Enriched property files to also contain configuration parameters which were...

Enriched property files to also contain configuration parameters which were expected as environmental variables
Exclusively rely on property file values to connect to InfluxDB for historical metric values
Improved the arrangement of State class fields
Improved prediction logs

morphemic-forecasting-exponentialsmoothing/src/r_predictors/prediction_configuration-windows.properties

+#AMQ_HOST=ems
+#AMQ_USER=aaa
+#AMQ_PASSWORD=111
+#AMQ_PORT_BROKER=61610
+APP_NAME=default_application
+METHOD=exponential_smoothing
+# in file -> METHOD=Holt-Winters
+#DATA_PATH=./
+INFLUXDB_HOSTNAME=ui-influxdb
+INFLUXDB_PORT=8086
+INFLUXDB_USERNAME=morphemic
+INFLUXDB_PASSWORD=password
+
 broker_address=localhost
 broker_port=61610
 broker_username=morphemic

morphemic-forecasting-exponentialsmoothing/src/r_predictors/prediction_configuration.properties

+#AMQ_HOST=ems
+#AMQ_USER=aaa
+#AMQ_PASSWORD=111
+#AMQ_PORT_BROKER=61610
+APP_NAME=default_application
+METHOD=exponential_smoothing
+# in file -> METHOD=Holt-Winters
+#DATA_PATH=./
+INFLUXDB_HOSTNAME=ui-influxdb
+INFLUXDB_PORT=8086
+INFLUXDB_USERNAME=morphemic
+INFLUXDB_PASSWORD=password
+
 broker_address=localhost
 broker_port=61610
 broker_username=morphemic

morphemic-forecasting-exponentialsmoothing/src/runtime/Predictor.py

@@ -135,7 +135,7 @@ def calculate_and_publish_predictions(prediction_horizon,maximum_time_required_f
 
         #Below we subtract one reconfiguration interval, as we cannot send a prediction for a time point later than one prediction_horizon interval
         wait_time = State.next_prediction_time - prediction_horizon - time.time()
-        print("Waiting for "+str((int(wait_time*100))/100)+" seconds")
+        print("Waiting for "+str((int(wait_time*100))/100)+" seconds from time "+str(time.time()))
         if (wait_time>0):
             time.sleep(wait_time)
             if(not Listener.start_forecasting):
@@ -241,7 +241,7 @@ class Listener(messaging.listener.MorphemicListener):
                 print("Problem while retrieving epoch start and/or prediction_horizon")
                 return
 
-            maximum_time_required_for_prediction = State.prediction_processing_time_safety_margin_seconds #initialization, assuming 20 seconds processing time to derive a first prediction
+            maximum_time_required_for_prediction = State.prediction_processing_time_safety_margin_seconds #initialization, assuming X seconds processing time to derive a first prediction
             if ((self.prediction_thread is None) or (not self.prediction_thread.is_alive())):
                 self.prediction_thread = threading.Thread(target = calculate_and_publish_predictions, args =[prediction_horizon,maximum_time_required_for_prediction])
                 self.prediction_thread.start()

morphemic-forecasting-exponentialsmoothing/src/runtime/operational_status/State.py

@@ -5,28 +5,40 @@ class State:
     """
     Fail-safe default values introduced below
     """
+
+    #Used to create the dataset from the InfluxDB
+    application_name = "default_application"
+    influxdb_dbname = "morphemic"
+    influxdb_password = "password"
+    influxdb_username = "morphemic"
+    influxdb_port = 8086
+    influxdb_hostname = "ui-influxdb"
+    path_to_datasets = "./datasets"
+    dataset_file_name = "exponential_smoothing_dataset.csv"
+    number_of_days_to_use_data_from = 365
+
+    #Forecaster variables
     metrics_to_predict = []
     epoch_start = 0
     next_prediction_time = 0
     previous_prediction = None
     configuration_file_location="/home/src/r_predictors/prediction_configuration.properties"
     configuration_details = Properties()
-    broker_address = "localhost"
-    broker_port = 61610
-    broker_username = "morphemic"
-    broker_password = "morphemic"
-    path_to_datasets = "./datasets"
-    dataset_file_name = None
-    number_of_days_to_use_data_from = 365
-
-    prediction_processing_time_safety_margin_seconds = None
-    connection = None
+    prediction_processing_time_safety_margin_seconds = 20
     disconnected = True
     disconnection_handler = threading.Condition()
     initial_metric_list_received = False
     testing_prediction_functionality = False
 
 
+    #Connection details
+    connection = None
+    broker_address = "localhost"
+    broker_port = 61610
+    broker_username = "morphemic"
+    broker_password = "morphemic"
+
+
     @staticmethod
     def check_stale_connection():
         return (not State.connection.conn.is_connected())

morphemic-forecasting-exponentialsmoothing/src/runtime/utilities/Utilities.py

@@ -20,6 +20,13 @@ class Utilities:
             State.broker_username = State.configuration_details.get("broker_username").data
             State.broker_password = State.configuration_details.get("broker_password").data
 
+            State.influxdb_hostname = State.configuration_details.get("INFLUXDB_HOSTNAME").data
+            State.influxdb_port = int(State.configuration_details.get("INFLUXDB_PORT").data)
+            State.influxdb_username = State.configuration_details.get("INFLUXDB_USERNAME").data
+            State.influxdb_password = State.configuration_details.get("INFLUXDB_PASSWORD").data
+            State.influxdb_dbname = State.configuration_details.get("INFLUXDB_DBNAME").data
+            State.influxdb_org = State.configuration_details.get("INFLUXDB_ORG").data
+            State.application_name = State.configuration_details.get("APP_NAME").data
         #This method accesses influx db to retrieve the most recent metric values.
     @staticmethod
     def update_monitoring_data():
@@ -28,6 +35,8 @@ class Utilities:
         print("Starting dataset creation process...")
 
         try:
+            """
+            Deprecated functionality to retrieve dataset creation details. Relevant functionality moved inside the load configuration method
             influxdb_hostname = os.environ.get("INFLUXDB_HOSTNAME","localhost")
             influxdb_port = int(os.environ.get("INFLUXDB_PORT","8086"))
             influxdb_username = os.environ.get("INFLUXDB_USERNAME","morphemic")
@@ -35,20 +44,21 @@ class Utilities:
             influxdb_dbname = os.environ.get("INFLUXDB_DBNAME","morphemic")
             influxdb_org = os.environ.get("INFLUXDB_ORG","morphemic")
             application_name = "default_application"
+            """
 
             #_start_collection = None # '30m','1h', '2d', #None for everything
             _start_collection = str(State.number_of_days_to_use_data_from)+"d" # '30m','1h', '2d', None for everything
             pathlib.Path(State.path_to_datasets).mkdir(parents=True, exist_ok=True)
             configs = {
-                'hostname': influxdb_hostname,
-                'port': influxdb_port,
-                'username': influxdb_username,
-                'password': influxdb_password,
-                'dbname': influxdb_dbname,
+                'hostname': State.influxdb_hostname,
+                'port': State.influxdb_port,
+                'username': State.influxdb_username,
+                'password': State.influxdb_password,
+                'dbname': State.influxdb_dbname,
                 'path_dataset': State.path_to_datasets
             }
 
-            datasetmaker = DatasetMaker(application_name,_start_collection,configs)
+            datasetmaker = DatasetMaker(State.application_name,_start_collection,configs)
             response = datasetmaker.make()
 
             print ("Dataset creation process finished with response "+str(response))

morphemic-forecasting-exponentialsmoothing/src/test/test_scheduler.py

@@ -28,6 +28,6 @@ if __name__=="__main__":
 
         #Below we subtract one reconfiguration interval, as we cannot send a prediction for a time point later than one prediction_horizon interval
         wait_time = next_prediction_time - horizon - time.time()
-        print("Waiting for "+str((int(wait_time*100))/100)+" seconds")
+        print("Waiting for "+str((int(wait_time*100))/100)+" seconds from time "+str(time.time()))
         if (wait_time>0):
           time.sleep(wait_time)
\ No newline at end of file