code: def compare_test_results(
      pdf1,
      pdf2,
      acceptable_difference,
      use_percentage,
      engine,
      comparing=True,
  ):
      """
      Compare values, number of rows, columns, and column names
  
      ----------
      pdf1 : blazing results (pandas dataframe)
      pdf2: drill/spark results (pandas dataframe)
      acceptable_difference: This parameter is related to the acceptable difference beetween values
      from blazingsql results and drill/spark results.
      use_percentage: (True/False) to indicate if the results will be compared by percentage or difference.
      comparing: Parameter to indicate if the results from blazingsql will be compared with the results from drill or spark
      """
  
      compareResults = True
      error_message = ""
      stringResult = ""
      columnNamesComparison = True
      resultComparisson = ""
  
      if "compare_result_values" in Settings.data["RunSettings"]:
          compareResults = Settings.data["RunSettings"][
              "compare_result_values"
          ]
  
      # For dateTest (CURRENT_DATE, CURRENT_TIME, CURRENT_TIMESTAMP)
      if not comparing:
          compareResults = False
  
      if compareResults:
          columnNamesComparison = compare_column_names(pdf1, pdf2)
          if columnNamesComparison is not True:
              error_message = "Column names are not the same"
  
          resultComparisson = compare_result_values(
              pdf1, pdf2, acceptable_difference, use_percentage, engine
          )
          if resultComparisson != "Success":
              error_message = resultComparisson[6:]
  
          stringResult = resultComparisson
          if (
              resultComparisson != "Success"
              or columnNamesComparison is False
          ):
              stringResult = "Fail"
      else:
          stringResult = "Success"
  
      return (
          error_message,
          stringResult,
          columnNamesComparison,
          resultComparisson,
      )
  
imports: import json
  import logging
  import os
  import re
  import time
  import yaml
  import numpy
  import pandas
  import blazingsql
  from blazingsql import DataType
  from BlazingLogging import loggingHandler
  from Configuration import ExecutionMode
  from Configuration import Settings
  from DataBase import createSchema
label_desc: Use image node_id 15 for calling a global function with example usage: compare_test_results(pdf1, pdf2, acceptable_difference, use_percentage, engine, comparing) and returns: error_message,  stringResult,  columnNamesComparison,  resultComparisson