From e233b5ea23e79bf74726e577f623069aa26bee59 Mon Sep 17 00:00:00 2001
From: Piao <guangyuan.piao@dell.com>
Date: Fri, 16 Aug 2024 10:03:23 +0100
Subject: [PATCH] update to run everyday

---
 server/cronjob/prediction-cron |  2 +-
 server/cronjob/prediction.py   | 23 ++++++++++++++---------
 2 files changed, 15 insertions(+), 10 deletions(-)

diff --git a/server/cronjob/prediction-cron b/server/cronjob/prediction-cron
index 7c8c649..89d28e5 100644
--- a/server/cronjob/prediction-cron
+++ b/server/cronjob/prediction-cron
@@ -1 +1 @@
-*/10 * * * * root /usr/bin/python /usr/src/app/cronjob/prediction.py >> /var/log/cron.log 2>&1
+0 0 * * * root /usr/bin/python /usr/src/app/cronjob/prediction.py >> /var/log/cron.log 2>&1
diff --git a/server/cronjob/prediction.py b/server/cronjob/prediction.py
index 25b49e9..80943e6 100644
--- a/server/cronjob/prediction.py
+++ b/server/cronjob/prediction.py
@@ -35,19 +35,24 @@
 def main():
     """
     Run prediction based on given input
+    Implemented based on daily prediction 
     """
+    cur_time = datetime.now().strftime('%Y-%m-%dT%H:%M:%S.000Z')
+
     parser = argparse.ArgumentParser('Prediction service')
     parser.add_argument(
         '--prometheus_query', 
         type=str, 
         help='API endpoint to get the relevant metric', 
-        default=f'{PROMETHEUS}' + '/api/v1/query_range?query=sum(increase(kepler_container_joules_total{job=%27kepler%27}[10m]))&start=2024-08-11T00:00:00.000Z&end=2024-08-13T00:00:00.000Z&step=600s'
+        default='sum(increase(kepler_container_joules_total{job=%27kepler%27}[1d]))&start=2024-08-11T00:00:00.000Z&'+f'end={cur_time}&step=86400s'
     )
     parser.add_argument('--forecasting_method', help='Choose forecasting method [ARIMA, HBNN]', default='ARIMA')
     args = parser.parse_args()
 
+    # Get full query
+    prometheus_query = f'{PROMETHEUS}/api/v1/query_range?query={args.prometheus_query}'
     # Get the metrics
-    res = requests.get(args.prometheus_query)
+    res = requests.get(prometheus_query)
     print(res.content)
     if (res.ok):
         res_json = json.loads(res.content)['data']['result'][0]['values']
@@ -56,18 +61,18 @@ def main():
         times = data_dict.keys()
         vals = data_dict.values()
         vals = np.array(list(vals)).astype(float)
-        print('times', times)
-        print('vals', vals)
+        print('\ntimes', times)
+        print('\nvals', vals)
         
         # Get the precition
-        pred = AutoARIMA(vals, evaluate=10)
+        pred = AutoARIMA(vals, evaluate=1)
         print(pred.prediction, pred.upper_bound, pred.lower_bound)
 
         # Construct JSON format data to be posted
         data = {
-            "aggregation_interval": 600,
+            "aggregation_interval": 86400,
             "forecasting_lower_bounds": pred.lower_bound if isinstance(pred.lower_bound, list) else [pred.lower_bound],
-            "forecasting_model": "ARIMA",
+            "forecasting_model": args.forecasting_method,
             "forecasting_period": 1,
             "forecasting_upper_bounds": pred.upper_bound if isinstance(pred.upper_bound, list) else [pred.upper_bound],
             "forecasting_values": pred.prediction if isinstance(pred.prediction, list) else [pred.prediction],
@@ -78,11 +83,11 @@ def main():
 
         store(ENDPOINT, data)
     else:
-        print(f'Response: {res}')
+        print(f'\nResponse: {res}')
 
 
 def store(
-    endpoint: str = 'http://data-storage.integration/prediction', 
+    endpoint: str = ENDPOINT, 
     data: dict = TEST_DATA,
 ):
     """ Post data to REST API endpoint