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ASF GitHub Bot commented on FLINK-3871: --------------------------------------- Github user fhueske commented on a diff in the pull request: https://github.com/apache/flink/pull/3663#discussion_r113241182 --- Diff: flink-connectors/flink-connector-kafka-base/src/main/java/org/apache/flink/streaming/util/serialization/AvroRowDeserializationSchema.java --- @@ -0,0 +1,157 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.flink.streaming.util.serialization; + +import java.io.ByteArrayInputStream; +import java.io.IOException; +import java.util.List; +import org.apache.avro.Schema; +import org.apache.avro.generic.GenericData; +import org.apache.avro.generic.GenericRecord; +import org.apache.avro.io.DatumReader; +import org.apache.avro.io.Decoder; +import org.apache.avro.io.DecoderFactory; +import org.apache.avro.reflect.ReflectDatumReader; +import org.apache.avro.specific.SpecificData; +import org.apache.avro.specific.SpecificRecord; +import org.apache.avro.util.Utf8; +import org.apache.flink.types.Row; +import org.apache.flink.util.Preconditions; + +/** + * Deserialization schema from Avro bytes over {@link SpecificRecord} to {@link Row}. + * + * Deserializes the <code>byte[]</code> messages into (nested) Flink Rows. + * + * {@link Utf8} is converted to regular Java Strings. + */ +public class AvroRowDeserializationSchema extends AbstractDeserializationSchema<Row> { + + /** + * Schema for deterministic field order. + */ + private final Schema schema; + + /** + * Reader that deserializes byte array into a record. + */ + private final DatumReader<GenericRecord> datumReader; + + /** + * Input stream to read message from. + */ + private final MutableByteArrayInputStream inputStream; + + /** + * Avro decoder that decodes binary data + */ + private final Decoder decoder; + + /** + * Record to deserialize byte array to. + */ + private GenericRecord record; + + /** + * Creates a Avro deserialization schema for the given record. + * + * @param recordClazz Avro record class used to deserialize Avro's record to Flink's row + */ + @SuppressWarnings("unchecked") + public AvroRowDeserializationSchema(Class<? extends SpecificRecord> recordClazz) { + Preconditions.checkNotNull(recordClazz, "Avro record class must not be null."); + this.schema = SpecificData.get().getSchema(recordClazz); + this.datumReader = new ReflectDatumReader<>(schema); + this.record = new GenericData.Record(schema); --- End diff -- We can use a specific record here. We have the class for it. ``` this.record = (SpecificRecord) SpecificData.newInstance(recordClazz, schema); ``` > Add Kafka TableSource with Avro serialization > --------------------------------------------- > > Key: FLINK-3871 > URL: https://issues.apache.org/jira/browse/FLINK-3871 > Project: Flink > Issue Type: New Feature > Components: Table API & SQL > Reporter: Fabian Hueske > Assignee: Ivan Mushketyk > > Add a Kafka TableSource which supports Avro serialized data. > The KafkaAvroTableSource should support two modes: > # SpecificRecord Mode: In this case the user specifies a class which was > code-generated by Avro depending on a schema. Flink treats these classes as > regular POJOs. Hence, they are also natively supported by the Table API and > SQL. Classes generated by Avro contain their Schema in a static field. The > schema should be used to automatically derive field names and types. Hence, > there is no additional information required than the name of the class. > # GenericRecord Mode: In this case the user specifies an Avro Schema. The > schema is used to deserialize the data into a GenericRecord which must be > translated into possibly nested {{Row}} based on the schema information. > Again, the Avro Schema is used to automatically derive the field names and > types. This mode is less efficient than the SpecificRecord mode because the > {{GenericRecord}} needs to be converted into {{Row}}. > This feature depends on FLINK-5280, i.e., support for nested data in > {{TableSource}}. -- This message was sent by Atlassian JIRA (v6.3.15#6346)