**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.request_id = request_id
        self.retry = retry
        self.timeout = timeout
        self.metadata = metadata
        self.gcp_conn_id = gcp_conn_id
        self.impersonation_chain = impersonation_chain
        self.deferrable = deferrable
        self.polling_interval_seconds = polling_interval_seconds
    def execute(self, context: Context) -> None:
        hook = DataprocHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
        operation = self._delete_cluster(hook)
        if not self.deferrable:
            hook.wait_for_operation(timeout=self.timeout, result_retry=self.retry, operation=operation)
            self.log.info("Cluster deleted.")
        else:
            end_time: float = time.time() + self.timeout
            self.defer(
                trigger=DataprocDeleteClusterTrigger(
                    gcp_conn_id=self.gcp_conn_id,
                    project_id=self.project_id,
                    region=self.region,
                    cluster_name=self.cluster_name,
                    end_time=end_time,
                    metadata=self.metadata,
                    impersonation_chain=self.impersonation_chain,
                    polling_interval_seconds=self.polling_interval_seconds,
                ),
                method_name="execute_complete",
            )
    def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> Any: