Spark Streaming實時流處理筆記(5)—— Kafka API 程式設計
阿新 • • 發佈:2018-12-06
1 新建 Maven工程
pom檔案
<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/maven-v4_0_0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.myspark.com</groupId >
<artifactId>sparktrain</artifactId>
<version>1.0</version>
<inceptionYear>2008</inceptionYear>
<properties>
<scala.version>2.11.12</scala.version>
<kafka.version>0.9.0.0</kafka.version>
</properties>
<repositories >
<repository>
<id>scala-tools.org</id>
<name>Scala-Tools Maven2 Repository</name>
<url>http://scala-tools.org/repo-releases</url>
</repository>
</repositories>
<pluginRepositories>
<pluginRepository>
< id>scala-tools.org</id>
<name>Scala-Tools Maven2 Repository</name>
<url>http://scala-tools.org/repo-releases</url>
</pluginRepository>
</pluginRepositories>
<dependencies>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${scala.version}</version>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka_2.11</artifactId>
<version>${kafka.version}</version>
</dependency>
</dependencies>
<build>
<sourceDirectory>src/main/scala</sourceDirectory>
<testSourceDirectory>src/test/scala</testSourceDirectory>
<plugins>
<plugin>
<groupId>org.scala-tools</groupId>
<artifactId>maven-scala-plugin</artifactId>
<executions>
<execution>
<goals>
<goal>compile</goal>
<goal>testCompile</goal>
</goals>
</execution>
</executions>
<configuration>
<scalaVersion>${scala.version}</scalaVersion>
<args>
<arg>-target:jvm-1.5</arg>
</args>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-eclipse-plugin</artifactId>
<configuration>
<downloadSources>true</downloadSources>
<buildcommands>
<buildcommand>ch.epfl.lamp.sdt.core.scalabuilder</buildcommand>
</buildcommands>
<additionalProjectnatures>
<projectnature>ch.epfl.lamp.sdt.core.scalanature</projectnature>
</additionalProjectnatures>
<classpathContainers>
<classpathContainer>org.eclipse.jdt.launching.JRE_CONTAINER</classpathContainer>
<classpathContainer>ch.epfl.lamp.sdt.launching.SCALA_CONTAINER</classpathContainer>
</classpathContainers>
</configuration>
</plugin>
</plugins>
</build>
<reporting>
<plugins>
<plugin>
<groupId>org.scala-tools</groupId>
<artifactId>maven-scala-plugin</artifactId>
<configuration>
<scalaVersion>${scala.version}</scalaVersion>
</configuration>
</plugin>
</plugins>
</reporting>
</project>
2 生產者原始碼
KafkaProperties.java
package com.myspark.kafka;
/*
*
* Kafka 配置檔案
* */
public class KafkaProperties {
public static final String ZK = "192.168.30.131:2181";
public static final String TOPIC = "hello_topic";
public static final String BROKER_LIST = "192.168.30.131:9092";
}
KafkaProducer.java
package com.myspark.kafka;
import kafka.javaapi.producer.Producer;
import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig;
import java.util.Properties;
public class KafkaProducer extends Thread {
private String topic;
private Producer<Integer, String> producer;
public KafkaProducer(String topic) {
this.topic = topic;
Properties properties = new Properties();
properties.put("metadata.broker.list", KafkaProperties.BROKER_LIST);
properties.put("serializer.class", "kafka.serializer.StringEncoder");
/*
* The number of acknowledgments the producer requires the leader to have received before considering a request complete.
* This controls the durability of the messages sent by the producer.
*
* request.required.acks = 0 - means the producer will not wait for any acknowledgement from the leader.
* request.required.acks = 1 - means the leader will write the message to its local log and immediately acknowledge
* request.required.acks = -1 - means the leader will wait for acknowledgement from all in-sync replicas before acknowledging the write
*/
properties.put("request.required.acks", "1");
producer = new Producer<Integer, String>(new ProducerConfig(properties));
}
@Override
public void run() {
int messageNo = 1;
while (true) {
String message = "message_" + messageNo;
producer.send(new KeyedMessage<Integer, String>(topic, message));
System.out.println("Sent: " + message);
messageNo++;
try{
Thread.sleep(2000);
}catch (Exception e){
e.printStackTrace();
}
}
}
}
KafkaClientApp.java
package com.myspark.kafka;
/*
* Kafka Java API測試
* */
public class KafkaClientApp {
public static void main(String[] args) {
new KafkaProducer(KafkaProperties.TOPIC).start();
}
}
測試
先啟動 zookeeper,然後啟動 kafka
kafka-server-start.sh $KAFKA_HOME/config/server.properties
[[email protected] ~]$ jps -m
2624 Kafka /home/hadoop/apps/kafka_2.11-0.9.0.0/config/server.properties
2714 Jps -m
1405 QuorumPeerMain /home/hadoop/apps/zookeeper-3.4.5-cdh5.7.0/bin/../conf/zoo.cfg
[[email protected] ~]$
啟動消費者
kafka-console-consumer.sh --zookeeper node1:2181 --topic hello_topic
然後啟動 KafkaClientApp
3 消費者
KafkaProperties.java
package com.myspark.kafka;
/*
*
* Kafka 配置檔案
* */
public class KafkaProperties {
public static final String ZK = "192.168.30.131:2181";
public static final String TOPIC = "hello_topic";
public static final String BROKER_LIST = "192.168.30.131:9092";
public static final String GROUP_ID = "test_group1";
}
KafkaConsumer.java
package com.myspark.kafka;
import kafka.consumer.Consumer;
import kafka.consumer.ConsumerConfig;
import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;
public class KafkaConsumer extends Thread {
private String topic;
public KafkaConsumer(String topic) {
this.topic = topic;
}
private ConsumerConnector createConnector() {
Properties properties = new Properties();
properties.put("zookeeper.connect", KafkaProperties.ZK);
properties.put("group.id",KafkaProperties.GROUP_ID);
return Consumer.createJavaConsumerConnector(new ConsumerConfig(properties));
}
@Override
public void run() {
ConsumerConnector consumer = createConnector();
Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
topicCountMap.put(topic, 1);
//String : topic
//第二個引數:資料流
Map<String, List<KafkaStream<byte[], byte[]>>> messageStream = consumer.createMessageStreams(topicCountMap);
KafkaStream<byte[], byte[]> stream = messageStream.get(topic).get(0); //獲取每次接收到的資料
ConsumerIterator<byte[], byte[]> iterator = stream.iterator();
while(iterator.hasNext()){
String message = new String(iterator.next().message());
System.out.println("receive: "+message);
}
}
}
KafkaClientApp.java
package com.myspark.kafka;
/*
* Kafka Java API測試
* */
public class KafkaClientApp {
public static void main(String[] args) {
new KafkaProducer(KafkaProperties.TOPIC).start();
new KafkaConsumer(KafkaProperties.TOPIC).start();
}
}