def METHOD_NAME(
    mock_data_dir: mock.MagicMock,
    mock_bq: mock.MagicMock,
):
    datasource = CDCHIVData()
    datasource.write_to_bq('dataset', 'gcs_bucket', demographic="race", geographic="national")
    assert mock_bq.call_count == 2
    mock_bq_race_age_national, mock_bq_race_national = mock_bq.call_args_list
    # RACE/AGE NATIONAL TABLE NEEDED FOR AGE ADJUSTMENT
    (race_age_national_df, _dataset, race_age_table_name), _col_types = mock_bq_race_age_national
    assert race_age_table_name == "by_race_age_national"
    expected_race_age_national_df = pd.read_csv(GOLDEN_DATA['race_age_national'], dtype=EXP_DTYPE)
    assert_frame_equal(race_age_national_df, expected_race_age_national_df, check_like=True)
    # BY RACE NATIONAL
    (race_national_df, _dataset, race_table_name), _col_types = mock_bq_race_national
    assert race_table_name == "race_and_ethnicity_national_time_series"
    expected_race_national_df = pd.read_csv(GOLDEN_DATA['race_national'], dtype=EXP_DTYPE)
    assert_frame_equal(race_national_df, expected_race_national_df, check_like=True)