First of all, are you sure the input data is correct? From the stacktrace
it seems to me the issue might be that the input data is invalid.

Looking at the code of AvroToRowDataConverters, It sounds like STRING
should work with avro enums. Can you provide a minimal reproducer (without
confluent schema registry) with a valid input?

On Tue, Oct 12, 2021 at 6:19 PM Dongwon Kim <eastcirc...@gmail.com> wrote:

> Hi community,
>
> Can I get advice on this question?
>
> Another user just sent me an email asking whether I found a solution or a
> workaround for this question, but I'm still stuck there.
>
> Any suggestions?
>
> Thanks in advance,
>
> Dongwon
>
> ---------- Forwarded message ---------
> From: Dongwon Kim <eastcirc...@gmail.com>
> Date: Mon, Aug 9, 2021 at 7:26 PM
> Subject: How to deserialize Avro enum type in Flink SQL?
> To: user <user@flink.apache.org>
>
>
> Hi community,
>
> I have a Kafka topic where the schema of its values is defined by the
> "MyRecord" record in the following Avro IDL and registered to the Confluent
> Schema Registry.
>
>> @namespace("my.type.avro")
>> protocol MyProtocol {
>>   enum MyEnumType {
>>     TypeVal1, TypeVal2
>>   }
>>   record MyEntry {
>>     MyEnumType type;
>>   }
>>   record MyRecord {
>>     array<MyEntry> entries;
>>   }
>> }
>
>
> To read from the topic, I've defined the following DDL:
>
>> CREATE TABLE my_table
>
> (
>>     `entries` ARRAY<ROW<
>>         *`type` ??? (This is the main question)*
>>     >>
>> ) WITH (
>>     'connector' = 'kafka',
>>     'topic' = 'my-topic',
>>     'properties.bootstrap.servers' = '...:9092',
>>     'scan.startup.mode' = 'latest-offset',
>>     'value.format' = 'avro-confluent',
>>     'value.avro-confluent.schema-registry.url' = 'http://...:8081'
>>
> )
>
>
> And I run the following query :
>
>> SELECT * FROM my_table
>
>
> Now I got the following messages in Flink-1.13.1 when I use *STRING* for
> the type:
>
>> *Caused by: java.io.IOException: Failed to deserialize Avro record.*
>>   at
>> org.apache.flink.formats.avro.AvroRowDataDeserializationSchema.deserialize(AvroRowDataDeserializationSchema.java:106)
>>   at
>> org.apache.flink.formats.avro.AvroRowDataDeserializationSchema.deserialize(AvroRowDataDeserializationSchema.java:46)
>>   at
>> org.apache.flink.api.common.serialization.DeserializationSchema.deserialize(DeserializationSchema.java:82)
>>   at
>> org.apache.flink.streaming.connectors.kafka.table.DynamicKafkaDeserializationSchema.deserialize(DynamicKafkaDeserializationSchema.java:113)
>>   at
>> org.apache.flink.streaming.connectors.kafka.internals.KafkaFetcher.partitionConsumerRecordsHandler(KafkaFetcher.java:179)
>>   at
>> org.apache.flink.streaming.connectors.kafka.internals.KafkaFetcher.runFetchLoop(KafkaFetcher.java:142)
>>   at
>> org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:826)
>>   at
>> org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:110)
>>   at
>> org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:66)
>>   at
>> org.apache.flink.streaming.runtime.tasks.SourceStreamTask$LegacySourceFunctionThread.run(SourceStreamTask.java:269)
>> *Caused by: org.apache.avro.AvroTypeException: Found
>> my.type.avro.MyEnumType, expecting union*
>>   at
>> org.apache.avro.io.ResolvingDecoder.doAction(ResolvingDecoder.java:308)
>>   at org.apache.avro.io.parsing.Parser.advance(Parser.java:86)
>>   at
>> org.apache.avro.io.ResolvingDecoder.readIndex(ResolvingDecoder.java:275)
>>   at
>> org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:187)
>>   at
>> org.apache.avro.generic.GenericDatumReader.readArray(GenericDatumReader.java:298)
>>   at
>> org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:183)
>>   at
>> org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:160)
>>   at
>> org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:187)
>>   at
>> org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:160)
>>   at
>> org.apache.avro.generic.GenericDatumReader.readField(GenericDatumReader.java:259)
>>   at
>> org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:247)
>>   at
>> org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:179)
>>   at
>> org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:160)
>>   at
>> org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:153)
>>   at
>> org.apache.flink.formats.avro.RegistryAvroDeserializationSchema.deserialize(RegistryAvroDeserializationSchema.java:81)
>>   at
>> org.apache.flink.formats.avro.AvroRowDataDeserializationSchema.deserialize(AvroRowDataDeserializationSchema.java:103)
>>   ... 9 more
>
> The reason I use the STRING type is just for fast-prototyping.
>
> While reading through [1], I've been thinking about using *RAW('class',
> 'snapshot')* where 'class' is my.type.avro.MyEnumType, but I'm not sure
> whether it is a good idea and if so, what can be a value for the snapshot.
>
> [1]
> https://ci.apache.org/projects/flink/flink-docs-release-1.13/docs/dev/table/types/#raw
>
> Thanks in advance,
>
> Dongwon
>

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