def METHOD_NAME(
    self,
    bigquery_client,
    storage_client,
    test_bucket,
    temporary_gcs_folder,
    project_id,
    temporary_dataset,
):
    non_incremental_sql_path = (
        TEST_DIR
        / "data"
        / "test_sql"
        / "moz-fx-data-test-project"
        / "test"
        / "non_incremental_query_v1"
        / "query.sql"
    )
    non_incremental_table = (
        f"{project_id}.{temporary_dataset}.non_incremental_query_v1"
    )
    date_partition = bigquery.table.TimePartitioning(field="d")
    job_config = bigquery.QueryJobConfig(
        destination=non_incremental_table, time_partitioning=date_partition
    )
    with open(non_incremental_sql_path) as query_stream:
        query = query_stream.read()
        query_job = bigquery_client.query(query, job_config=job_config)
        query_job.result()
    res = subprocess.run(
        (
            "./script/publish_public_data_json",
            "publish_json",
            "--query_file=" + str(non_incremental_sql_path),
            "--target_bucket=" + test_bucket.name,
            "--gcs_path=" + temporary_gcs_folder,
            "--public_project_id=" + project_id,
        )
    )
    assert res.returncode == 0
    gcp_path = (
        f"{temporary_gcs_folder}api/v1/tables/test/"
        + "non_incremental_query/v1/files/"
    )
    blobs = storage_client.list_blobs(test_bucket, prefix=gcp_path)
    blob_count = 0
    for blob in blobs:
        blob_count += 1
        content = json.loads(blob.download_as_string().decode("utf-8"))
        assert blob.content_type == "application/json"
        assert blob.content_encoding == "gzip"
        assert len(content) == 3
    assert blob_count == 1