当我尝试如下操作时，它对我很好，您可以尝试打印有助于比较的模式，也可以删除null（）以供长类型尝试。

fields.name("key1").type().nullable().longType().longDefault(0);

import org.apache.avro.AvroRuntimeException;
import org.apache.avro.Schema;
import org.apache.avro.SchemaBuilder;
import org.apache.avro.SchemaBuilder.FieldAssembler;
import org.apache.avro.SchemaBuilder.RecordBuilder;
import org.apache.avro.file.DataFileReader;
import org.apache.avro.file.DataFileWriter;
import org.apache.avro.generic.GenericData.Record;
import org.apache.avro.generic.GenericDatumReader;
import org.apache.avro.generic.GenericDatumWriter;
import org.apache.avro.generic.GenericRecord;
import org.apache.avro.generic.GenericRecordBuilder;
import org.apache.avro.io.DatumReader;
import org.apache.avro.io.DatumWriter;

import java.io.File;
import java.io.IOException;

public class GenericRecordExample {

  public static void main(String[] args) {

    FieldAssembler<Schema> fields;
    RecordBuilder<Schema> record = SchemaBuilder.record("Customer");
    fields = record.namespace("com.example").fields();
    fields = fields.name("first_name").type().nullable().stringType().noDefault();
    fields = fields.name("last_name").type().nullable().stringType().noDefault();
    fields = fields.name("account_number").type().nullable().longType().longDefault(0);

    Schema schema = fields.endRecord();
    System.out.println(schema.toString());

    // we build our first customer
    GenericRecordBuilder customerBuilder = new GenericRecordBuilder(schema);
    customerBuilder.set("first_name", "John");
    customerBuilder.set("last_name", "Doe");
    customerBuilder.set("account_number", 999333444111L);
    Record myCustomer = customerBuilder.build();
    System.out.println(myCustomer);

    // writing to a file
    final DatumWriter<GenericRecord> datumWriter = new GenericDatumWriter<>(schema);
    try (DataFileWriter<GenericRecord> dataFileWriter = new DataFileWriter<>(datumWriter)) {
      dataFileWriter.create(myCustomer.getSchema(), new File("customer-generic.avro"));
      dataFileWriter.append(myCustomer);
      System.out.println("Written customer-generic.avro");
    } catch (IOException e) {
      System.out.println("Couldn't write file");
      e.printStackTrace();
    }

    // reading from a file
    final File file = new File("customer-generic.avro");
    final DatumReader<GenericRecord> datumReader = new GenericDatumReader<>();
    GenericRecord customerRead;
    try (DataFileReader<GenericRecord> dataFileReader = new DataFileReader<>(file, datumReader)){
      customerRead = dataFileReader.next();
      System.out.println("Successfully read avro file");
      System.out.println(customerRead.toString());

      // get the data from the generic record
      System.out.println("First name: " + customerRead.get("first_name"));

      // read a non existent field
      System.out.println("Non existent field: " + customerRead.get("not_here"));
    }
    catch(IOException e) {
      e.printStackTrace();
    }
  }
}

如果我正确理解您的问题，您正在尝试接受JSON字符串并将它们保存在Cloud Storage存储桶中，在数据通过数据流时使用Avro作为数据的编码器。在我看来，您的代码没有任何明显的错误。我已经这样做了，包括将数据保存到Cloud Storage和BigQuery。

您可以考虑使用一种更简单且可能更不容易出错的方法：为您的数据定义一个Java类，并在其上使用Avro注释以使编码器能够正常工作。这是一个例子：

import org.apache.avro.reflect.Nullable;
import org.apache.beam.sdk.coders.AvroCoder;
import org.apache.beam.sdk.coders.DefaultCoder;

@DefaultCoder(AvroCoder.class)
public class Data {
    public long nonNullableValue;
    @Nullable public long nullableValue;
}

然后，在您的DnFn实现中使用此类型，就像您可能已经使用的那样。Beam应该能够使用Avro在工作人员之间正确移动数据，即使标记为@Nullable的字段为空。