要在没有模式注册表的情况下反序列化AVRO，可以使用Confluent的Schema Registry客户端库进行手动解析和反序列化AVRO消息。下面是一个示例代码，演示了如何使用AWS MSK S3 Sink Connector将AVRO消息写入S3，并在不使用模式注册表的情况下进行反序列化：

import com.amazonaws.services.s3.AmazonS3;
import com.amazonaws.services.s3.AmazonS3ClientBuilder;
import com.amazonaws.services.s3.model.ObjectMetadata;
import io.confluent.kafka.serializers.AbstractKafkaAvroDeserializer;
import org.apache.avro.generic.GenericRecord;
import org.apache.commons.io.IOUtils;
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.TopicPartition;
import org.apache.kafka.common.serialization.StringDeserializer;

import java.io.ByteArrayInputStream;
import java.io.InputStream;
import java.nio.charset.StandardCharsets;
import java.util.Collections;
import java.util.Properties;

public class AvroDeserializerWithoutRegistry {

    public static void main(String[] args) {
        String topic = "your-topic";
        String bootstrapServers = "your-bootstrap-servers";
        String s3Bucket = "your-s3-bucket";
        String s3KeyPrefix = "your-s3-key-prefix";

        Properties props = new Properties();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
        props.put(ConsumerConfig.GROUP_ID_CONFIG, "avro-consumer");
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);

        KafkaConsumer consumer = new KafkaConsumer<>(props);
        consumer.subscribe(Collections.singletonList(topic));

        AmazonS3 s3Client = AmazonS3ClientBuilder.defaultClient();

        while (true) {
            ConsumerRecords records = consumer.poll(100);
            for (ConsumerRecord record : records) {
                String key = record.key();
                String avroPayload = record.value();

                // Deserialize AVRO payload
                byte[] avroBytes = avroPayload.getBytes(StandardCharsets.ISO_8859_1);
                GenericRecord genericRecord = deserializeAvro(avroBytes);

                // Upload AVRO payload to S3
                String s3Key = s3KeyPrefix + key + ".avro";
                ObjectMetadata metadata = new ObjectMetadata();
                metadata.setContentLength(avroBytes.length);
                InputStream inputStream = new ByteArrayInputStream(avroBytes);
                s3Client.putObject(s3Bucket, s3Key, inputStream, metadata);
                IOUtils.closeQuietly(inputStream);
            }
            consumer.commitSync();
        }
    }

    private static GenericRecord deserializeAvro(byte[] avroBytes) {
        // Replace "your-schema" with your actual AVRO schema
        String schema = "your-schema";
        AbstractKafkaAvroDeserializer deserializer = new AbstractKafkaAvroDeserializer() {
            @Override
            protected Object deserialize(String topic, Boolean isKey, byte[] payload) {
                return null;
            }
        };
        deserializer.configure(Collections.singletonMap("schema.registry.url", ""), false);
        return (GenericRecord) deserializer.deserialize("", avroBytes, schema);
    }
}

请确保替换代码中的以下值：

• your-topic：要消费的Kafka主题
• your-bootstrap-servers：Kafka集群的引导服务器地址
• your-s3-bucket：要将AVRO消息写入的S3存储桶
• your-s3-key-prefix：用于AVRO消息在S3中的键前缀
• your-schema：用于AVRO消息的实际模式

在上述代码中，我们使用了AbstractKafkaAvroDeserializer类来手动反序列化AVRO消息，替代了通常使用的模式注册表。然后，我们使用AWS SDK将AVRO消息上传到S3存储桶中。

请注意，由于没有使用模式注册表，我们需要手动提供AVRO模式。在示例代码中，将"your-schema"替换为您的AVRO模式。