code: def Read_tpch_files(column_names, files_dir, table, data_types):
      table_pdf = None
      dataframes = []
  
      for dataFile in listdir(files_dir):
          if isdir(files_dir + "/" + dataFile):
              continue
          dataFileTokens = dataFile.split(".")
          dataFileName = dataFileTokens[0]
          dataFileExt = dataFileTokens[1]
          tableName_ = table + "_"
          if dataFileExt == "psv":
              if (table == dataFileName) or re.match(
                  tableName_, dataFileName
              ):
                  file_dir = files_dir + "/" + dataFile
                  tmp = cudf.read_csv(
                      file_dir,
                      delimiter="|",
                      names=column_names,
                      dtype=data_types,
                  )
                  dataframes.append(tmp)
      if len(dataframes) != 0:
          table_pdf = cudf.concat(dataframes)
      return table_pdf
  
imports: import os
  import re
  import tempfile
  from collections import OrderedDict
  from os import listdir
  from os.path import isdir
  import glob
  from enum import IntEnum, unique
  import cudf
  import dask_cudf
  import numpy
  import pandas
  import pyblazing
  from blazingsql import DataType
  from pyhive import hive
  from Configuration import Settings
  from DemoTest.chronometer import Chronometer
label_desc: Use image node_id 18 for calling a global function with example usage: Read_tpch_files(column_names, files_dir, table, data_types) and returns: table_pdf