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)