**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
retry=self.retry,
            timeout=self.timeout,
            metadata=self.metadata,
        )
        if not self.deferrable:
            hook.wait_for_operation(timeout=self.timeout, result_retry=self.retry, operation=operation)
        else:
            self.defer(
                trigger=DataprocClusterTrigger(
                    cluster_name=self.cluster_name,
                    project_id=self.project_id,
                    region=self.region,
                    gcp_conn_id=self.gcp_conn_id,
                    impersonation_chain=self.impersonation_chain,
                    polling_interval_seconds=self.polling_interval_seconds,
                ),
                method_name="execute_complete",
            )
        self.log.info("Updated %s cluster.", self.cluster_name)
    def execute_complete(self, context: Context, event: dict[str, Any]) -> Any:
        """
        Callback for when the trigger fires - returns immediately.
        Relies on trigger to throw an exception, otherwise it assumes execution was successful.
        """
        cluster_state = event["cluster_state"]
        cluster_name = event["cluster_name"]
        if cluster_state == ClusterStatus.State.ERROR:
            raise AirflowException(f"Cluster is in ERROR state:\n{cluster_name}")
        self.log.info("%s completed successfully.", self.task_id)
class DataprocCreateBatchOperator(GoogleCloudBaseOperator):