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
source_project, source_dataset, source_table = _split_tablename(
            table_input=source_project_dataset_table,
            default_project_id=self.project_id,
            var_name='source_project_dataset_table',
        )
        configuration = {
            'extract': {
                'sourceTable': {
                    'projectId': source_project,
                    'datasetId': source_dataset,
                    'tableId': source_table,
                },
                'compression': compression,
                'destinationUris': destination_cloud_storage_uris,
                'destinationFormat': export_format,
            }
        }  # 
        if labels:
            configuration['labels'] = labels
        if export_format == 'CSV':
            # 
            # 
            # 
            configuration['extract']['fieldDelimiter'] = field_delimiter
            configuration['extract']['printHeader'] = print_header
        job = self.insert_job(configuration=configuration, project_id=self.project_id)
        self.running_job_id = job.job_id
        return job.job_id
    # 
    def run_query(