class_docstr: Provides arguments to Spark UDFs.
docstr: Given a data source definition, load the data as a Spark DataFrame.
  
  Args:
      data_source (Union[FeatureGroupDataSource, CSVDataSource, ParquetDataSource,
          BaseDataSource]): A user specified data source from the feature_processor
          decorator's parameters.
      params (Optional[Dict[str, Union[str, Dict]]]): Parameters provided to the
          feature_processor decorator.
  
  Returns:
      DataFrame: The contents of the data source as a Spark DataFrame.
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code: def _load_data_frame(
      self,
      data_source: Union[
          FeatureGroupDataSource,
          CSVDataSource,
          ParquetDataSource,
          BaseDataSource,
      ],
      params: Optional[Dict[str, Union[str, Dict]]] = None,
  ) -> DataFrame:
      """Given a data source definition, load the data as a Spark DataFrame.
  
      Args:
          data_source (Union[FeatureGroupDataSource, CSVDataSource, ParquetDataSource,
              BaseDataSource]): A user specified data source from the feature_processor
              decorator's parameters.
          params (Optional[Dict[str, Union[str, Dict]]]): Parameters provided to the
              feature_processor decorator.
  
      Returns:
          DataFrame: The contents of the data source as a Spark DataFrame.
      """
      if isinstance(data_source, (CSVDataSource, ParquetDataSource)):
          return self.input_loader.load_from_s3(data_source)
  
      if isinstance(data_source, FeatureGroupDataSource):
          return self.input_loader.load_from_feature_group(data_source)
  
      if isinstance(data_source, PySparkDataSource):
          spark_session = self.spark_session_factory.spark_session
          return data_source.read_data(
              spark=spark_session, params=params
          )
  
      if isinstance(data_source, BaseDataSource):
          return data_source.read_data(params=params)
  
      raise ValueError(f"Unknown data source type: {type(data_source)}")
  
imports: from __future__ import absolute_import
  from abc import ABC, abstractmethod
  from inspect import signature
  from typing import Any, Callable, Dict, Generic, List, OrderedDict, TypeVar, Union, Optional
  import attr
  from pyspark.sql import DataFrame, SparkSession
  from sagemaker.feature_store.feature_processor._data_source import CSVDataSource, FeatureGroupDataSource, ParquetDataSource, BaseDataSource, PySparkDataSource
  from sagemaker.feature_store.feature_processor._feature_processor_config import FeatureProcessorConfig
  from sagemaker.feature_store.feature_processor._input_loader import SparkDataFrameInputLoader
  from sagemaker.feature_store.feature_processor._params_loader import ParamsLoader
  from sagemaker.feature_store.feature_processor._spark_factory import SparkSessionFactory
label_desc: Use image node_id 5 for calling the SparkArgProvider obj's underlying member method code with example usage: obj._load_data_frame(data_source, params) and returns: self, self, data_source, data_source