xiaohui-sun commented on a change in pull request #4176: [TE] anomaly detector
interface change and implementation for rule-based detection
URL: https://github.com/apache/incubator-pinot/pull/4176#discussion_r280170399
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File path:
thirdeye/thirdeye-pinot/src/main/java/org/apache/pinot/thirdeye/detection/components/ThresholdRuleDetector.java
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@@ -87,8 +91,38 @@
df.mapInPlace(BooleanSeries.HAS_TRUE, COL_ANOMALY, COL_TOO_HIGH,
COL_TOO_LOW);
DatasetConfigDTO datasetConfig =
data.getDatasetForMetricId().get(me.getId());
- return DetectionUtils.makeAnomalies(slice, df, COL_ANOMALY, endTime,
+ List<MergedAnomalyResultDTO> anomalies =
DetectionUtils.makeAnomalies(slice, df, COL_ANOMALY, endTime,
DetectionUtils.getMonitoringGranularityPeriod(monitoringGranularity,
datasetConfig), datasetConfig);
+ return DetectionResult.from(anomalies,
TimeSeries.fromDataFrame(constructThresholdBoundaries(df)));
+ }
+
+ @Override
+ public TimeSeries computePredictedTimeSeries(MetricSlice slice) {
+ InputData data =
+ this.dataFetcher.fetchData(new
InputDataSpec().withTimeseriesSlices(Collections.singletonList(slice)));
+ DataFrame df = data.getTimeseries().get(slice);
+ return TimeSeries.fromDataFrame(constructThresholdBoundaries(df));
+ }
+
+ private DataFrame constructThresholdBoundaries(DataFrame df) {
+ if (!Double.isNaN(this.min)) {
+ df.addSeries(COL_LOWER_BOUND, DoubleSeries.fillValues(df.size(),
this.min));
+ }
+ if (!Double.isNaN(this.max)) {
+ df.addSeries(COL_UPPER_BOUND, DoubleSeries.fillValues(df.size(),
this.max));
+ }
+ df.addSeries(COL_VALUE, DoubleSeries.fillValues(df.size(),
predictedValue()));
+ return df;
+ }
+
+ private double predictedValue() {
Review comment:
Why we show percentage change for threshold based rules?
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