import logging import es_api.object as ob import es_api.machine_learning.anomaly_detection as mlad import es_properties.index as es_idx_prop import es_properties.machine_learning as es_ml_prop logging.basicConfig(level=logging.DEBUG) if __name__ == "__main__": ctx = { "analy_es_object": None, "index_properties": es_idx_prop.twaren_device, "mlad_properties": es_ml_prop.anomaly_detect_twaren_device, "mlad_result": None } ob.prepare_all(ctx) and \ mlad.process(ctx) # ob.prepare_all(ctx) and \ # mlad.get_resutl_process(ctx)
import es_api.object as ob import es_api.index as idx import es_api.search as es_search import es_api.bulk as es_bulk import es_properties.index as es_idx_prop import es_properties.search as es_search_prop logging.basicConfig(level=logging.DEBUG) if __name__ == "__main__": ctx = { "data_es_object": None, "analy_es_object": None, "is_created_new_index": None, "index_properties": es_idx_prop.twaren_device, "search_properties": None, "search_result": None, "override_index_name": "twaren_asr_device" } ctx = ob.prepare_all(ctx) and \ idx.create_process(ctx) for day_range in es_search.time_range_from_now_props_list("d", 3): search_properties = es_search.replace_range_prop( es_search_prop.twaren_asr_device, day_range) ctx["search_properties"] = search_properties es_search.scan(ctx) and \ es_bulk.bulk_from_scan(ctx)
# import logging import es_api.object as ob import es_properties.machine_learning as es_ml_prop import es_api.machine_learning.forecast as fc_es import mysql_api.forecast_data as fc_sql # logging.basicConfig(level=logging.DEBUG) if __name__ == "__main__": for ml_job_id, metric in es_ml_prop.ML_JOB_METRIC_MAPPING.items(): ctx = { "analy_es_object": None, "ml_job_id": ml_job_id, "forecast": { "metric": metric, "job_id": None, "job_time": None } } ob.prepare_all(ctx) and \ fc_es.forecast_job(ctx) and \ fc_sql.insert_forecast_record(ctx) and \ print(ctx)
return ctx if __name__ == "__main__": for ml_job_id, metric in es_ml_prop.ML_JOB_METRIC_MAPPING.items(): for traffic_id, device_keyword in TRAFFIC_ID_DEVICE_KEYWORD_MAPPING.items( ): device_searcher = ".*" + device_keyword + ".*" ctx = { "analy_es_object": None, "ml_job_id": ml_job_id, "forecast": { "metric": metric, "job_id": "", "device_searcher": device_searcher, "result": None }, "inms_traffic": { "id": traffic_id, "upper_bound": "" } } ob.prepare_all(ctx) and \ fc_local_sql.query_forecast_job_id(ctx) and \ fc_es.search_forecast_data(ctx) and \ extract_forecast_data_to_inms(ctx) and \ inms_netflow_sql.update_traffic_bound(ctx) and \ print(ctx)
import es_api.object as ob import es_api.index as idx import es_api.machine_learning.anomaly_detection as mlad import es_api.search as es_search import es_api.bulk as es_bulk import es_properties.index as es_idx_prop import es_properties.machine_learning as es_ml_prop import es_properties.search as es_search_prop logging.basicConfig(level=logging.DEBUG) if __name__ == "__main__": while True: ctx = { "data_es_object": None, "analy_es_object": None, "is_created_new_index": None, "index_properties": es_idx_prop.twaren_device, "mlad_properties": es_ml_prop.anomaly_detect_twaren_device, "search_properties": es_search_prop.twaren_asr_device, "search_result": None, "mlad_result": None } ob.prepare_all(ctx) and \ idx.create_process(ctx) and \ es_search.scan(ctx) and \ es_bulk.bulk_from_scan(ctx) and \ time.sleep(300)
import logging import es_api.object as ob import es_api.index as idx import es_api.bulk as es_bulk import es_properties.index as es_idx_prop import mysql_api.interfaces_traffic_data as sql_traffic_data logging.basicConfig(level=logging.DEBUG) if __name__ == "__main__": ctx = { "sql_data": None, "analy_es_object": None, "is_created_new_index": None, "index_properties": es_idx_prop.twaren_netflow, "search_result": sql_traffic_data.query_netflow(), "mlad_properties": None, "mlad_result": None } ob.prepare_all(ctx) and \ idx.create_process(ctx) and \ es_bulk.bulk_from_mysql(ctx) and\ print(ctx)