jasonyanwenl commented on a change in pull request #5866:
URL: https://github.com/apache/incubator-pinot/pull/5866#discussion_r473202402



##########
File path: 
thirdeye/thirdeye-pinot/src/main/java/org/apache/pinot/thirdeye/api/detection/AnomalyDetectionResource.java
##########
@@ -511,24 +499,19 @@ private TaskDTO pollingTask(long taskId) {
   }
 
   private void cleanStates(MetricConfigDTO metricConfigDTO, DatasetConfigDTO 
datasetConfigDTO) {
+    // Clean up ad hoc data
     if (datasetConfigDTO != null) {
-      datasetConfigDAO.delete(datasetConfigDTO);
-      LOG.info("Deleted dataset: {}", datasetConfigDTO);
-
-      int anomalyCnt = anomalyDAO.deleteByPredicate(
-          Predicate.EQ("collection", datasetConfigDTO.getName()));
-      LOG.info("Deleted {} anomalies with dataset {}",
-          anomalyCnt, datasetConfigDTO.getName());
+      int onlineDetectionDataCnt = onlineDetectionDataDAO
+          .deleteByPredicate(Predicate.EQ("dataset", 
datasetConfigDTO.getName()));

Review comment:
       Thank you for the point! This is a good idea. But it also has some 
trade-off. Like during the detection pipeline workflow, we cannot reuse the 
existing DAO layer logic to retrieve dataset/metric configurations from 
corresponding tables. Probably we will add some extra logic to separate online 
detection from the original detection during the DAO layer for this. Currently 
how about let's currently keep this and I will note down this in the design doc 
for future reference?




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