Fix automated monitoring, prevent duplicate queries

sodadata · May 3, 2024 · 0903719 · 0903719
1 parent 5e51e69
commit 0903719
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Showing 2 changed files with 6 additions and 11 deletions.
diff --git a/soda/core/soda/execution/check/automated_monitoring_run.py b/soda/core/soda/execution/check/automated_monitoring_run.py
@@ -60,9 +60,6 @@ def create_anomaly_detection_checks(self) -> List[AnomalyMetricCheck]:
             )
             anomaly_metric_check.archetype = "volumeConsistency"
 
-            # Execute query to change the value of metric class to get the historical results
-            self.data_source_scan.execute_queries()
-
             annomaly_detection_checks.append(anomaly_metric_check)
 
         return annomaly_detection_checks
@@ -110,8 +107,6 @@ def create_schema_checks(self) -> List[SchemaCheck]:
             schema_check = SchemaCheck(schema_check_cfg, self.data_source_scan, partition=partition)
             schema_check.archetype = "schemaConsistency"
 
-            # Execute query to change the value of metric class to get the historical results
-            self.data_source_scan.execute_queries()
             schema_checks.append(schema_check)
         return schema_checks
 

diff --git a/soda/core/soda/scan.py b/soda/core/soda/scan.py
@@ -504,6 +504,12 @@ def execute(self) -> int:
                 self._logs.info(f"Refer to list of valid attributes and values at {attributes_page_url}.")
 
             if not invalid_checks:
+                # Run profiling, data samples, automated monitoring, sample tables
+                try:
+                    self.run_data_source_scan()
+                except Exception as e:
+                    self._logs.error("""An error occurred while executing data source scan""", exception=e)
+
                 # Each data_source is asked to create metric values that are returned as a list of query results
                 for data_source_scan in self._data_source_scans:
                     data_source_scan.execute_queries()
@@ -518,12 +524,6 @@ def execute(self) -> int:
                         for metric_dep in metric.derived_formula.metric_dependencies.values():
                             metric.queries += metric_dep.queries
 
-                # Run profiling, data samples, automated monitoring, sample tables
-                try:
-                    self.run_data_source_scan()
-                except Exception as e:
-                    self._logs.error("""An error occurred while executing data source scan""", exception=e)
-
                 # Evaluates the checks based on all the metric values
                 for check in self._checks:
                     # First get the metric values for this check