class_docstr: Represents the source of a dataset stored in a spark table.
class_docstr_tok: ["Represents","the","source","of","a","dataset","stored","in","a","spark","table","."]
docstr: Loads the dataset source as a Spark Dataset Source.
  
  Returns:
      An instance of ``pyspark.sql.DataFrame``.
docstr_tok: ["Loads","the","dataset","source","as","a","Spark","Dataset","Source",".","Returns",":","An","instance","of","``","pyspark.sql.DataFrame","``","."]
code: def load(self, **kwargs):  # pylint: disable=unused-argument
      """Loads the dataset source as a Spark Dataset Source.
  
      Returns:
          An instance of ``pyspark.sql.DataFrame``.
  
      """
      from pyspark.sql import SparkSession
  
      spark = SparkSession.builder.getOrCreate()
  
      if self._path:
          return spark.read.parquet(self._path)
      if self._table_name:
          return spark.read.table(self._table_name)
      if self._sql:
          return spark.sql(self._sql)
  
file_path: mlflow/mlflow/data/spark_dataset_source.py
imports: from typing import Any, Dict, Optional
  from mlflow.data.dataset_source import DatasetSource
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.utils.annotations import experimental
label_desc: Use image node_id 3 for calling the SparkDatasetSource obj's underlying member method code with example usage: obj.load() and returns: spark, spark, spark