,可以通过以下步骤实现:
以下是一个示例代码,演示了如何将带有参数的案例类转换为Avro消息并发送到Kafka:
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericRecord;
import org.apache.avro.io.BinaryEncoder;
import org.apache.avro.io.EncoderFactory;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
public class AvroProducer {
private static final String SCHEMA_JSON = "{\"type\":\"record\",\"name\":\"Example\",\"fields\":[{\"name\":\"param1\",\"type\":\"string\"},{\"name\":\"param2\",\"type\":\"int\"}]}";
private static final String KAFKA_TOPIC = "example_topic";
private static final String KAFKA_BOOTSTRAP_SERVERS = "localhost:9092";
public static void main(String[] args) {
// 创建Avro Schema
Schema.Parser parser = new Schema.Parser();
Schema schema = parser.parse(SCHEMA_JSON);
// 创建Kafka Producer
KafkaProducer<String, byte[]> producer = new KafkaProducer<>(getKafkaConfig());
// 创建案例类实例
Example example = new Example("value1", 123);
// 将案例类转换为Avro消息
GenericRecord record = new GenericData.Record(schema);
record.put("param1", example.getParam1());
record.put("param2", example.getParam2());
byte[] avroMessage = serializeAvroMessage(record, schema);
// 发送Avro消息到Kafka
ProducerRecord<String, byte[]> kafkaRecord = new ProducerRecord<>(KAFKA_TOPIC, avroMessage);
producer.send(kafkaRecord);
producer.close();
}
private static byte[] serializeAvroMessage(GenericRecord record, Schema schema) {
ByteArrayOutputStream outputStream = new ByteArrayOutputStream();
BinaryEncoder encoder = EncoderFactory.get().binaryEncoder(outputStream, null);
try {
org.apache.avro.io.DatumWriter<GenericRecord> writer = new org.apache.avro.specific.SpecificDatumWriter<>(schema);
writer.write(record, encoder);
encoder.flush();
outputStream.close();
} catch (IOException e) {
e.printStackTrace();
}
return outputStream.toByteArray();
}
private static Map<String, Object> getKafkaConfig() {
Map<String, Object> config = new HashMap<>();
config.put("bootstrap.servers", KAFKA_BOOTSTRAP_SERVERS);
config.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
config.put("value.serializer", "org.apache.kafka.common.serialization.ByteArraySerializer");
return config;
}
}
class Example {
private String param1;
private int param2;
public Example(String param1, int param2) {
this.param1 = param1;
this.param2 = param2;
}
public String getParam1() {
return param1;
}
public int getParam2() {
return param2;
}
}
在上述示例代码中,我们创建了一个名为"Example"的Avro Schema,包含了两个字段:"param1"和"param2"。然后,我们创建了一个名为"Example"的案例类,并将其实例化为"example"对象。接下来,我们将案例类对象转换为Avro消息,并使用Kafka Producer将Avro消息发送到名为"example_topic"的Kafka主题。
请注意,示例代码中的Kafka配置和主题名称是示意性的,你需要根据实际情况进行修改。
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希望以上信息能对你有所帮助!如有更多问题,请随时提问。
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