Java实现Kafka读写笔记
Posted ZeroTeam_麒麟
tags:
篇首语:本文由小常识网(cha138.com)小编为大家整理,主要介绍了Java实现Kafka读写笔记相关的知识,希望对你有一定的参考价值。
1.POM.XML
<dependencies>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-clients</artifactId>
<version>0.8.2.1</version>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka_2.11</artifactId>
<version>0.8.2.1</version>
</dependency>
</dependencies>
2.生成者
import kafka.javaapi.producer.Producer;
import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig;
import java.util.Properties;
public class RunKafkaProduce
private final Producer<String, String> producer;
public final static String TOPIC = "logstest";
private RunKafkaProduce()
Properties props = new Properties();
// 此处配置的是kafka的broker地址:端口列表
props.put("metadata.broker.list", "172.19.4.230:9092");
//配置value的序列化类
props.put("serializer.class", "kafka.serializer.StringEncoder");
//配置key的序列化类
props.put("key.serializer.class", "kafka.serializer.StringEncoder");
//request.required.acks
//0, which means that the producer never waits for an acknowledgement from the broker (the same behavior as 0.7). This option provides the lowest latency but the weakest durability guarantees (some data will be lost when a server fails).
//1, which means that the producer gets an acknowledgement after the leader replica has received the data. This option provides better durability as the client waits until the server acknowledges the request as successful (only messages that were written to the now-dead leader but not yet replicated will be lost).
//-1, which means that the producer gets an acknowledgement after all in-sync replicas have received the data. This option provides the best durability, we guarantee that no messages will be lost as long as at least one in sync replica remains.
props.put("request.required.acks","-1");
producer = new Producer<String, String>(new ProducerConfig(props));
void produce()
int messageNo = 1;
final int COUNT = 101;
int messageCount = 0;
while (messageNo < COUNT)
String key = String.valueOf(messageNo);
String data = "Hello kafka message :" + key;
producer.send(new KeyedMessage<String, String>(TOPIC, key ,data));
System.out.println(data);
messageNo ++;
messageCount++;
System.out.println("Producer端一共产生了" + messageCount + "条消息!");
public static void main( String[] args )
new RunKafkaProduce().produce();
3.消费着
import kafka.consumer.ConsumerConfig;
import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;
import kafka.serializer.StringDecoder;
import kafka.utils.VerifiableProperties;
import org.apache.kafka.clients.producer.KafkaProducer;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;
/**
*
* // _ooOoo_ //
* // o8888888o //
* // 88" . "88 //
* // (| ^_^ |) //
* // O\\ = /O //
* // ____/`---'\\____ //
* // .' \\\\| |// `. //
* // / \\\\||| : |||// \\ //
* // / _||||| -:- |||||- \\ //
* // | | \\\\\\ - /// | | //
* // | \\_| ''\\---/'' | | //
* // \\ .-\\__ `-` ___/-. / //
* // ___`. .' /--.--\\ `. . ___ //
* // ."" '< `.___\\_<|>_/___.' >'"". //
* // | | : `- \\`.;`\\ _ /`;.`/ - ` : | | //
* // \\ \\ `-. \\_ __\\ /__ _/ .-` / / //
* // ========`-.____`-.___\\_____/___.-`____.-'======== //
* // `=---=' //
* // ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ //
* // 佛祖保佑 再无Bug //
*
* User:Klin
* Date:2017/4/18 0018
*/
public class RunKafkaConsumer
private final ConsumerConnector consumer;
private final static String TOPIC="logstest";
private RunKafkaConsumer()
Properties props=new Properties();
//zookeeper
props.put("zookeeper.connect","zero230:2181");
//topic
props.put("group.id","logstest");
//Zookeeper 超时
props.put("zookeeper.session.timeout.ms", "4000");
props.put("zookeeper.sync.time.ms", "200");
props.put("auto.commit.interval.ms", "1000");
props.put("auto.offset.reset", "smallest");
props.put("serializer.class", "kafka.serializer.StringEncoder");
ConsumerConfig config=new ConsumerConfig(props);
consumer= kafka.consumer.Consumer.createJavaConsumerConnector(config);
void consume()
Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
topicCountMap.put(TOPIC, new Integer(1));
StringDecoder keyDecoder = new StringDecoder(new VerifiableProperties());
StringDecoder valueDecoder = new StringDecoder(new VerifiableProperties());
Map<String, List<KafkaStream<String, String>>> consumerMap =
consumer.createMessageStreams(topicCountMap,keyDecoder,valueDecoder);
KafkaStream<String, String> stream = consumerMap.get(TOPIC).get(0);
ConsumerIterator<String, String> it = stream.iterator();
int messageCount = 0;
while (it.hasNext())
System.out.println(it.next().message());
messageCount++;
if(messageCount == 100)
System.out.println("Consumer端一共消费了" + messageCount + "条消息!");
public static void main(String[] args)
new RunKafkaConsumer().consume();
以上是关于Java实现Kafka读写笔记的主要内容,如果未能解决你的问题,请参考以下文章