Kafka

消息发送流程

Kafka的Pruducer采取异步发送,两个线程:main线程和sender线程,一个线程共享变量-RecordAccumulator

main给RecordAccumulator,Sender线程从RecordAccumulator中拉取消息发送到Kafka broker。

发送流程

main线程(Producer->Itercepters->Serializer->Partitioner)->RecordAccumulator->Sender

Itercepters拦截器:传入String

Serializer序列化器:传入String,返回Byte

Partitioner分区器:传入Byte

html 复制代码
        <!--导入依赖-->
        <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka-clients</artifactId>
            <version>2.2.0</version>
        </dependency>
java 复制代码
package com.atguigu.producer;

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

import java.util.Properties;

public class MyProducer {
    public static void main(String[] args) {
        //1.创建Kafka生产者
        Properties properties = new Properties();
        //配置信息,可用ProducerConfig.进行提示
        //2.指定连接的Kafka集群
        properties.put("bootstrap.servers","hadoop102:9092");
        //接收机制
        properties.put("acks","all");
        //4.重试次数
        properties.put("retries","3");
        //等等,可以设置更多的参数

        //创建生产者对象
        KafkaProducer<String, String> producer = new KafkaProducer<>(properties);
        //发送数据
        producer.send(new ProducerRecord<String, String>("first","atiguigu"));
        //关闭连接
        producer.close();
    }
}
java 复制代码
package com.atguigu.producer;

import org.apache.kafka.clients.producer.*;
import org.apache.kafka.common.serialization.StringSerializer;

import java.util.Properties;
import java.util.concurrent.Future;

public class CallBackProducer {
    public static void main(String[] args) {
        //创建配置信息
        Properties properties = new Properties();
        properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG,"hadoop102:9092");
        properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,"org.apache.kafka.common.serialization.StringSerializer");
        properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,"org.apache.kafka.common.serialization.StringSerializer");
        //创建生产者对象
        KafkaProducer<String, String> producer = new KafkaProducer<>(properties);
        //发送数据
        for (int i = 0; i < 10; i++) {
            producer.send(new ProducerRecord<>("first",
                    "stiguigu--" + i),
                    (recordMetadata, e) -> {
                        if (e == null) {
                            System.out.println(recordMetadata.partition() + "--" + recordMetadata.offset());
                        }else{
                            e.printStackTrace();
                        }
                    }
            );
        }
        //关闭资源
        producer.close();
    }
}
java 复制代码
package com.atguigu.consumer;

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 java.util.Arrays;
import java.util.Properties;

public class MyConsumer {
    public static void main(String[] args) {

        Properties properties = new Properties();
        //连接集群
        properties.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG."hadoop102:9092");
        //自动提交
        properties.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG,true);
        //自动提交延时
        properties.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG,"1000");
        //key,value反序列化
        properties.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG,"org.apache.kafka.common.serialization.StringDeserializer");
        properties.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG,"org.apache.kafka.common.serialization.StringDeserializer");
        //消费组
        properties.put(ConsumerConfig.GROUP_ID_CONFIG,"bigdata");
        //创建消费者
        KafkaConsumer consumer = new KafkaConsumer<>(properties);
        //订阅主题
        consumer.subscribe(Arrays.asList("first","second"));
        //获取数据
        while (true) {
            ConsumerRecords<String, String> consumerRecords = consumer.poll(100);
            for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
                System.out.println(consumerRecord.key() + "--" + consumerRecord.value());
            }
        }
        //关闭连接
//        consumer.close();
    }
}
相关推荐
q***72876 小时前
Spring Boot集成Kafka:最佳实践与详细指南
spring boot·kafka·linq
小坏讲微服务6 小时前
Spring Cloud Alibaba整合 Kafka 的完整实现
分布式·spring cloud·kafka·消息队列·springboot·linq
zl9798996 小时前
RabbitMQ-延迟队列
分布式·rabbitmq
-大头.8 小时前
深入解析ZooKeeper核心机制
分布式·zookeeper·wpf
s***45311 小时前
【RabbitMQ】超详细Windows系统下RabbitMQ的安装配置
windows·分布式·rabbitmq
jinxinyuuuus11 小时前
Info Flow:分布式信息采集、数据去重与内容分级的工程实现
人工智能·分布式·程序人生·生活
WHFENGHE1 天前
输电线路分布式故障定位在线监测装置:技术解析与实际应用价值
分布式
johnny2331 天前
Kafka系列之脚本使用
kafka
BD_Marathon1 天前
【Kafka】
分布式·kafka
FinTech老王1 天前
集中式 vs 分布式数据库:金融用户如何选择?——金仓数据库的双架构实践与选型指南
数据库·分布式·金融