**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
@classmethod
    def setup_class(cls):
        super().setup_class()
        cls.extra_links_expected_calls_base = [
            call.ti.xcom_push(execution_date=None, key="conf", value=DATAPROC_CLUSTER_CONF_EXPECTED)
        ]
    def test_deprecation_warning(self):
        with pytest.warns(AirflowProviderDeprecationWarning) as warnings:
            DataprocScaleClusterOperator(task_id=TASK_ID, cluster_name=CLUSTER_NAME, project_id=GCP_PROJECT)
        assert_warning("DataprocUpdateClusterOperator", warnings)
    @mock.patch(DATAPROC_PATH.format("DataprocHook"))
    def test_execute(self, mock_hook):
        self.extra_links_manager_mock.attach_mock(mock_hook, "hook")
        mock_hook.return_value.update_cluster.result.return_value = None
        cluster_update = {
            "config": {"worker_config": {"num_instances": 3}, "secondary_worker_config": {"num_instances": 4}}
        }
        update_cluster_args = {
            "project_id": GCP_PROJECT,
            "region": GCP_REGION,
            "cluster_name": CLUSTER_NAME,
            "cluster": cluster_update,
            "graceful_decommission_timeout": {"seconds": 600},
            "update_mask": UPDATE_MASK,
        }
        expected_calls = [
            *self.extra_links_expected_calls_base,