Créer un JAR d'un bean personnalisé

package org.example.local_project.beansjar.kafka_avro_beans;

import io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient;
import io.confluent.kafka.serializers.KafkaAvroSerializer;
import io.confluent.kafka.serializers.KafkaAvroSerializerConfig;

public class KafkaAvroSerializerBean extends KafkaAvroSerializer {

	@Override
	public void configure(KafkaAvroSerializerConfig config) {
		this.schemaRegistry = new CachedSchemaRegistryClient(config.getSchemaRegistryUrls(), 1000);
		this.strategyUsesSchema(true);
		this.autoRegisterSchema = true;
//		this.useSchemaReflection = true;
//		this.normalizeSchema = true;
//		this.useLatestVersion = true; 
//		this.avroReflectionAllowNull = true;
	}
}

package org.example.local_project.beansjar.kafka_avro_beans;

import io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient;
import io.confluent.kafka.serializers.KafkaAvroDeserializer;
import io.confluent.kafka.serializers.KafkaAvroDeserializerConfig;

public class KafkaAvroDeserializerBean extends KafkaAvroDeserializer {

	@Override
	public void configure(KafkaAvroDeserializerConfig config) {
		this.schemaRegistry = new CachedSchemaRegistryClient(config.getSchemaRegistryUrls(), 1000);
		this.useSpecificAvroReader = false;
	}
}

package org.example.local_project.beansjar.kafka_avro_beans;

import java.io.ByteArrayOutputStream;
import java.nio.charset.StandardCharsets;

import org.apache.avro.Schema;

import org.apache.avro.generic.GenericData.Record;
import org.apache.avro.generic.GenericDatumReader;
import org.apache.avro.generic.GenericDatumWriter;
import org.apache.avro.io.DatumReader;
import org.apache.avro.io.DatumWriter;
import org.apache.avro.io.DecoderFactory;
import org.apache.avro.io.EncoderFactory;
import org.apache.avro.io.JsonEncoder;


public class KafkaAvroConverterBean {

	// AVRO schema
	static Schema  schema = new Schema.Parser().parse( 
			"{" 
	         + "\"doc\": \"Sample schema to help you get started.\"," 
	         + "\"fields\": [" 
		     + "{"
			 + "\"doc\": \"The int type is a 32-bit signed integer.\"," 
		     + "\"name\": \"my_field1\","
			 + "\"type\": \"int\"" 
			 + "}," 
			 + "{"
			 + "\"doc\": \"The double type is a double precision (64-bit) IEEE 754 floating-point number.\","
			 + "\"name\": \"my_field2\"," 
			 + "\"type\": \"int\"" 
			 + "}," 
			 + "{"
			 + "\"doc\": \"The string is a unicode character sequence.\"," 
			 + "\"name\": \"my_field3\","
			 + "\"type\": \"string\"" 
			 + "}" 
			 + "]," 
			 + "\"name\": \"AvroSample\","
			 + "\"namespace\": \"talend\"," 
			 + "\"type\": \"record\"" 
			 + "}");
	
	
	public static String avroToJsonString(Object body) throws RuntimeException {
		try {
			ByteArrayOutputStream baos = new ByteArrayOutputStream();
            DatumWriter<Record> writer = new GenericDatumWriter<Record>(schema);
            JsonEncoder encoder = EncoderFactory.get().jsonEncoder(schema, baos, false);
            writer.write((Record)body, encoder);
            encoder.flush();
            baos.flush();
            return new String(baos.toByteArray(), StandardCharsets.UTF_8);
	    } catch (Exception e) {
		      throw new RuntimeException(
		          String.format("Error coverting Avro to Json of schema %s", schema), e);
	    } 
	}
	
	public static Record jsonStringToAvro(Object jsonString) throws RuntimeException {
	    try {
	      DatumReader<Object> reader = new GenericDatumReader<Object>(schema);
	      return (Record)reader.read(null, DecoderFactory.get().jsonDecoder(schema, (String)jsonString));
	    } catch (Exception e) {
		      throw new RuntimeException(
		          String.format("Error coverting json %s to Avro of schema %s", jsonString, schema), e);
	    }
	}
}