Is it possible to deserialize Avro message(consuming message from Kafka) without giving Reader schema in ConfluentRegistryAvroDeserializationSchema - apache-kafka

Question

I am using Kafka Connector in Apache Flink for access to streams served by Confluent Kafka.
Apart from schema registry url ConfluentRegistryAvroDeserializationSchema.forGeneric(...) expecting 'reader' schema.
Instead of providing read schema I want to use same writer's schema(lookup in registry) for reading the message too because Consumer will not have latest schema.
FlinkKafkaConsumer010<GenericRecord> myConsumer =
new FlinkKafkaConsumer010<>("topic-name", ConfluentRegistryAvroDeserializationSchema.forGeneric(<reader schema goes here>, "http://host:port"), properties);
myConsumer.setStartFromLatest();
https://ci.apache.org/projects/flink/flink-docs-release-1.9/dev/connectors/kafka.html
"Using these deserialization schema record will be read with the schema that was retrieved from Schema Registry and transformed to a statically provided"
Since I do not want to keep schema definition at consumer side how do I deserialize Avro message from Kafka using writer's schema?
Appreciate your help!

Answer 1

I don't think it is possible to use directly ConfluentRegistryAvroDeserializationSchema.forGeneric. It is intended to be used with a reader schema and they have preconditions checking for this.
You have to implement your own. Two import things:
Set specific.avro.reader to false (other wise you'll get specific records)
The KafkaAvroDeserializer has to be lazily initialized (because it isn't serializable it self, as it holds a reference to the schema registry client)
import io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient;
import io.confluent.kafka.schemaregistry.client.SchemaRegistryClient;
import io.confluent.kafka.serializers.AbstractKafkaAvroSerDeConfig;
import io.confluent.kafka.serializers.KafkaAvroDeserializer;
import io.confluent.kafka.serializers.KafkaAvroDeserializerConfig;
import java.util.HashMap;
import java.util.Map;
import org.apache.avro.generic.GenericRecord;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.java.typeutils.TypeExtractor;
import org.apache.flink.streaming.util.serialization.KeyedDeserializationSchema;
public class KafkaGenericAvroDeserializationSchema
implements KeyedDeserializationSchema<GenericRecord> {
private final String registryUrl;
private transient KafkaAvroDeserializer inner;
public KafkaGenericAvroDeserializationSchema(String registryUrl) {
this.registryUrl = registryUrl;
}
#Override
public GenericRecord deserialize(
byte[] messageKey, byte[] message, String topic, int partition, long offset) {
checkInitialized();
return (GenericRecord) inner.deserialize(topic, message);
}
#Override
public boolean isEndOfStream(GenericRecord nextElement) {
return false;
}
#Override
public TypeInformation<GenericRecord> getProducedType() {
return TypeExtractor.getForClass(GenericRecord.class);
}
private void checkInitialized() {
if (inner == null) {
Map<String, Object> props = new HashMap<>();
props.put(AbstractKafkaAvroSerDeConfig.SCHEMA_REGISTRY_URL_CONFIG, registryUrl);
props.put(KafkaAvroDeserializerConfig.SPECIFIC_AVRO_READER_CONFIG, false);
SchemaRegistryClient client =
new CachedSchemaRegistryClient(
registryUrl, AbstractKafkaAvroSerDeConfig.MAX_SCHEMAS_PER_SUBJECT_DEFAULT);
inner = new KafkaAvroDeserializer(client, props);
}
}
}
env.addSource(
new FlinkKafkaConsumer<>(
topic,
new KafkaGenericAvroDeserializationSchema(schemaReigstryUrl),
kafkaProperties));