Avro does not respect default values defined in schema

[basimons]

Hello,

I encountered something strange while doing some tests with the avro decoding.

Example here, was ran in version 2.16.0:

 String avroWithDefault = """
        {
        "type": "record",
        "name": "Employee",
        "fields": [
         {"name": "name", "type": ["string", "null"], "default" : "bram"},
         {"name": "age", "type": "int"},
         {"name": "emails", "type": {"type": "array", "items": "string"}},
         {"name": "boss", "type": ["Employee","null"]}
        ]}
        """;

// Notice no name field
String employeeJson = """
{
    "age" : 26,
    "emails" : ["[email protected]"],
    "boss" : {
         "name" : "test",
         "age" : 33,
         "emails" : ["[email protected]"]
    }
}
""";

SchemaFormat schema = new AvroMapper().schemaFrom(avroWithDefault);
JsonNode jsonObject = new ObjectMapper().reader().readTree(payload);
byte[] objectAsBytes = new AvroMapper().writer().with(formatSchema).writeValueAsBytes(jsonObject);

// Decode it again
JsonNode decodedObject = new AvroMapper().reader(schema).readTree(payload);

System.out.println(decodedObject.toString());

If you look at this object you see that the default value is not filled. It is just a null, all the other fields are filled just as expected. I tried this with different schemas and not having a union with a null, but just the default, but that would result in a JsonMappingException.

Am I doing something wrong here, or is this not supported? It doesn't say that it does not support default values like it says in the protobuffer one.

Thanks in advance

EDIT: This makes sense that it does not work, as you cannot write a AVRO file with a default without a value for it. I think it should've thrown an error on writing. But the main question is why it doesn't work with a reading schema that has a default, but a writing schema that does have one. See my other question.

[cowtowncoder]

I think this is not supported, at least with Jackson's native Avro read implementation. Apache Avro-lib -backed variant, while slower, might handle default values correctly.

As to how to enable Apache Avro lib backend, I think there are unit tests that do that.

I agree, it'd be good to document this gap.

[basimons]

Thanks for your response.

I tried looking for a unit test, but I couldn't find one. I did however find the ApacheAvroparserImpl. When I implemented it like this:

  try (AvroParser parser =new ApacheAvroFactory(new AvroMapper()).createParser(payload)) {
            parser.setSchema(schema);
            
            TreeNode treeNode = parser.readValueAsTree();
            System.out.println(treeNode);
        };

It does not work unfortunately (as in no default values). Am I doing it correctly or should I also use a different codec?

[basimons]

I made some changes, as of course the code that I showed in my first message does not fully make sense. You cannot not write a value, even if it has a default. So I changed it to this:

 String writingSchema = """
        {
        "type": "record",
        "name": "Employee",
        "fields": [
         {"name": "age", "type": "int"},
         {"name": "emails", "type": {"type": "array", "items": "string"}},
         {"name": "boss", "type": ["Employee","null"]}
        ]}
        """;

        String readingSchema = """
        {
        "type": "record",
        "name": "Employee",
        "fields": [
         {"name": "name", "type": ["string", "null"], "default" : "bram"},
         {"name": "age", "type": "int"},
         {"name": "emails", "type": {"type": "array", "items": "string"}},
         {"name": "boss", "type": ["Employee","null"]}
        ]}
        """;


        String employeeJson = """
            {
                "age" : 26,
                "emails" : ["[email protected]", "[email protected]"],
                "boss" : {
                    "age" : 33,
                    "emails" : ["[email protected]"]
                }
            }
            """;

When I do this, when I read the values, I get the following exception: java.io.IOException: Invalid Union index (26); union only has 2 types. Which is the same as reported here: #164

[cowtowncoder]

The only other note I have is that this:

new ApacheAvroFactory(new AvroMapper()).

is wrong way around: it should be

new AvroMapper(new ApacheAvroFactory)

to have correct linking; and then you should be able to create ObjectReader / ObjectWriter through which you can assign schema.

But I suspect that won't change things too much: you should either way have ApacheAvroFactory that is using Apache Avro lib.

[basimons]

Ah thanks, didn't know that. I tried it, but as you said it did indeed not work.

Whats weird, I even tried decoding it with the apache avro library myself. I just used GenericDatumReader (and all things that come with it), but I would get exactly the same error. This does not make sense right? As I'm sure that what I'm doing is allowed by Avro (adding a default field in a reader schema, that is not in the write schema), as I have done it many times in my Kafka cluster.

Do you happen to know what the difference might be? Do my Kafka clients do anything special for this?

[basimons]

I finally get it. In your kafka cluster it saves the writing schema with it. If you parse it like this:

  Schema avroSchema = ((AvroSchema) schema).getAvroSchema();
        GenericDatumReader<GenericRecord> objectGenericDatumReader = new GenericDatumReader<>(writingschema, avroSchema);

BinaryDecoder binaryDecoder = DecoderFactory.get().binaryDecoder(payload, null);
GenericRecord read = objectGenericDatumReader.read(null, binaryDecoder);

So with the specific writer schema.

It does work. Normally kafka does it this way for you, but I don't think the AvroMapper has a way do to it with 2 schemas.

[cowtowncoder]

@basimons Avro module does indeed allow use of 2 schema (read/write) configuration -- it's been a while so I'll have to see how it was done. I think AvroMapper has methods to construct Jackson AvroSchema from 2 separate schemas.

[cowtowncoder]

Ah. Close: AvroSchema has method withReaderSchema(AvroSchema rs) where you get both schema instances, then call method on "writer schema" (one used on writing records). From ArrayEvolutionTest:

        final AvroSchema srcSchema = MAPPER.schemaFrom(SCHEMA_XY_ARRAY_JSON);
        final AvroSchema dstSchema = MAPPER.schemaFrom(SCHEMA_XYZ_ARRAY_JSON);
        final AvroSchema xlate = srcSchema.withReaderSchema(dstSchema);

and then you construct ObjectReader as usual.