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https://issues.apache.org/jira/browse/FLINK-3871?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15983208#comment-15983208
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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_r113241294
  
    --- 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;
    --- End diff --
    
    `GenericRecord` -> `SpecificRecord`


> 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}}.



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