code: 
  
  
  
  
  import json
  import os
  from dataclasses import dataclass
  
  import numpy as np
  import pyarrow as pa
  
  import datasets
  from utils import get_duration
  
  
  _A							    =	1000_0000_0000
  _A							    =	1_0000
  
  _A    , _A							    =	os.path.split(__file__)
  _A							    =	os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))
  def 						lowerCAmelCase_       (	__a	,	__a )       ->			datasets.Dataset:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: List[str]	     =pa.Table.from_pydict({'''col''': [0] * chunk_size} )
  							SCREAMING_SNAKE_CASE			: Optional[Any]	     =pa.concat_tables([table] * (num_examples // chunk_size) )
  							return datasets.Dataset(__a	,	fingerprint='''table_100B''' )
  
  
  @dataclass
  class 							_lowerCAmelCase		:
  				lowerCamelCase__									=    42
  				lowerCamelCase__									=    42
  				lowerCamelCase__									=    42
  				lowerCamelCase__									=    42
  
  
  
  
  				def     __a		( self							)    ->      List[Any]:
  											SCREAMING_SNAKE_CASE			: Optional[Any]	     =np.random.default_rng(self.seed							)
  											SCREAMING_SNAKE_CASE			: str	     =rng.integers(low=self.low		,		high=self.high		,		size=self.size							).tolist()
  
  
  
  
  				def __iter__( self							)    ->      int:
  											return iter(self._sampled_values							)
  
  
  
  
  
  
  
  				def __len__( self							)    ->      int:
  											return self.size
  
  
  
  
  
  
  
  @get_duration
  def 						lowerCAmelCase_       (	__a )       ->			Tuple:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: Optional[int]	     =dataset[0]
  @get_duration
  def 						lowerCAmelCase_       (	__a )       ->			Union[str, Any]:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: str	     =dataset[-1]
  @get_duration
  def 						lowerCAmelCase_       (	__a )       ->			List[Any]:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: int	     =dataset[range(len(__a ) // 2	,	len(__a ) // 2 + 1024 )]
  @get_duration
  def 						lowerCAmelCase_       (	__a )       ->			List[Any]:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: int	     =dataset[RandIter(0	,	len(__a )	,	1024	,	seed=42 )]
  def 						lowerCAmelCase_       (	)       ->			Tuple:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: Tuple	     ={'''num examples''': SPEED_TEST_N_EXAMPLES}
  							SCREAMING_SNAKE_CASE			: Dict	     =(get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
  							print('''generating dataset''' )
  							SCREAMING_SNAKE_CASE			: Dict	     =generate_100B_dataset(num_examples=__a	,	chunk_size=__a )
  							print('''Functions''' )
  							for func in functions:
  														print(func.__name__ )
  														SCREAMING_SNAKE_CASE			: List[str]	     =func(__a )
  
  							with open(__a	,	'''wb''' ) as f:
  														f.write(json.dumps(__a ).encode('''utf-8''' ) )
  
  
  if __name__ == "__main__":  # useful to run the profiler
  							benchmark_table_100B()
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  from __future__ import annotations
  def 						lowerCAmelCase_       (	__a	,	__a	,	__a	,	__a )       ->			None:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE     ,							SCREAMING_SNAKE_CASE			: Any	     =m - 1, 0
  							while i >= 0 and j < n:
  														if key == mat[i][j]:
  																					print(f'Key {key} found at row- {i + 1} column- {j + 1}' )
  																					return
  														if key < mat[i][j]:
  																					i -= 1
  														else:
  																					j += 1
  							print(f'Key {key} not found' )
  def 						lowerCAmelCase_       (	)       ->			None:
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: int	     =[[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
  							SCREAMING_SNAKE_CASE			: List[str]	     =int(input('''Enter the element to be searched:''' ) )
  							print(__a )
  							search_in_a_sorted_matrix(__a	,	len(__a )	,	len(mat[0] )	,	__a )
  
  
  if __name__ == "__main__":
  							import doctest
  
  							doctest.testmod()
  							main()
  
  
  
  
  
  
  