BigQuery supports clustering for both partitioned and non-partitioned tables.

Reference: [https://cloud.google.com/bigquery/docs/clustered-tables](https://cloud.google.com/bigquery/docs/clustered-tables)
airflow/providers/google/cloud/hooks/bigquery.py
"""
        Executes a BigQuery extract command to copy data from BigQuery to
        Google Cloud Storage. See here:
        https://cloud.google.com/bigquery/docs/reference/v2/jobs
        For more details about these parameters.
        :param source_project_dataset_table: The dotted ``<dataset>.<table>``
            BigQuery table to use as the source data.
        :type source_project_dataset_table: str
        :param destination_cloud_storage_uris: The destination Google Cloud
            Storage URI (e.g. gs://some-bucket/some-file.txt). Follows
            convention defined here:
            https://cloud.google.com/bigquery/exporting-data-from-bigquery#exportingmultiple
        :type destination_cloud_storage_uris: list
        :param compression: Type of compression to use.
        :type compression: str
        :param export_format: File format to export.
        :type export_format: str
        :param field_delimiter: The delimiter to use when extracting to a CSV.
        :type field_delimiter: str
        :param print_header: Whether to print a header for a CSV file extract.
        :type print_header: bool
        :param labels: a dictionary containing labels for the job/query,
            passed to BigQuery
        :type labels: dict
        """
        warnings.warn(
            "This method is deprecated. Please use `BigQueryHook.insert_job` method.", DeprecationWarning
        )
        if not self.project_id:
            raise ValueError("The project_id should be set")