def save_data_view(self, role, party_id, data_info, mark=False): with DB.connection_context(): data_views = DataView.select().where( DataView.f_job_id == self.job_id, DataView.f_component_name == self.component_name, DataView.f_task_id == self.task_id, DataView.f_role == role, DataView.f_party_id == party_id) is_insert = True if mark and self.component_name == "upload_0": return if data_views: data_view = data_views[0] is_insert = False else: data_view = DataView() data_view.f_create_time = current_timestamp() data_view.f_job_id = self.job_id data_view.f_component_name = self.component_name data_view.f_task_id = self.task_id data_view.f_role = role data_view.f_party_id = party_id data_view.f_update_time = current_timestamp() for k, v in data_info.items(): if k in [ 'f_job_id', 'f_component_name', 'f_task_id', 'f_role', 'f_party_id' ] or v == getattr(DataView, k).default: continue setattr(data_view, k, v) if is_insert: data_view.save(force_insert=True) else: data_view.save() return data_view
def save_job_info(self, role, party_id, job_info, create=False): with DB.connection_context(): schedule_logger(self.job_id).info('save {} {} job: {}'.format( role, party_id, job_info)) jobs = Job.select().where(Job.f_job_id == self.job_id, Job.f_role == role, Job.f_party_id == party_id) is_insert = True if jobs: job = jobs[0] is_insert = False if job.f_status == JobStatus.TIMEOUT: return None elif create: job = Job() job.f_create_time = current_timestamp() else: return None job.f_job_id = self.job_id job.f_role = role job.f_party_id = party_id if 'f_status' in job_info: if job.f_status in [JobStatus.COMPLETE, JobStatus.FAILED]: # Termination status cannot be updated # TODO: return if (job_info['f_status'] in [ JobStatus.FAILED, JobStatus.TIMEOUT ]) and (not job.f_end_time): if not job.f_start_time: return job_info['f_end_time'] = current_timestamp() job_info['f_elapsed'] = job_info[ 'f_end_time'] - job.f_start_time job_info['f_update_time'] = current_timestamp() if (job_info['f_status'] in [ JobStatus.FAILED, JobStatus.TIMEOUT, JobStatus.CANCELED, JobStatus.COMPLETE ]): job_info['f_tag'] = 'job_end' update_fields = [] for k, v in job_info.items(): try: if k in ['f_job_id', 'f_role', 'f_party_id' ] or v == getattr(Job, k).default: continue setattr(job, k, v) update_fields.append(getattr(Job, k)) except: pass if is_insert: job.save(force_insert=True) else: job.save(only=update_fields)
def insert_data_to_db(self, metric_namespace: str, metric_name: str, data_type: int, kv, job_level=False): with DB.connection_context(): try: tracking_metric = TrackingMetric.model(table_index=self.job_id) tracking_metric.f_job_id = self.job_id tracking_metric.f_component_name = self.component_name if not job_level else 'dag' tracking_metric.f_task_id = self.task_id tracking_metric.f_role = self.role tracking_metric.f_party_id = self.party_id tracking_metric.f_metric_namespace = metric_namespace tracking_metric.f_metric_name = metric_name tracking_metric.f_type = data_type default_db_source = tracking_metric.to_json() tracking_metric_data_source = [] for k, v in kv: db_source = default_db_source.copy() db_source['f_key'] = serialize_b64(k) db_source['f_value'] = serialize_b64(v) db_source['f_create_time'] = current_timestamp() tracking_metric_data_source.append(db_source) self.bulk_insert_model_data( TrackingMetric.model(table_index=self.get_table_index()), tracking_metric_data_source) except Exception as e: schedule_logger(self.job_id).exception(e)
def update_job_progress(job_id, dag, current_task_id): role, party_id = query_job_info(job_id) component_count = len( dag.get_dependency(role=role, party_id=int(party_id))['component_list']) success_count = success_task_count(job_id=job_id) job = Job() job.f_progress = float(success_count) / component_count * 100 job.f_update_time = current_timestamp() job.f_current_tasks = json_dumps([current_task_id]) return job
def save_task(self, role, party_id, task_info): with DB.connection_context(): tasks = Task.select().where( Task.f_job_id == self.job_id, Task.f_component_name == self.component_name, Task.f_task_id == self.task_id, Task.f_role == role, Task.f_party_id == party_id) is_insert = True if tasks: task = tasks[0] is_insert = False else: task = Task() task.f_create_time = current_timestamp() task.f_job_id = self.job_id task.f_component_name = self.component_name task.f_task_id = self.task_id task.f_role = role task.f_party_id = party_id if 'f_status' in task_info: if task.f_status in [TaskStatus.COMPLETE, TaskStatus.FAILED]: # Termination status cannot be updated # TODO: pass for k, v in task_info.items(): try: if k in [ 'f_job_id', 'f_component_name', 'f_task_id', 'f_role', 'f_party_id' ] or v == getattr(Task, k).default: continue except: pass setattr(task, k, v) if is_insert: task.save(force_insert=True) else: task.save() return task
def save(self, *args, **kwargs): if hasattr(self, "update_date"): self.update_date = datetime.datetime.now() if hasattr(self, "update_time"): self.update_time = current_timestamp() super(DataBaseModel, self).save(*args, **kwargs)
def submit_job(job_data, job_id=None): if not job_id: job_id = generate_job_id() schedule_logger(job_id).info('submit job, job_id {}, body {}'.format(job_id, job_data)) job_dsl = job_data.get('job_dsl', {}) job_runtime_conf = job_data.get('job_runtime_conf', {}) job_utils.check_pipeline_job_runtime_conf(job_runtime_conf) job_parameters = job_runtime_conf['job_parameters'] job_initiator = job_runtime_conf['initiator'] job_type = job_parameters.get('job_type', '') if job_type != 'predict': # generate job model info job_parameters['model_id'] = '#'.join([dtable_utils.all_party_key(job_runtime_conf['role']), 'model']) job_parameters['model_version'] = job_id train_runtime_conf = {} else: detect_utils.check_config(job_parameters, ['model_id', 'model_version']) # get inference dsl from pipeline model as job dsl job_tracker = Tracking(job_id=job_id, role=job_initiator['role'], party_id=job_initiator['party_id'], model_id=job_parameters['model_id'], model_version=job_parameters['model_version']) pipeline_model = job_tracker.get_output_model('pipeline') job_dsl = json_loads(pipeline_model['Pipeline'].inference_dsl) train_runtime_conf = json_loads(pipeline_model['Pipeline'].train_runtime_conf) path_dict = save_job_conf(job_id=job_id, job_dsl=job_dsl, job_runtime_conf=job_runtime_conf, train_runtime_conf=train_runtime_conf, pipeline_dsl=None) job = Job() job.f_job_id = job_id job.f_roles = json_dumps(job_runtime_conf['role']) job.f_work_mode = job_parameters['work_mode'] job.f_initiator_party_id = job_initiator['party_id'] job.f_dsl = json_dumps(job_dsl) job.f_runtime_conf = json_dumps(job_runtime_conf) job.f_train_runtime_conf = json_dumps(train_runtime_conf) job.f_run_ip = '' job.f_status = JobStatus.WAITING job.f_progress = 0 job.f_create_time = current_timestamp() initiator_role = job_initiator['role'] initiator_party_id = job_initiator['party_id'] if initiator_party_id not in job_runtime_conf['role'][initiator_role]: schedule_logger(job_id).info("initiator party id error:{}".format(initiator_party_id)) raise Exception("initiator party id error {}".format(initiator_party_id)) get_job_dsl_parser(dsl=job_dsl, runtime_conf=job_runtime_conf, train_runtime_conf=train_runtime_conf) TaskScheduler.distribute_job(job=job, roles=job_runtime_conf['role'], job_initiator=job_initiator) # push into queue job_event = job_utils.job_event(job_id, initiator_role, initiator_party_id) try: RuntimeConfig.JOB_QUEUE.put_event(job_event) except Exception as e: raise Exception('push job into queue failed') schedule_logger(job_id).info( 'submit job successfully, job id is {}, model id is {}'.format(job.f_job_id, job_parameters['model_id'])) board_url = BOARD_DASHBOARD_URL.format(job_id, job_initiator['role'], job_initiator['party_id']) logs_directory = get_job_log_directory(job_id) return job_id, path_dict['job_dsl_path'], path_dict['job_runtime_conf_path'], logs_directory, \ {'model_id': job_parameters['model_id'],'model_version': job_parameters['model_version']}, board_url