def _execute_subjob(self, build_id, subjob_id, executor, atomic_commands):
        subjob_event_data = {'build_id': build_id, 'subjob_id': subjob_id, 'executor_id': executor.id}

        analytics.record_event(analytics.SUBJOB_EXECUTION_START, **subjob_event_data)
        results_file = executor.execute_subjob(build_id, subjob_id, atomic_commands, self._base_executor_index)
        analytics.record_event(analytics.SUBJOB_EXECUTION_FINISH, **subjob_event_data)

        results_url = self._master_api.url('build', build_id, 'subjob', subjob_id, 'result')
        data = {
            'slave': '{}:{}'.format(self.host, self.port),
            'metric_data': {'executor_id': executor.id},
        }
        files = {'file': ('payload', open(results_file, 'rb'), 'application/x-compressed')}

        self._idle_executors.put(executor)  # work is done; mark executor as idle
        self._network.post(results_url, data=data, files=files)  # todo: check return code

        self._logger.info('Build {}, Subjob {} completed and sent results to master.', build_id, subjob_id)
This is the method for executing a subjob asynchronously. This performs the work required by executing the
dataset/ETHPy150Open box/ClusterRunner/app/slave/cluster_slave.py/ClusterSlave._execute_subjob