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
:param max_results: The maximum number of results to return in a single response page.
            Leverage the page tokens to iterate through the entire collection.
        :type max_results: int
        :return: List of tables associated with the dataset
        """
        warnings.warn("This method is deprecated. Please use ``get_dataset_tables``.", DeprecationWarning)
        project_id = project_id or self.project_id
        tables = self.get_client().list_tables(
            dataset=DatasetReference(project=project_id, dataset_id=dataset_id),
            max_results=max_results,
        )
        if table_prefix:
            result = [t.reference.to_api_repr() for t in tables if t.table_id.startswith(table_prefix)]
        else:
            result = [t.reference.to_api_repr() for t in tables]
        self.log.info("%s tables found", len(result))
        return result
    @GoogleBaseHook.fallback_to_default_project_id
    def get_datasets_list(
        self,
        project_id: Optional[str] = None,
        include_all: bool = False,
        filter_: Optional[str] = None,
        max_results: Optional[int] = None,
        page_token: Optional[str] = None,
        retry: Retry = DEFAULT_RETRY,
    ) -> List[DatasetListItem]:
        """
        Method returns full list of BigQuery datasets in the current project
        For more information, see: