java实现kafka消息发送和接收

之前写了一篇关于kafka集群搭建的点击打开链接。想了解的可以看下。

今天这个实现是和前面集群对应的。使用的是新版的API。属性如果想定制自己的,需要到官方网址上面去查看一下对应的值。

推介大家多去看看官方的介绍和demo。网上有些翻译过来的例子并不完善,最好是知己知彼,才能百战不殆

maven:

	<dependency>
    		<groupId>org.apache.kafka</groupId>
    		<artifactId>kafka-clients</artifactId>
    		<version>0.11.0.0</version>
    	</dependency>
   	    <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka-streams</artifactId>
            <version>0.11.0.0</version>
    	</dependency>

生产者Producer:

package com.roncoo.example.kafka;

import java.util.Properties;

import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;

public class ProducerDemo {

    private final KafkaProducer<String, String> producer;

    public final static String TOPIC = "test5";

    private ProducerDemo() {
        Properties props = new Properties();
        props.put("bootstrap.servers", "xxx:9092,1xxx:9092,xxx:9092");//xxx服务器ip
        props.put("acks", "all");//所有follower都响应了才认为消息提交成功,即"committed"
        props.put("retries", 0);//retries = MAX 无限重试,直到你意识到出现了问题:)
        props.put("batch.size", 16384);//producer将试图批处理消息记录,以减少请求次数.默认的批量处理消息字节数
        //batch.size当批量的数据大小达到设定值后,就会立即发送,不顾下面的linger.ms
        props.put("linger.ms", 1);//延迟1ms发送,这项设置将通过增加小的延迟来完成--即,不是立即发送一条记录,producer将会等待给定的延迟时间以允许其他消息记录发送,这些消息记录可以批量处理
        props.put("buffer.memory", 33554432);//producer可以用来缓存数据的内存大小。
        props.put("key.serializer",
                "org.apache.kafka.common.serialization.IntegerSerializer");
        props.put("value.serializer",
              "org.apache.kafka.common.serialization.StringSerializer");

        producer = new KafkaProducer<String, String>(props);
    }

    public void produce() {
        int messageNo = 1;
        final int COUNT = 5;

        while(messageNo < COUNT) {
            String key = String.valueOf(messageNo);
            String data = String.format("hello KafkaProducer message %s from hubo 06291018 ", key);
            
            try {
                producer.send(new ProducerRecord<String, String>(TOPIC, data));
            } catch (Exception e) {
                e.printStackTrace();
            }

            messageNo++;
        }
        
        producer.close();
    }

    public static void main(String[] args) {
        new ProducerDemo().produce();
    }
}

消费者Consumer:

package com.roncoo.example.kafka;
import java.util.Arrays;
import java.util.Properties;

import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;


public class UserKafkaConsumer extends Thread {

        public static void main(String[] args){
            Properties properties = new Properties();
            properties.put("bootstrap.servers", "xxx:9092,xxx:9092,xxx:9092");//xxx是服务器集群的ip
            properties.put("group.id", "jd-group");
            properties.put("enable.auto.commit", "true");
            properties.put("auto.commit.interval.ms", "1000");
            properties.put("auto.offset.reset", "latest");
            properties.put("session.timeout.ms", "30000");
            properties.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
            properties.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");

            KafkaConsumer<String, String> kafkaConsumer = new KafkaConsumer<>(properties);
            kafkaConsumer.subscribe(Arrays.asList("test5"));
            while (true) {
                ConsumerRecords<String, String> records = kafkaConsumer.poll(100);
                for (ConsumerRecord<String, String> record : records) {
                    System.out.println("-----------------");
                    System.out.printf("offset = %d, value = %s", record.offset(), record.value());
                    System.out.println();
                }
            }

        }
}



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转载自blog.csdn.net/wobuaizhi/article/details/80950337