[ 
https://issues.apache.org/jira/browse/FLINK-9444?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16531128#comment-16531128
 ] 

ASF GitHub Bot commented on FLINK-9444:
---------------------------------------

Github user twalthr commented on a diff in the pull request:

    https://github.com/apache/flink/pull/6218#discussion_r199748214
  
    --- Diff: 
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/AvroRowDeserializationSchema.java
 ---
    @@ -17,154 +17,338 @@
     
     package org.apache.flink.formats.avro;
     
    +import org.apache.flink.annotation.PublicEvolving;
     import 
org.apache.flink.api.common.serialization.AbstractDeserializationSchema;
    +import org.apache.flink.api.common.typeinfo.BasicArrayTypeInfo;
     import org.apache.flink.api.common.typeinfo.TypeInformation;
    -import org.apache.flink.formats.avro.typeutils.AvroRecordClassConverter;
    +import org.apache.flink.api.common.typeinfo.Types;
    +import org.apache.flink.api.java.typeutils.MapTypeInfo;
    +import org.apache.flink.api.java.typeutils.ObjectArrayTypeInfo;
    +import org.apache.flink.api.java.typeutils.RowTypeInfo;
    +import org.apache.flink.formats.avro.typeutils.AvroSchemaConverter;
     import org.apache.flink.formats.avro.utils.MutableByteArrayInputStream;
     import org.apache.flink.types.Row;
     import org.apache.flink.util.Preconditions;
     
    +import org.apache.avro.LogicalTypes;
     import org.apache.avro.Schema;
    -import org.apache.avro.generic.GenericRecord;
    +import org.apache.avro.generic.GenericData;
    +import org.apache.avro.generic.GenericDatumReader;
    +import org.apache.avro.generic.GenericFixed;
    +import org.apache.avro.generic.IndexedRecord;
     import org.apache.avro.io.DatumReader;
     import org.apache.avro.io.Decoder;
     import org.apache.avro.io.DecoderFactory;
     import org.apache.avro.specific.SpecificData;
     import org.apache.avro.specific.SpecificDatumReader;
     import org.apache.avro.specific.SpecificRecord;
    -import org.apache.avro.specific.SpecificRecordBase;
    -import org.apache.avro.util.Utf8;
    +import org.joda.time.DateTime;
    +import org.joda.time.DateTimeFieldType;
    +import org.joda.time.LocalDate;
    +import org.joda.time.LocalTime;
     
     import java.io.IOException;
     import java.io.ObjectInputStream;
     import java.io.ObjectOutputStream;
    +import java.lang.reflect.Array;
    +import java.math.BigDecimal;
    +import java.math.BigInteger;
    +import java.nio.ByteBuffer;
    +import java.sql.Date;
    +import java.sql.Time;
    +import java.sql.Timestamp;
    +import java.util.HashMap;
     import java.util.List;
    +import java.util.Map;
    +import java.util.TimeZone;
     
     /**
    - * Deserialization schema from Avro bytes over {@link SpecificRecord} to 
{@link Row}.
    + * Deserialization schema from Avro bytes to {@link Row}.
      *
    - * <p>Deserializes the <code>byte[]</code> messages into (nested) Flink 
Rows.
    + * <p>Deserializes the <code>byte[]</code> messages into (nested) Flink 
rows. It converts Avro types
    + * into types that are compatible with Flink's Table & SQL API.
      *
    - * {@link Utf8} is converted to regular Java Strings.
    + * <p>Projects with Avro records containing logical date/time types need 
to add a JodaTime
    + * dependency.
    + *
    + * <p>Note: Changes in this class need to be kept in sync with the 
corresponding runtime
    + * class {@link AvroRowSerializationSchema} and schema converter {@link 
AvroSchemaConverter}.
      */
    +@PublicEvolving
     public class AvroRowDeserializationSchema extends 
AbstractDeserializationSchema<Row> {
     
        /**
    -    * Avro record class.
    +    * Used for time conversions into SQL types.
    +    */
    +   private static final TimeZone LOCAL_TZ = TimeZone.getDefault();
    +
    +   /**
    +    * Avro record class for deserialization. Might be null if record class 
is not available.
         */
        private Class<? extends SpecificRecord> recordClazz;
     
        /**
    -    * Schema for deterministic field order.
    +    * Schema string for deserialization.
    +    */
    +   private String schemaString;
    +
    +   /**
    +    * Avro serialization schema.
         */
        private transient Schema schema;
     
        /**
    -    * Reader that deserializes byte array into a record.
    +    * Type information describing the result type.
         */
    -   private transient DatumReader<SpecificRecord> datumReader;
    +   private transient TypeInformation<Row> typeInfo;
     
        /**
    -    * Input stream to read message from.
    +    * Record to deserialize byte array.
         */
    -   private transient MutableByteArrayInputStream inputStream;
    +   private transient IndexedRecord record;
     
        /**
    -    * Avro decoder that decodes binary data.
    +    * Reader that deserializes byte array into a record.
         */
    -   private transient Decoder decoder;
    +   private transient DatumReader<IndexedRecord> datumReader;
     
        /**
    -    * Record to deserialize byte array to.
    +    * Input stream to read message from.
         */
    -   private SpecificRecord record;
    +   private transient MutableByteArrayInputStream inputStream;
     
        /**
    -    * Type information describing the result type.
    +    * Avro decoder that decodes binary data.
         */
    -   private transient TypeInformation<Row> typeInfo;
    +   private transient Decoder decoder;
     
        /**
    -    * Creates a Avro deserialization schema for the given record.
    +    * Creates a Avro deserialization schema for the given specific record 
class. Having the
    +    * concrete Avro record class might improve performance.
         *
         * @param recordClazz Avro record class used to deserialize Avro's 
record to Flink's row
         */
    -   public AvroRowDeserializationSchema(Class<? extends SpecificRecordBase> 
recordClazz) {
    +   public AvroRowDeserializationSchema(Class<? extends SpecificRecord> 
recordClazz) {
                Preconditions.checkNotNull(recordClazz, "Avro record class must 
not be null.");
                this.recordClazz = recordClazz;
    -           this.schema = SpecificData.get().getSchema(recordClazz);
    -           this.datumReader = new SpecificDatumReader<>(schema);
    -           this.record = (SpecificRecord) 
SpecificData.newInstance(recordClazz, schema);
    -           this.inputStream = new MutableByteArrayInputStream();
    -           this.decoder = DecoderFactory.get().binaryDecoder(inputStream, 
null);
    -           this.typeInfo = AvroRecordClassConverter.convert(recordClazz);
    +           schema = SpecificData.get().getSchema(recordClazz);
    +           typeInfo = AvroSchemaConverter.convert(recordClazz);
    +           schemaString = schema.toString();
    +           record = (SpecificRecord) SpecificData.newInstance(recordClazz, 
schema);
    +           datumReader = new SpecificDatumReader<>(schema);
    +           inputStream = new MutableByteArrayInputStream();
    +           decoder = DecoderFactory.get().binaryDecoder(inputStream, null);
    +   }
    +
    +   /**
    +    * Creates a Avro deserialization schema for the given Avro schema 
string.
    +    *
    +    * @param avroSchemaString Avro schema string to deserialize Avro's 
record to Flink's row
    +    */
    +   public AvroRowDeserializationSchema(String avroSchemaString) {
    +           Preconditions.checkNotNull(avroSchemaString, "Avro schema must 
not be null.");
    +           recordClazz = null;
    +           typeInfo = AvroSchemaConverter.convert(avroSchemaString);
    +           schemaString = avroSchemaString;
    +           schema = new Schema.Parser().parse(avroSchemaString);
    +           record = new GenericData.Record(schema);
    +           datumReader = new GenericDatumReader<>(schema);
    +           inputStream = new MutableByteArrayInputStream();
    +           decoder = DecoderFactory.get().binaryDecoder(inputStream, null);
    +           // check for a schema that describes a record
    +           if (!(typeInfo instanceof RowTypeInfo)) {
    +                   throw new IllegalArgumentException("Row type 
information expected.");
    +           }
        }
     
        @Override
        public Row deserialize(byte[] message) throws IOException {
    -           // read record
                try {
                        inputStream.setBuffer(message);
    -                   this.record = datumReader.read(record, decoder);
    -           } catch (IOException e) {
    -                   throw new RuntimeException("Failed to deserialize 
Row.", e);
    +                   final IndexedRecord read = datumReader.read(record, 
decoder);
    --- End diff --
    
    Good point. I had a specific record before and changed it to 
`IndexedRecord` later. Will correct that.


> KafkaAvroTableSource failed to work for map and array fields
> ------------------------------------------------------------
>
>                 Key: FLINK-9444
>                 URL: https://issues.apache.org/jira/browse/FLINK-9444
>             Project: Flink
>          Issue Type: Bug
>          Components: Kafka Connector, Table API &amp; SQL
>    Affects Versions: 1.6.0
>            Reporter: Jun Zhang
>            Assignee: Jun Zhang
>            Priority: Blocker
>              Labels: patch, pull-request-available
>             Fix For: 1.6.0
>
>         Attachments: flink-9444.patch
>
>
> When some Avro schema has map/array fields and the corresponding TableSchema 
> declares *MapTypeInfo/ListTypeInfo* for these fields, an exception will be 
> thrown when registering the *KafkaAvroTableSource*, complaining like:
> Exception in thread "main" org.apache.flink.table.api.ValidationException: 
> Type Map<String, Integer> of table field 'event' does not match with type 
> GenericType<java.util.Map> of the field 'event' of the TableSource return 
> type.
>  at org.apache.flink.table.api.ValidationException$.apply(exceptions.scala:74)
>  at 
> org.apache.flink.table.sources.TableSourceUtil$$anonfun$validateTableSource$1.apply(TableSourceUtil.scala:92)
>  at 
> org.apache.flink.table.sources.TableSourceUtil$$anonfun$validateTableSource$1.apply(TableSourceUtil.scala:71)
>  at 
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
>  at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
>  at 
> org.apache.flink.table.sources.TableSourceUtil$.validateTableSource(TableSourceUtil.scala:71)
>  at 
> org.apache.flink.table.plan.schema.StreamTableSourceTable.<init>(StreamTableSourceTable.scala:33)
>  at 
> org.apache.flink.table.api.StreamTableEnvironment.registerTableSourceInternal(StreamTableEnvironment.scala:124)
>  at 
> org.apache.flink.table.api.TableEnvironment.registerTableSource(TableEnvironment.scala:438)



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