def METHOD_NAME(spark_dataset):
    """Test random splitter for Spark dataframes.
    NOTE: some split results may not match exactly with the ratios, which may
    be owing to the limited number of rows in the testing data. A approximate
    match with certain level of tolerance is therefore used instead for tests."""
    splits = spark_random_split(spark_dataset, ratio=RATIOS[0], seed=SEED)
    assert splits[0].count() / NUM_ROWS == pytest.approx(RATIOS[0], abs=TOL)
    assert splits[1].count() / NUM_ROWS == pytest.approx(1 - RATIOS[0], abs=TOL)
    splits = spark_random_split(spark_dataset, ratio=RATIOS, seed=SEED)
    assert splits[0].count() / NUM_ROWS == pytest.approx(RATIOS[0], abs=TOL)
    assert splits[1].count() / NUM_ROWS == pytest.approx(RATIOS[1], abs=TOL)
    assert splits[2].count() / NUM_ROWS == pytest.approx(RATIOS[2], abs=TOL)