





from __future__ import annotations




def  lowerCAmelCase_ (							UpperCamelCase_					,		UpperCamelCase_  )     ->		int:
       if len(UpperCamelCase_  ) < k or k < 0:
              raise ValueError("Invalid Input"  )
       UpperCamelCase_          =  UpperCamelCase_          =  sum(array[:k]  )
       for i in range(len(UpperCamelCase_  ) - k  ):
              UpperCamelCase_          =  current_sum - array[i] + array[i + k]
              UpperCamelCase_          =  max(UpperCamelCase_					,		UpperCamelCase_  )
       return max_sum


if __name__ == "__main__":
     from doctest import testmod
     from random import randint

     testmod()
     _UpperCAmelCase        =				[randint(-1_0_0_0, 1_0_0_0) for i in range(1_0_0)]
     _UpperCAmelCase        =				randint(0, 1_1_0)
     print(f'''The maximum sum of {k} consecutive elements is {max_sum_in_array(array,k)}''')








from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader



class 							_UpperCamelCase					(	lowerCAmelCase_     ):

       def __init__(		self: List[Any]					,   _SCREAMING_SNAKE_CASE: pyspark.sql.DataFrame					,   _SCREAMING_SNAKE_CASE: Optional[NamedSplit] = None					,   _SCREAMING_SNAKE_CASE: Optional[Features] = None					,   _SCREAMING_SNAKE_CASE: bool = True					,   _SCREAMING_SNAKE_CASE: str = None					,   _SCREAMING_SNAKE_CASE: bool = False					,   _SCREAMING_SNAKE_CASE: str = None					,   _SCREAMING_SNAKE_CASE: bool = True					,   _SCREAMING_SNAKE_CASE: str = "arrow"					,   **_SCREAMING_SNAKE_CASE: Union[str, Any]					,   )       -> Any:




              """simple docstring"""


              super().__init__(
                  split=_SCREAMING_SNAKE_CASE					,   features=_SCREAMING_SNAKE_CASE					,   cache_dir=_SCREAMING_SNAKE_CASE					,   keep_in_memory=_SCREAMING_SNAKE_CASE					,   streaming=_SCREAMING_SNAKE_CASE					,   **_SCREAMING_SNAKE_CASE					,   )
              UpperCamelCase_          =  load_from_cache_file
              UpperCamelCase_          =  file_format
              UpperCamelCase_          =  Spark(
                  df=_SCREAMING_SNAKE_CASE					,   features=_SCREAMING_SNAKE_CASE					,   cache_dir=_SCREAMING_SNAKE_CASE					,   working_dir=_SCREAMING_SNAKE_CASE					,   **_SCREAMING_SNAKE_CASE					,   )



       def lowercase (		self: str		)       -> Optional[Any]:




              """simple docstring"""


              if self.streaming:
                     return self.builder.as_streaming_dataset(split=self.split		)
              UpperCamelCase_          =  None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
              self.builder.download_and_prepare(
                  download_mode=_SCREAMING_SNAKE_CASE					,   file_format=self._file_format					,   )
              return self.builder.as_dataset(split=self.split		)

