class_docstr: A class that provides distributed, random access to a Dataset.
  
  See: ``Dataset.to_random_access_dataset()``.
class_docstr_tok: ["A","class","that","provides","distributed",",","random","access","to","a","Dataset",".","See",":","``","Dataset.to_random_access_dataset","(",")","``","."]
docstr: Asynchronously finds the record for a single key.
  
  Args:
      key: The key of the record to find.
  
  Returns:
      ObjectRef containing the record (in pydict form), or None if not found.
docstr_tok: ["Asynchronously","finds","the","record","for","a","single","key",".","Args",":","key",":","The","key","of","the","record","to","find",".","Returns",":","ObjectRef","containing","the","record","(","in","pydict","form",")",",","or","None","if","not","found","."]
code: def get_async(self, key: Any) -> ObjectRef[Any]:
      """Asynchronously finds the record for a single key.
  
      Args:
          key: The key of the record to find.
  
      Returns:
          ObjectRef containing the record (in pydict form), or None if not found.
      """
      block_index = self._find_le(key)
      if block_index is None:
          return ray.put(None)
      return self._worker_for(block_index).get.remote(block_index, key)
  
imports: import bisect
  import logging
  import random
  import time
  from collections import defaultdict
  from typing import TYPE_CHECKING, Any, List, Optional
  import numpy
  import ray
  from ray.data._internal.remote_fn import cached_remote_fn
  from ray.data.block import BlockAccessor
  from ray.data.context import DataContext
  from ray.types import ObjectRef
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 3 for calling the RandomAccessDataset obj's underlying member method code with example usage: obj.get_async(key) and returns: self, ray