spring boot集成Kafka发送和订阅数据两种方式

spring boot集成Kafka发送和订阅数据两种方式 Kafka安装

MacBook Linux安装Kafka

Linux解压安装Kafka

kafka可视化工具Kafka Tool安装使用

Kafka集群和kafka-manager安装

方式一 maven的pom.xml引入依赖

<dependency>
            <groupId>org.springframework.kafkagroupId>
            <artifactId>spring-kafkaartifactId>
        dependency>

配置文件

spring:
    kafka:
        bootstrap-servers: 192.168.1.7:9092 
        producer:
            retries: 3
            acks: 1
            batch-size: 16384
            properties:
                linger:
                    ms: 0
            buffer-memory: 33554432
            key-serializer: org.apache.kafka.common.serialization.StringSerializer
            value-serializer: org.apache.kafka.common.serialization.StringSerializer
        consumer:
            properties:
                group:
                    id: defaultConsumerGroup
                session:
                    timeout:
                        ms: 120000
                request:
                    timeout:
                        ms: 180000
            enable-auto-commit: true
            auto:
                commit:
                    interval:
                        ms: 1000
            auto-offset-reset: latest
            key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
            value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
            max-poll-records: 50
        listener:
            missing-topics-fatal: false
            type: batch

代码里直接使用: KafkaTemplate, 因为spring启动时会自动把bean对象加载到容器里

发送数据到kafka

@Autowired
private KafkaTemplate kafkaTemplate;

//发送数据到kafka
private void sendKafka(String abcd, String efg) {
        Map<String, Object> body = new HashMap<>(8);
        body.put("time", System.currentTimeMillis());
        body.put("abcd", abcd);
        body.put("efg", efg);
        kafkaTemplate.send("test-topic", JSON.toJSONString(body));
    }

订阅数据

import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;

import java.util.List;

@Component
public class KafkaConsumer {

    @Autowired
    private ProcessDataComponent processDataComponent;
    
    /**
     * 单个topic订阅
     */
    @KafkaListener(topics = "test-topic1")
    public void onDeviceSubStatusMessageDevice(List<ConsumerRecord<String, ?>> listRecord) {
        process(listRecord);
    }
    
    /**
     * 订阅多个topic
     */
    @KafkaListener(topics = {
            "topic1",
            "topic2",
            "topic3"
    })
    public void onDeviceMessage(List<ConsumerRecord<String, ?>> listRecord) {
        process(listRecord);
    }


    private void process(List<ConsumerRecord<String, ?>> listRecord) {
        listRecord.forEach(record -> {
            processDataComponent.process(record.key(), record.value() + "");
        });
    }

}

方式二 maven的pom.xml引入依赖

<dependency>
			<groupId>org.apache.kafkagroupId>
			<artifactId>kafka-clientsartifactId>
			<version>1.0.2version>
		dependency>

发送数据到kafka

package com.test.kafka.demo;

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

import java.util.Properties;

public class KafkaProducerDemo {

    public static void main(String[] args) {
        Properties props = new Properties();
        props.put("bootstrap.servers", "192.168.1.7:9092");
        props.put("acks", "all");
        props.put("retries", 0);
        props.put("batch.size", 16384);
        props.put("linger.ms", 1);
        props.put("buffer.memory", 33554432);
        props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");

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

        for (int i = 0; i < 100; i++) {
            producer.send(new ProducerRecord<String, String>("my-topic", Integer.toString(i), Integer.toString(i)));
        }

        producer.close();
    }

}

订阅数据

package com.test.kafka.demo;

import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

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

public class KafkaComsumerDemo {
    private static Logger logger = LoggerFactory.getLogger(KafkaComsumerDemo.class);

    public static void main(String[] args) {
        try {
            Properties props = new Properties();
            props.put("bootstrap.servers", "192.168.1.7:9092");
            props.put("group.id", "group-foo1");
            props.put("auto.offset.reset", "earliest");
            //策略1 自动提交,周期性的提交偏移量
            props.put("enable.auto.commit", "true");
            props.put("auto.commit.interval.ms", "1000");
            //策略2 consumer.commitSync() //调用commitSync，手动同步ack。每处理完1条消息，commitSync 1次
            //策略3 consumer.commitASync() //手动异步ack


            props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
            props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
            KafkaConsumer<String, String> kafkaConsumer = new KafkaConsumer<String, String>(props);
            kafkaConsumer.subscribe(Arrays.asList("my-topic"));
            boolean flag = true;
            while (flag) {
                ConsumerRecords<String, String> records = kafkaConsumer.poll(100);
                for (ConsumerRecord<String, String> record : records) {
                    logger.info("offset = {},key = {},value = {}", record.offset(), record.key(), record.value());
                }

            }
            kafkaConsumer.close();
            logger.info("consumer client has been closed");

        } catch (Exception e) {
            logger.error("{}", e.getMessage());
        }

    }

}