spring整合kafak（一）

一.环境要求

1.操作系统：win10

2.项目情况：spring+struts1+mybatis (老项目，非maven项目)

3.kafka_2.12-2.7.0 【新版本的kafka已经内置了zookeeper，因此不需要单独下载zookeeper】

下载kafka_2.12-2.7.0已经在云盘分享，也可以去官网自行下载（http://kafka.apache.org/downloads）

链接：https://pan.baidu.com/s/1atZaQ8kkAZrnsJJnlc5IWQ
提取码：c57f
复制这段内容后打开百度网盘手机App，操作更方便哦

二.整合操作

1.导入依赖，因为是非maven项目，所以要导入jar包（kafka_2.12-2.7.0.jar，kafka-clients-1.0.1.jar，kafka-raft-2.7.0.jar）

jar包下载地址已在云盘分享

链接：https://pan.baidu.com/s/15WU3d9wpjURfy5JtSo8JwQ
提取码：orz2
复制这段内容后打开百度网盘手机App，操作更方便哦

如果是maven项目，可以直接在pom.xml中添加依赖

<dependency>
   <groupId>org.apache.kafka</groupId>
   <artifactId>kafka_2.12</artifactId>
   <version>2.7.0</version>
</dependency>

注意：导入的依赖或jar包版本与你下载的kafka版本保持一致

2.创建生产者

package org.kafka;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.kafka.clients.producer.Callback;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.clients.producer.RecordMetadata;
import java.util.Properties;

/**
 * kafka 创建生产者
 * fjt
 * 20210325
 */
public class KafkaProduce {
    private static Properties properties;
    private static Log log = LogFactory.getLog(KafkaProduce.class);
    public KafkaProduce(String url){
        properties = new Properties();
        properties.put("bootstrap.servers", url);
        properties.put("producer.type", "sync");
        properties.put("request.required.acks", "1");
        properties.put("serializer.class", "kafka.serializer.DefaultEncoder");
        properties.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        properties.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        properties.put("bak.partitioner.class", "kafka.producer.DefaultPartitioner");
        properties.put("bak.key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        properties.put("bak.value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
    }

    /**
     * @Title: sendMessage
     * @Description: 生产消息
     */
    public void sendMessage(String topic, String key, String value) {
        // 实例化produce
        KafkaProducer<String, String> kp = new KafkaProducer<String, String>(properties);

        // 消息封装
        ProducerRecord<String, String> pr = new ProducerRecord<String, String>(topic, key, value);

        // 发送数据
        kp.send(pr, new Callback() {
            // 回调函数
            @Override
            public void onCompletion(RecordMetadata metadata, Exception exception) {
                if (null != exception) {
                    log.error("记录的offset在:" + metadata.offset() + exception.getMessage());
                }
            }
        });

        // 关闭produce
        kp.close();
    }
}

3.创建消费者

package org.kafka;

import com.gexin.fastjson.JSONObject;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;

import java.util.Collections;
import java.util.Properties;

/**
 * 创建消费者
 * fjt
 * 20210325
 */
public class KafkaConsume {
    private static Properties properties;
    private long SIZE = 100;
    KafkaConsumer<String, String> consumer;
    private static Log log = LogFactory.getLog(KafkaConsume.class);

    public KafkaConsume(String url){
        properties = new Properties();
        properties.put("bootstrap.servers", url);
        properties.put("zookeeper.connect", url);
        properties.put("group.id", "kafkaDemo");
        properties.put("zookeeper.session.timeout.ms", "4000");
        properties.put("zookeeper.sync.time.ms", "200");
        properties.put("auto.commit.interval.ms", "1000");
        properties.put("auto.offset.reset", "earliest");
        properties.put("serializer.class", "kafka.serializer.StringEncoder");
        properties.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        properties.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
    }

    /**
     * @Title: getMessage
     * @Description: 消费一个消息
     */
    public void getMessage(String topic) {
        consumer = new KafkaConsumer<String, String>(properties);
        // 订阅主题
        consumer.subscribe(Collections.singletonList(topic));
        while (true) {
            ConsumerRecords<String, String> records = consumer.poll(SIZE);
            for (ConsumerRecord<String, String> record : records) {
                try {
                    System.out.println("消费者接收数据如下：");
                    System.out.printf("offset = %d, key = %s, value = %s", record.offset(), record.key(), record.value());
                    //消息数据为JSON格式的字符串，解析数据
                    JSONObject msgInfo = JSONObject.parseObject(record.value());
                    System.out.println(msgInfo.getString("deveui"));
                    System.out.println(msgInfo.getString("type"));
                    System.out.println(msgInfo.getString("happendtime"));
                    System.out.println(msgInfo.getString("msg"));
                }catch ( Exception e){
                    log.error(e.getMessage());
                }
            }
        }
    }

    public void closeConsumer() {
        consumer.close();
    }


}

4.调用生产者/消费者示例

package org.kafka;

/**
 * 生产者/消费者调用示例
 * fjt
 * 2021.03.25
 */
public class KafkaDemo {
    public static void main( String[] args )
    {
        String url = "127.0.0.1:9092";
        String topic = "topic";

        //生产者
        KafkaProduce kp = new KafkaProduce(url);
        //生产一条消息
        kp.sendMessage(topic, "key", "{\"deveui\":\"13579\",\"type\":\"fault\",\"happendtime\":\"2013-03-25 13:24:19\",\"msg\":\"XXX位置XX设备发生故障，请及时处理\"}");

        //消费者
        KafkaConsume kc = new KafkaConsume(url);
        //消费指定topic的数据
        kc.getMessage(topic);
    }
}

三.整合测试

1.下载后的kafka_2.12-2.7.0.tgz解压到指定目录（建议不要放在中文目录下）

2.kafka根目录下新建data和kafka-logs文件夹，后面要用到，作为kafka快照和日志的存储文件夹

3.修改配置文件

进入到config目录，

修改server.properties里面log.dirs路径未log.dirs=D:\\MyStudy\\Kafka\\kafka_2.12-2.7.0\\kafka-logs

修改zookeeper.properties里面dataDir路径为dataDir=D:\\MyStudy\\Kafka\\kafka_2.12-2.7.0\\data

注意：文件夹分割符一定要是”\\”

4.启动kafka内置的zookeeper