code: def merge_chunk(
      lhs,
      *args,
      result_meta,
      **kwargs,
  ):
      rhs, *args = args
      left_index = kwargs.get("left_index", False)
      right_index = kwargs.get("right_index", False)
      empty_index_dtype = result_meta.index.dtype
      categorical_columns = result_meta.select_dtypes(
          include="category"
      ).columns
  
      if categorical_columns is not None:
          for col in categorical_columns:
              left = None
              right = None
  
              if col in lhs:
                  left = lhs[col]
              elif col == kwargs.get("right_on", None) and left_index:
                  if isinstance(lhs.index.dtype, pd.CategoricalDtype):
                      left = lhs.index
  
              if col in rhs:
                  right = rhs[col]
              elif col == kwargs.get("left_on", None) and right_index:
                  if isinstance(rhs.index.dtype, pd.CategoricalDtype):
                      right = rhs.index
  
              dtype = "category"
              if left is not None and right is not None:
                  dtype = methods.union_categoricals(
                      [
                          left.astype("category"),
                          right.astype("category"),
                      ]
                  ).dtype
  
              if left is not None:
                  if isinstance(left, pd.Index):
                      lhs.index = left.astype(dtype)
                  else:
                      lhs = lhs.assign(**{col: left.astype(dtype)})
              if right is not None:
                  if isinstance(right, pd.Index):
                      rhs.index = right.astype(dtype)
                  else:
                      rhs = rhs.assign(**{col: right.astype(dtype)})
  
      out = lhs.merge(rhs, *args, **kwargs)
  
      # Workaround for pandas bug where if the left frame of a merge operation is
      # empty, the resulting dataframe can have columns in the wrong order.
      # https://github.com/pandas-dev/pandas/issues/9937
      if len(lhs) == 0:
          out = out[result_meta.columns]
  
      # Workaround pandas bug where if the output result of a merge operation is
      # an empty dataframe, the output index is `int64` in all cases, regardless
      # of input dtypes.
      if len(out) == 0 and empty_index_dtype is not None:
          out.index = out.index.astype(empty_index_dtype)
      return out
  
imports: from __future__ import annotations
  import math
  import pickle
  import warnings
  from functools import partial, wraps
  import numpy
  import pandas
  from pandas.api.types import is_dtype_equal
  from tlz import merge_sorted, unique
  from dask.base import is_dask_collection, tokenize
  from dask.dataframe import methods
  from dask.dataframe.core import DataFrame, Index, Series, _concat, _deprecated_kwarg, _Frame, _maybe_from_pandas, is_broadcastable, map_partitions, new_dd_object, prefix_reduction, suffix_reduction
  from dask.dataframe.dispatch import group_split_dispatch, hash_object_dispatch
  from dask.dataframe.io import from_pandas
  from dask.dataframe.shuffle import partitioning_index, rearrange_by_divisions, shuffle, shuffle_group
  from dask.dataframe.utils import asciitable, check_meta, is_dataframe_like, is_series_like, make_meta, strip_unknown_categories
  from dask.highlevelgraph import HighLevelGraph
  from dask.layers import BroadcastJoinLayer
  from dask.utils import M, apply, get_default_shuffle_method
label_desc: Use image node_id 4 for calling a global function with example usage: merge_chunk(lhs) and returns: out