code: def test_filters_at_row_group_level(tmpdir):
      tmp_path = str(tmpdir)
      df = pd.DataFrame({"x": range(10), "y": list("aabbccddee")})
      ddf = dd.from_pandas(df, npartitions=5)
      assert ddf.npartitions == 5
  
      ddf.to_parquet(tmp_path, engine="pyarrow", row_group_size=10 / 5)
  
      a = dask_cudf.read_parquet(
          tmp_path, filters=[("x", "==", 1)], split_row_groups=True
      )
      assert a.npartitions == 1
      assert (a.shape[0] == 1).compute()
  
      ddf.to_parquet(tmp_path, engine="pyarrow", row_group_size=1)
  
      b = dask_cudf.read_parquet(
          tmp_path, filters=[("x", "==", 1)], split_row_groups=True
      )
      assert b.npartitions == 1
      assert (b.shape[0] == 1).compute()
  
imports: import glob
  import math
  import os
  import numpy
  import pandas
  import pytest
  import dask
  from dask import dataframe
  from dask.utils import natural_sort_key
  import cudf
  import dask_cudf
label_desc: Use image node_id 15 for calling a global function with example usage: test_filters_at_row_group_level(tmpdir) without return types