Hi people!

I was digging deeper this days and found the "root cause" of the issue and the 
difference between avro reading from files and avro reading from Kafka & SR.

plz see: 
https://lists.apache.org/x/thread.html/r8ad7bd574f7dc4904139295c7de612a35438571c5b9caac673521d22@%3Cuser.flink.apache.org%3E

The main problem with Kafka & SR is, that the 
"org.apache.avro.generic.GenericDatumReader" is initialized with and "expected" 
schema which is taken from the flinks sql table definition. When it comes to 
deserializing the and attribute with type "enum" it does not match with the 
expected schema where this same attribute is typed as "string". Hence avro 
deserializer breaks here.

Not sure how to tackle that issue. The functioning of the 
"GeneraticDatumReader" can not really be changed. A solution could be to create 
an analogues reader for reading data based on SQL ddl.

Cheers, Peter

On 2021/10/12 16:18:30 Dongwon Kim 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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