Segments from data puller not in db #350 (#351)

* improve logging

* set constant window size

* fix

* improve logging, save detected segments from push\pull process

* fix

* fix

* fix according review

* save segemnts, improve bucket managing in analytics

analytics/analytics/detectors/pattern_detector.py

@@ -36,9 +36,9 @@ class PatternDetector(Detector):
         self.analytic_unit_id = analytic_unit_id
         self.pattern_type = pattern_type
         self.model = resolve_model_by_pattern(self.pattern_type)
-        self.window_size = 150
+        self.max_window_size = 150
+        self.window_size = 0
         self.bucket = DataBucket()
-        self.bucket_full_reported = False
 
     def train(self, dataframe: pd.DataFrame, segments: list, cache: Optional[models.ModelCache]) -> models.ModelCache:
         # TODO: pass only part of dataframe that has segments
@@ -66,19 +66,13 @@ class PatternDetector(Detector):
 
     def recieve_data(self, data: pd.DataFrame, cache: Optional[ModelCache]) -> Optional[dict]:
         self.bucket.receive_data(data.dropna())
+        if cache and self.window_size == 0:
+            self.window_size = cache['WINDOW_SIZE']
 
         if len(self.bucket.data) >= self.window_size and cache != None:
-            if not self.bucket_full_reported:
-                logging.debug('{} unit`s bucket full, run detect'.format(self.analytic_unit_id))
-                self.bucket_full_reported = True
-
             res = self.detect(self.bucket.data, cache)
-
-            excess_data = len(self.bucket.data) - self.window_size
+            excess_data = len(self.bucket.data) - self.max_window_size
             self.bucket.drop_data(excess_data)
             return res
-        else:
-            filling = len(self.bucket.data)*100 / self.window_size
-            logging.debug('bucket for {} {}% full'.format(self.analytic_unit_id, filling))
         
         return None

server/src/controllers/analytics_controller.ts

@@ -44,8 +44,14 @@ function onTaskResult(taskResult: TaskResult) {
   }
 }
 
-function onDetect(detectionResult: DetectionResult) {
-  processDetectionResult(detectionResult.analyticUnitId, detectionResult);
+async function onDetect(detectionResult: DetectionResult) {
+  let id = detectionResult.analyticUnitId;
+  let payload = await processDetectionResult(id, detectionResult);
+  await Promise.all([
+    Segment.insertSegments(payload.segments),
+    AnalyticUnitCache.setData(id, payload.cache),
+    AnalyticUnit.setDetectionTime(id, payload.lastDetectionTime),
+  ]);
 }
 
 async function onMessage(message: AnalyticsMessage) {
@@ -58,7 +64,7 @@ async function onMessage(message: AnalyticsMessage) {
   }
 
   if(message.method === AnalyticsMessageMethod.DETECT) {
-    onDetect(message.payload.payload);
+    await onDetect(message.payload.payload);
     methodResolved = true;
   }
 

server/src/services/data_puller.ts

@@ -43,9 +43,7 @@ export class DataPuller {
       panelUrl = unit.panelUrl;
     }
 
-    let startTime = Date.now();
     let data = queryByMetric(unit.metric, panelUrl, from, to, HASTIC_API_KEY);
-    console.log(`data puller: query took ${Date.now() - startTime}ms for unit id ${unit.id}`);
     return data;
     
   }