Changes in Analytics.

- UNSPECIFIED option added in the "AnalyzerOperationMode" enum as a best practice.
- In SparkStreamer, changed the thresholds parameter from optional to compulsory.

proto/analytics_frontend.proto

@@ -30,8 +30,9 @@ message AnalyzerId {
 }
 
 enum AnalyzerOperationMode {
-  ANALYZEROPERATIONMODE_BATCH     = 0;
-  ANALYZEROPERATIONMODE_STREAMING = 1;
+  ANALYZEROPERATIONMODE_UNSPECIFIED = 0;
+  ANALYZEROPERATIONMODE_BATCH       = 1;
+  ANALYZEROPERATIONMODE_STREAMING   = 2;
 }
 
 message Analyzer {

src/analytics/backend/service/SparkStreaming.py

@@ -73,7 +73,7 @@ def ApplyThresholds(aggregated_df, thresholds):
         )
     return aggregated_df
 
-def SparkStreamer(kpi_list, oper_list, window_size=None, win_slide_duration=None, thresholds=None, time_stamp_col=None):
+def SparkStreamer(kpi_list, oper_list, thresholds, window_size=None, win_slide_duration=None, time_stamp_col=None):
     """
     Method to perform Spark operation Kafka stream.
     NOTE: Kafka topic to be processesd should have atleast one row before initiating the spark session. 
@@ -86,7 +86,6 @@ def SparkStreamer(kpi_list, oper_list, window_size=None, win_slide_duration=None
     if window_size        is None: window_size        = "60 seconds"    # default
     if win_slide_duration is None: win_slide_duration = "30 seconds"    # default
     if time_stamp_col     is None: time_stamp_col     = "time_stamp"    # default
-    if thresholds         is None: thresholds         = {}              # No threshold will be applied
     
     try:
         # Read data from Kafka