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/operators/bigquery.py
or standard SQL (false).
    :type use_legacy_sql: bool
    :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud.
    :type gcp_conn_id: str
    :param bigquery_conn_id: (Deprecated) The connection ID used to connect to Google Cloud.
        This parameter has been deprecated. You should pass the gcp_conn_id parameter instead.
    :type bigquery_conn_id: str
    :param location: The geographic location of the job. See details at:
        https://cloud.google.com/bigquery/docs/locations#specifying_your_location
    :type location: str
    :param impersonation_chain: Optional service account to impersonate using short-term
        credentials, or chained list of accounts required to get the access_token
        of the last account in the list, which will be impersonated in the request.
        If set as a string, the account must grant the originating account
        the Service Account Token Creator IAM role.
        If set as a sequence, the identities from the list must grant
        Service Account Token Creator IAM role to the directly preceding identity, with first
        account from the list granting this role to the originating account (templated).
    :type impersonation_chain: Union[str, Sequence[str]]
    """
    template_fields = (
        'table',
        'gcp_conn_id',
        'sql1',
        'sql2',
        'impersonation_chain',
    )
    ui_color = BigQueryUIColors.CHECK.value
    @apply_defaults
    def __init__(