jihaozh commented on a change in pull request #4190: [TE] pass predicted time
series thought out the detection pipeline
URL: https://github.com/apache/incubator-pinot/pull/4190#discussion_r282182826
##########
File path:
thirdeye/thirdeye-pinot/src/main/java/org/apache/pinot/thirdeye/detection/wrapper/AnomalyDetectorWrapper.java
##########
@@ -201,8 +206,58 @@ public DetectionPipelineResult run() throws Exception {
anomaly.getProperties().put(PROP_DETECTOR_COMPONENT_NAME,
this.detectorName);
}
long lastTimeStamp = this.getLastTimeStamp();
- return new DetectionPipelineResult(anomalies.stream().filter(anomaly ->
anomaly.getEndTime() <= lastTimeStamp).collect(
- Collectors.toList()), lastTimeStamp);
+ List<MergedAnomalyResultDTO> anomalyResults =
anomalies.stream().filter(anomaly -> anomaly.getEndTime() <=
lastTimeStamp).collect(
+ Collectors.toList());
+ PredictionResult predictedTimeSeries = new
PredictionResult(this.detectorName, this.metricUrn,
predictedResult.getDataFrame());
+ return new DetectionPipelineResult(anomalyResults, lastTimeStamp,
Collections.singletonList(predictedTimeSeries));
+ }
+
+ /**
+ * Join two time series, including current, baseline, lower bound and upper
bound. If two time series have overlapped region, take the average
+ * @param ts1 timeseries 1
+ * @param ts2 timeseries 2
+ * @return the consolidated time series
+ */
+ static TimeSeries consolidateTimeSeries(TimeSeries ts1, TimeSeries ts2) {
Review comment:
For now, this is logic is only used here and seems very specific for this
purpose. What about we put it here for now, and refactor this to be a util
function if there is another use case.
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