class_docstr: Deserialization schema from Avro bytes to Row. Deserializes the byte[] messages into (nested)
  Flink rows. It converts Avro types into types that are compatible with Flink's Table & SQL API.
  
  Projects with Avro records containing logical date/time types need to add a JodaTime dependency.
class_docstr_tok: ["Deserialization","schema","from","Avro","bytes","to","Row",".","Deserializes","the","byte","[","]","messages","into","(","nested",")","Flink","rows",".","It","converts","Avro","types","into","types","that","are","compatible","with","Flink","'s","Table","&","SQL","API",".","Projects","with","Avro","records","containing","logical","date\/time","types","need","to","add","a","JodaTime","dependency","."]
docstr: Creates an Avro deserialization schema for the given specific record class or Avro schema
  string. Having the concrete Avro record class might improve performance.
  
  :param record_class: Avro record class used to deserialize Avro's record to Flink's row.
  :param avro_schema_string: Avro schema string to deserialize Avro's record to Flink's row.
docstr_tok: ["Creates","an","Avro","deserialization","schema","for","the","given","specific","record","class","or","Avro","schema","string",".","Having","the","concrete","Avro","record","class","might","improve","performance",".",":","param","record_class",":","Avro","record","class","used","to","deserialize","Avro","'s","record","to","Flink","'s","row",".",":","param","avro_schema_string",":","Avro","schema","string","to","deserialize","Avro","'s","record","to","Flink","'s","row","."]
code: def __init__(
      self, record_class: str = None, avro_schema_string: str = None
  ):
      """
      Creates an Avro deserialization schema for the given specific record class or Avro schema
      string. Having the concrete Avro record class might improve performance.
  
      :param record_class: Avro record class used to deserialize Avro's record to Flink's row.
      :param avro_schema_string: Avro schema string to deserialize Avro's record to Flink's row.
      """
  
      if avro_schema_string is None and record_class is None:
          raise TypeError(
              "record_class or avro_schema_string should be specified."
          )
      j_deserialization_schema = None
      if record_class is not None:
          gateway = get_gateway()
          java_import(gateway.jvm, record_class)
          j_record_class = load_java_class(record_class)
          JAvroRowDeserializationSchema = (
              get_gateway().jvm.org.apache.flink.formats.avro.AvroRowDeserializationSchema
          )
          j_deserialization_schema = JAvroRowDeserializationSchema(
              j_record_class
          )
  
      elif avro_schema_string is not None:
          JAvroRowDeserializationSchema = (
              get_gateway().jvm.org.apache.flink.formats.avro.AvroRowDeserializationSchema
          )
          j_deserialization_schema = JAvroRowDeserializationSchema(
              avro_schema_string
          )
  
      super(AvroRowDeserializationSchema, self).__init__(
          j_deserialization_schema
      )
  
imports: from py4j.java_gateway import get_java_class, JavaObject, java_import
  from pyflink.common.io import InputFormat
  from pyflink.common.serialization import BulkWriterFactory, SerializationSchema, DeserializationSchema
  from pyflink.common.typeinfo import TypeInformation
  from pyflink.datastream.utils import ResultTypeQueryable
  from pyflink.java_gateway import get_gateway
  from pyflink.util.java_utils import get_field_value, load_java_class
label_desc: Use image node_id 1 to create a new AvroRowDeserializationSchema object from inherited base classes: DeserializationSchema with example: obj = AvroRowDeserializationSchema(record_class, avro_schema_string)