机制
props.put(ProducerConfig.RETRIES_CONFIG, 1);
//控制批处理大小,单位为字节
props.put(ProducerConfig.BATCH_SIZE_CONFIG, 16384);
//批量发送,延迟为1毫秒,启用该功能能有效减少生产者发送消息次数,从而提高并发量
props.put(ProducerConfig.LINGER_MS_CONFIG, 1);
//生产者可以使用的总内存字节来缓冲等待发送到服务器的记录
props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, 1024000);
//键的序列化方式
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class);
//值的序列化方式
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
return props;
}
}
监听器(也就是我们在消费者类中写的那两个函数)
@Component
public class DemoListener {
private static final Logger log= LoggerFactory.getLogger(DemoListener.class);
//声明consumerID为demo,监听topicName为topic.quick.demo的Topic
@KafkaListener(id = "demo", topics = "topic.quick.demo")
public void listen(String msgData) {
log.info("demo receive : "+msgData);
}
}