**Description**

This operator should cancel running workflow template `on_kill`. This option probably should be configurable because of request_id prameter in a job definition: https://googleapis.dev/python/dataproc/latest/gapic/v1/api.html#google.cloud.dataproc_v1.WorkflowTemplateServiceClient.instantiate_inline_workflow_template
https://googleapis.dev/python/dataproc/latest/gapic/v1/api.html#google.cloud.dataproc_v1.WorkflowTemplateServiceClient.instantiate_workflow_template

Note this will have to cancle the Google Long Running Operation for the workflow template (which will in turn cancel all children jobs and clean up relevant cluster).

**Use case / motivation**

Remove dangling workflow templates

**Related Issues**
#10381
#6371
self,
        *,
        cluster_name: str,
        project_id: str | None = None,
        region: str = "global",
        num_workers: int = 2,
        num_preemptible_workers: int = 0,
        graceful_decommission_timeout: str | None = None,
        gcp_conn_id: str = "google_cloud_default",
        impersonation_chain: str | Sequence[str] | None = None,
        **kwargs,
    ) -> None:
        super().__init__(**kwargs)
        self.project_id = project_id
        self.region = region
        self.cluster_name = cluster_name
        self.num_workers = num_workers
        self.num_preemptible_workers = num_preemptible_workers
        self.graceful_decommission_timeout = graceful_decommission_timeout
        self.gcp_conn_id = gcp_conn_id
        self.impersonation_chain = impersonation_chain
        
        warnings.warn(
            f"The `{type(self).__name__}` operator is deprecated, "
            "please use `DataprocUpdateClusterOperator` instead.",
            AirflowProviderDeprecationWarning,
            stacklevel=1,
        )
    def _build_scale_cluster_data(self) -> dict: