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大数据之Kafka————java来实现kafka相关操作

大数据kafkajava 2023-09-23 08:09:28 431人浏览 泡泡鱼
摘要

一、在java中配置pom junit junit 4.11 test org.apache.kafka kafka-clients 2.8.

一、在java中配置pom

           junit      junit      4.11      test              org.apache.kafka      kafka-clients      2.8.0              org.apache.kafka      kafka_2.12      2.8.0      

二、生产者方法

(1)、Producer

Java中写在生产者输入内容在kafka中可以让消费者提取

[root@kb144 config]# kafka-console-consumer.sh --bootstrap-server 192.168.153.144:9092 --topic kb22

package nj.zb.kb22.Kafka;import org.apache.kafka.clients.producer.KafkaProducer;import org.apache.kafka.clients.producer.ProducerConfig;import org.apache.kafka.clients.producer.ProducerRecord;import org.apache.kafka.common.serialization.StringSerializer;import java.util.Properties;import java.util.Scanner;public class MyProducer {    public static void main(String[] args) {        Properties properties = new Properties();        //生产者的配置文件        properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG,"192.168.153.144:9092");        //key的序列化        properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);        //value的序列化        properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,StringSerializer.class);               properties.put(ProducerConfig.ACKS_CONFIG,"1");        KafkaProducer producer = new KafkaProducer(properties);        Scanner scanner = new Scanner(System.in);        while (true){            System.out.println("请输入kafka的内容");            String msg =scanner.next();            ProducerRecord record = new ProducerRecord("kb22",msg);            producer.send(record);        }    }}

(2)、Producer进行多线程操作

  生产者多线程是一种常见的技术实践,可以提高消息生产的并发性和吞吐量。通过将消息生产任务分配给多个线程来并行地发送消息,可以有效地利用系统资源,加快消息的发送速度。

package nj.zb.kb22.Kafka;import org.apache.kafka.clients.producer.KafkaProducer;import org.apache.kafka.clients.producer.ProducerConfig;import org.apache.kafka.clients.producer.ProducerRecord;import org.apache.kafka.common.serialization.StringSerializer;import java.util.Properties;import java.util.concurrent.ExecutorService;import java.util.concurrent.Executors;public class MyProducer2 {    public static void main(String[] args) {        ExecutorService executorService = Executors.newCachedThreadPool();        for (int i = 0; i < 10; i++) {//i代表线程            Thread thread =new Thread(new Runnable() {                @Override                public void run() {                    Properties properties = new Properties();                      properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG,"192.168.153.144:9092");   properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);                properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,StringSerializer.class);  properties.put(ProducerConfig.ACKS_CONFIG,"0");  KafkaProducer producer = new KafkaProducer(properties);                    //多线程操作 j代表消息                    for (int j = 0; j < 100; j++) {                        String msg=Thread.currentThread().getName()+" "+ j;                        System.out.println(msg);                        ProducerRecord re = new ProducerRecord("kb22", msg);                        producer.send(re);                    }                }            });            executorService.execute(thread);        }        executorService.shutdown();        while (true){            if (executorService.isTerminated()){                System.out.println("game over");                break;            }        }    }}

三、消费者方法

(1)、Consumer

通过java来实现消费者

package nj.zb.kb22.Kafka;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 org.apache.kafka.common.serialization.StringDeserializer;import org.apache.kafka.common.serialization.StringSerializer;import java.time.Duration;import java.util.Collections;import java.util.Properties;public class MyConsumer {    public static void main(String[] args) {        Properties properties = new Properties();        properties.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG,"192.168.153.144:9092");        properties.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);        properties.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG,StringDeserializer.class);        //设置拉取信息后是否自动提交(kafka记录当前app是否已经获取到此信息),false 手动提交 ;true 自动提交        properties.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG,"false");                properties.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG,"earliest");        properties.put(ConsumerConfig.GROUP_ID_CONFIG,"GROUP3");        KafkaConsumer consumer = new KafkaConsumer(properties);        //创建好kafka消费者对象后,订阅消息,指定消费的topic        consumer.subscribe(Collections.singleton("kb22"));        while (true){            Duration mills = Duration.ofMillis(100);            ConsumerRecords records = consumer.poll(mills);            for (ConsumerRecord record:records){                String topic = record.topic();                int partition = record.partition();                long offset = record.offset();                String key = record.key();                String value = record.value();                long timestamp = record.timestamp();                System.out.println("topic:"+topic+"\tpartition"+partition+"\toffset"+offset+"\TKEy"+key+"\tvalue"+value+"\ttimestamp"+timestamp);            }            //consumer.commitAsync();//手动提交        }    }}

(2)、设置多人访问

package nj.zb.kb22.Kafka;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 org.apache.kafka.common.serialization.StringDeserializer;import java.time.Duration;import java.util.Collections;import java.util.Properties;public class MyConsumerThread {    //模仿多人访问    public static void main(String[] args) {        for (int i = 0; i <3; i++) {            new Thread(new Runnable() {                @Override                public void run() {                    Properties properties = new Properties();                    properties.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG,"192.168.153.144:9092");                    properties.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);                    properties.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG,StringDeserializer.class);                    //设置拉取信息后是否自动提交(kafka记录当前app是否已经获取到此信息),false 手动提交 ;true 自动提交                    properties.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG,"false");                                        properties.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG,"earliest");                    properties.put(ConsumerConfig.GROUP_ID_CONFIG,"GROUP3");                    KafkaConsumer consumer = new KafkaConsumer<>(properties);                    consumer.subscribe(Collections.singleton("kb22"));                    while (true){                        //poll探寻数据                        ConsumerRecords records = consumer.poll(Duration.ofMillis(100));                        for (ConsumerRecordrecord:records){String topic = record.topic();int partition = record.partition();long offset = record.offset();String key = record.key();String value = record.value();long timestamp = record.timestamp();String name = Thread.currentThread().getName();System.out.println("name"+name        +"\ttopic:"+topic        +"\tpartition" +partition        +"\toffset"+offset        +"\tkey"+key        +"\tvalue"+value        +"\ttimestamp"+timestamp);                        }                    }                }            }).start();        }    }}

来源地址:https://blog.csdn.net/ycz926940/article/details/131562785

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本文标题: 大数据之Kafka————java来实现kafka相关操作

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