class_docstr: Implementation of `Dataset.limit()`.
code: def __init__(self, limit: int):
      self._limit = limit
      super().__init__(
          "Limit",
          None,
          self._do_limit,
      )
  
imports: import itertools
  from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
  import ray
  from ray.data._internal.block_list import BlockList
  from ray.data._internal.delegating_block_builder import DelegatingBlockBuilder
  from ray.data._internal.execution.interfaces import TaskContext
  from ray.data._internal.fast_repartition import fast_repartition
  from ray.data._internal.plan import AllToAllStage
  from ray.data._internal.remote_fn import cached_remote_fn
  from ray.data._internal.shuffle_and_partition import PushBasedShufflePartitionOp, SimpleShufflePartitionOp
  from ray.data._internal.sort import SortKey, sort_impl
  from ray.data._internal.split import _split_at_index, _split_at_indices
  from ray.data.block import Block, BlockAccessor, BlockExecStats, BlockMetadata, BlockPartition
  from ray.data.context import DataContext
label_desc: Use image node_id 1 to create a new LimitStage object from inherited base classes: AllToAllStage with example: obj = LimitStage(limit)