code: def _concat_index(cls, prev_index: pd.Index, cur_index: pd.Index):
      if isinstance(prev_index, pd.RangeIndex) and isinstance(
          cur_index, pd.RangeIndex
      ):
          # handle RangeIndex that append may generate huge amount of data
          # e.g. pd.RangeIndex(10_000) and pd.RangeIndex(10_000)
          # will generate a Int64Index full of data
          # for details see GH#1647
          prev_stop = (
              prev_index.start + prev_index.size * prev_index.step
          )
          cur_start = cur_index.start
          if (
              prev_stop == cur_start
              and prev_index.step == cur_index.step
          ):
              # continuous RangeIndex, still return RangeIndex
              return prev_index.append(cur_index)
          else:
              # otherwise, return an empty index
              return pd.Index([], dtype=prev_index.dtype)
      elif isinstance(prev_index, pd.RangeIndex):
          return pd.Index([], prev_index.dtype).append(cur_index)
      elif isinstance(cur_index, pd.RangeIndex):
          return prev_index.append(pd.Index([], cur_index.dtype))
      return prev_index.append(cur_index)
  
imports: import pandas
  import numpy
  from ...None import opcodes
  from ...core import ENTITY_TYPE, OutputType, recursive_tile
  from ...serialization.serializables import FieldTypes, ListField, StringField, BoolField, AnyField
  from ...utils import lazy_import, has_unknown_shape
  from ..operands import DataFrameOperand, DataFrameOperandMixin, SERIES_TYPE
  from ..utils import parse_index, build_empty_df, build_empty_series, standardize_range_index, validate_axis
label_desc: Use image node_id 8 for calling the DataFrameConcat obj's underlying member method code with example usage: obj._concat_index(cls, prev_index, cur_index) and returns: prev_index, prev_index, pd, pd, prev_index