code: def to_pandas_without_arrow(
      columns,
      squeeze=False,
      index_col=None,
      dtype=None,
      index_map=None,
      batch_size=None,
  ):
      def f(iter):
          import pandas as pd
  
          counter = 0
          data = []
          for row in iter:
              counter += 1
              data.append(row)
              if batch_size and counter % batch_size == 0:
                  pd_df = pd.DataFrame(data, columns=columns)
                  pd_df = set_pandas_df_type_index(
                      pd_df, squeeze, index_col, dtype, index_map
                  )
                  yield pd_df
                  data = []
          if data:
              pd_df = pd.DataFrame(data, columns=columns)
              pd_df = set_pandas_df_type_index(
                  pd_df, squeeze, index_col, dtype, index_map
              )
              yield pd_df
  
      return f
  
imports: from bigdl.dllib.utils.file_utils import get_file_list, callZooFunc
  from bigdl.dllib.utils.utils import convert_row_to_numpy
  from bigdl.dllib.utils.common import *
  from bigdl.dllib.utils.log4Error import *
  import pyspark.sql.functions
  from typing import TYPE_CHECKING, Dict, List, Optional, Type, Union
  from numpy import float32, int32
label_desc: Use image node_id 23 for calling a global function with example usage: to_pandas_without_arrow(columns, squeeze, index_col, dtype, index_map, batch_size) and returns: f