Apache Kafka 与 Confluent Schema Registry 一起使用
创始人
2024-09-04 09:30:19
0

使用Apache Kafka与Confluent Schema Registry一起的解决方案包括以下几个步骤:

  1. 安装和配置Apache Kafka和Confluent Schema Registry

首先,需要按照官方文档的指导安装和配置Apache Kafka和Confluent Schema Registry。可以从Confluent官方网站上下载并安装Confluent Platform,该平台包含了Kafka和Schema Registry。

  1. 创建一个Kafka主题

在Kafka中,消息被发布到主题(topic)中。可以使用以下代码创建一个Kafka主题:

import kafka.admin.AdminUtils;
import kafka.utils.ZKStringSerializer$;
import org.I0Itec.zkclient.ZkClient;
import scala.collection.JavaConversions;

public class KafkaTopicCreator {
    public static void createTopic(String topicName, int numPartitions, int replicationFactor, Properties zkProperties) {
        ZkClient zkClient = new ZkClient(zkProperties.getProperty("zookeeper.connect"), 10000, 10000, ZKStringSerializer$.MODULE$);
        AdminUtils.createTopic(zkClient, topicName, numPartitions, replicationFactor, new Properties(), null);
        zkClient.close();
    }

    public static void main(String[] args) {
        Properties zkProperties = new Properties();
        zkProperties.setProperty("zookeeper.connect", "localhost:2181");
        createTopic("my-topic", 1, 1, zkProperties);
    }
}
  1. 创建一个Schema

在使用Confluent Schema Registry之前,需要定义和注册一个Schema。Schema是按照Avro格式定义的数据结构。以下是一个示例Avro Schema的定义:

{
    "type": "record",
    "name": "User",
    "fields": [
        {"name": "id", "type": "int"},
        {"name": "name", "type": "string"},
        {"name": "email", "type": "string"}
    ]
}
  1. 使用Confluent Schema Registry发送和接收消息

使用Confluent Schema Registry发送和接收消息需要使用Avro格式的数据,并使用Schema进行序列化和反序列化。以下是一个示例代码:

import io.confluent.kafka.serializers.KafkaAvroSerializer;
import org.apache.kafka.clients.producer.*;
import org.apache.kafka.common.serialization.StringSerializer;

import java.util.Properties;

public class KafkaAvroProducer {
    public static void main(String[] args) {
        Properties properties = new Properties();
        properties.setProperty("bootstrap.servers", "localhost:9092");
        properties.setProperty("key.serializer", StringSerializer.class.getName());
        properties.setProperty("value.serializer", KafkaAvroSerializer.class.getName());
        properties.setProperty("schema.registry.url", "http://localhost:8081");

        String topic = "my-topic";

        Producer producer = new KafkaProducer<>(properties);

        User user = new User(1, "John Doe", "johndoe@example.com");

        ProducerRecord record = new ProducerRecord<>(topic, user);
        producer.send(record, new Callback() {
            @Override
            public void onCompletion(RecordMetadata metadata, Exception exception) {
                if (exception != null) {
                    exception.printStackTrace();
                } else {
                    System.out.println("Message sent successfully to topic " + metadata.topic());
                }
            }
        });

        producer.flush();
        producer.close();
    }
}
import io.confluent.kafka.serializers.KafkaAvroDeserializer;
import org.apache.kafka.clients.consumer.*;
import org.apache.kafka.common.serialization.StringDeserializer;

import java.time.Duration;
import java.util.Collections;
import java.util.Properties;

public class KafkaAvroConsumer {
    public static void main(String[] args) {
        Properties properties = new Properties();
        properties.setProperty("bootstrap.servers", "localhost:9092");
        properties.setProperty("key.deserializer", StringDeserializer.class.getName());
        properties.setProperty("value.deserializer", KafkaAvroDeserializer.class.getName());
        properties.setProperty("schema.registry.url", "http://localhost:8081");
        properties.setProperty("group.id", "my-group");

        String topic = "my-topic";

        KafkaConsumer consumer = new KafkaConsumer<>(properties);
        consumer.subscribe(Collections.singleton(topic));

        while (true) {
            ConsumerRecords records = consumer.poll(Duration.ofMillis(100));
            for (ConsumerRecord record : records) {
                User user = record.value();
                System.out.println("Received message: " + user.toString());
            }
        }
    }
}

在上述代码中,User类是

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