code: def export_parallel():
      df = h2o.create_frame(rows=1000000, cols=100, seed=123)
  
      target_single = path.join(
          pyunit_utils.locate("results"), "export_file_single.csv"
      )
      target_parallel = path.join(
          pyunit_utils.locate("results"), "export_file_parallel.csv"
      )
  
      start = timer()
      h2o.export_file(df, target_single, parallel=False)
      end_single = timer()
      h2o.export_file(df, target_parallel, parallel=True)
      end_parallel = timer()
  
      single_duration = end_single - start
      parallel_duration = end_parallel - end_single
  
      print("Single-threaded export took {}".format(single_duration))
      print("Parallel export took {}".format(parallel_duration))
  
      assert filecmp.cmp(target_single, target_parallel, shallow=False)
      assert single_duration > parallel_duration
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from os import path
  from timeit import default_timer
  import filecmp
label_desc: Use image node_id 1 for calling a global function with example usage: export_parallel() without return types