def METHOD_NAME(setup, setup_hdfs):
    hdfs = setup_hdfs
    test_df = pd.DataFrame(
        {
            "a": np.arange(10).astype(np.int64, copy=False),
            "b": [f"s{i}" for i in range(10)],
            "c": np.random.rand(10),
        }
    )
    test_df2 = pd.DataFrame(
        {
            "a": np.arange(10).astype(np.int64, copy=False),
            "b": [f"s{i}" for i in range(10)],
            "c": np.random.rand(10),
        }
    )
    with hdfs.open(f"{TEST_DIR}/test.parquet", "wb", replication=1) as f:
        test_df.to_parquet(f, row_group_size=3)
    df = md.read_parquet(f"hdfs://localhost:8020{TEST_DIR}/test.parquet")
    res = df.to_pandas()
    pd.testing.assert_frame_equal(res, test_df)
    hdfs.mkdir(f"{TEST_DIR}/test_partitioned")
    with hdfs.open(
        f"{TEST_DIR}/test_partitioned/file1.parquet", "wb", replication=1
    ) as f:
        test_df.to_parquet(f, row_group_size=3)
    with hdfs.open(
        f"{TEST_DIR}/test_partitioned/file2.parquet", "wb", replication=1
    ) as f:
        test_df2.to_parquet(f, row_group_size=3)
    df = md.read_parquet(f"hdfs://localhost:8020{TEST_DIR}/test_partitioned")
    res = df.to_pandas()
    pd.testing.assert_frame_equal(res, pd.concat([test_df, test_df2]))