Map Avro files on Java class with different field names

Question

I've got a problem with simple spark task, which reads Avro file and then save it as Hive parquet table.

I've got 2 types of file, in general they are the same, but the key struct is a little different - field names.

Type 1

root
|-- pk: strucnt (nullable = true)
    |-- term_id: string (nullale = true)

Type 2

root
|-- pk: strucnt (nullable = true)
    |-- id: string (nullale = true)

I'm reading Avro using spark-avro. And then map this DF to bean like this

Dataset<SomeClass> df = avroDF.as(Encoders.bean(SomeClass.class));

SomeClass is a simple one-field class with getter and setter.

public class SomeClass{
    private String term_id;
    ...
}

So if I'm reading Avro type 1 - it's OK. But if I'm reading Avro type 2 - the error occures. And vice versa if I'm changing the field name to private String id;

Is there any universal solution for my problem? I found @AvroName, but it doesn't allow to set several names. Thanks.

Answer 1

Only one way is to change dataset fieldname to the name which is in schema. Use this example to do it:

val newName = Seq("id", "x1", "x2", "x3")
Dataset<SomeClass> df = avroDF.toDF(newNames: _*).as(Encoders.bean(SomeClass.class));

You can't cast dataframe to a BeanClass which has different field names.

Answer 2

The possible solution is

StructType avroExtendedSchema = avroDF.schema().add("id",DataTypes.StringType);
avroDF.map(row->RowFactory(row.getStruct(0),row.getStruct(0).getString(0)), 
       RowEncoder.apply(avroExtendedSchema)).toDF();

So the second field of DF will be named "id" and contain the string key. First "pk" struct can be dropped in the future.

avroDF.drop("pk");

PS I found the third type of schema:

root
|-- pk: strucnt (nullable = true)
    |-- id: int(nullale = true)

So the final code is like:

DataType keyType = avroDF.select("pk.*").schema().fields[0].dataType();
StructType avroExtendedSchema = avroDF.schema().add("id",keyType);
avroDF.map(row->RowFactory(row.getStruct(0),row.getStruct(0).get(0)), 
       RowEncoder.apply(avroExtendedSchema)).drop("pk").toDF();

This code suites for any primitive\\String key.