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? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@pinot.apache.org For additional commands, e-mail: commits-h...@pinot.apache.org