前言
在上一章 Kafka实战 中我们在局域网中搭建了一个Kafka节点，并尝试了通过命令行脚本来实现本地消息的发布与接收，了解了主从节点之间的关系等。这一章主要实现在本机通过Java代码实现对局域网中的Kafka节点进行消息的发布与接收。
准备工作
在Java中进行Kafka编程需要依赖kafka和kafka-clients两个包，下面直接提供maven配置文件pom.xml，不要忘记修改工程名:
<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>Test</groupId> <artifactId>Test</artifactId> <version>0.0.1-SNAPSHOT</version> <build> <sourceDirectory>src</sourceDirectory> <plugins> <plugin> <artifactId>maven-compiler-plugin</artifactId> <version>3.3</version> <configuration> <source>1.7</source> <target>1.7</target> </configuration> </plugin> </plugins> </build> <dependencies> <dependency> <groupId>org.apache.kafka</groupId> <artifactId>kafka-clients</artifactId> <version>0.9.0.0</version> </dependency> <dependency> <groupId>org.apache.kafka</groupId> <artifactId>kafka_2.10</artifactId> <version>0.9.0.0</version> </dependency> </dependencies> </project>
生产者
生产者有两种发布方式，同步和异步。异步方式增加了一个Callback参数来实现在消息成功发送后，开展后续的工作。
import java.util.Properties;
import java.util.concurrent.ExecutionException;
import org.apache.kafka.clients.producer.Callback;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.clients.producer.RecordMetadata;
public class Producer extends Thread
{
private final KafkaProducer<Integer, String> producer;
private final String topic;
// 是否需要异步发送
private final Boolean isAsync;
// 装有Kafka的机器的IP地址
private final String serverIp = "10.64.***.***";
public Producer(String topic, Boolean isAsync)
{
Properties props = new Properties();
props.put("bootstrap.servers", serverIp+":9092");
props.put("client.id", "DemoProducer");
props.put("key.serializer", "org.apache.kafka.common.serialization.IntegerSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
producer = new KafkaProducer<Integer, String>(props);
this.topic = topic;
this.isAsync = isAsync;
}
public void run() {
int messageNo = 1;
while(true)
{
String messageStr = "Message_" + messageNo;
long startTime = System.currentTimeMillis();
if (isAsync) {
producer.send(new ProducerRecord<Integer, String>(topic,
messageNo,
messageStr), new DemoCallBack(startTime, messageNo, messageStr));
} else {
try {
producer.send(new ProducerRecord<Integer, String>(topic,
messageNo,
messageStr)).get();
System.out.println("Sent message: (" + messageNo + ", " + messageStr + ")");
} catch (InterruptedException e) {
e.printStackTrace();
} catch (ExecutionException e) {
e.printStackTrace();
}
}
++messageNo;
}
}
}
class DemoCallBack implements Callback {
private long startTime;
private int key;
private String message;
public DemoCallBack(long startTime, int key, String message) {
this.startTime = startTime;
this.key = key;
this.message = message;
}
/**
* 当异步发送完成后需要进行的处理
**/
public void onCompletion(RecordMetadata metadata, Exception exception) {
long elapsedTime = System.currentTimeMillis() - startTime;
if (metadata != null) {
System.out.println(
"message(" + key + ", " + message + ") sent to partition(" + metadata.partition() +
"), " +
"offset(" + metadata.offset() + ") in " + elapsedTime + " ms");
} else {
exception.printStackTrace();
}
}
}调用方式：
// 开启生产者线程后，会向Kafka节点中对应的topic发送Message_**类型的消息 boolean isAsync = true; Producer producerThread = new Producer(KafkaProperties.topic, isAsync); producerThread.start();
消费者
消费者用来接收特定话题的消息。
import java.util.Collections;
import java.util.Properties;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import kafka.utils.ShutdownableThread;
public class Consumer extends ShutdownableThread
{
private final KafkaConsumer<Integer, String> consumer;
private final String topic;
private final String serverIp = "10.64.***.***";
public Consumer(String topic)
{
super("KafkaConsumerExample", false);
Properties props = new Properties();
props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, serverIp+":9092");
props.put(ConsumerConfig.GROUP_ID_CONFIG, "DemoConsumer");
props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "true");
props.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, "1000");
props.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, "30000");
props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.IntegerDeserializer");
props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringDeserializer");
consumer = new KafkaConsumer<>(props);
this.topic = topic;
}
@Override
public void doWork() {
consumer.subscribe(Collections.singletonList(this.topic));
ConsumerRecords<Integer, String> records = consumer.poll(1000);
for (ConsumerRecord<Integer, String> record : records) {
System.out.println("Received message: (" + record.key() + ", " + record.value() + ") at offset " + record.offset());
}
}
@Override
public String name() {
return null;
}
@Override
public boolean isInterruptible() {
return false;
}
}调用方式：
//开启消费者线程后，会接收到之前生产者发送的消息 Consumer consumerThread = new Consumer(KafkaProperties.topic); consumerThread.start();
总结
通过上面的简单的例子，我们就可以在自己的工程中向Kafka发送消息，并接收到自己订阅的消息了。
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