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Posted to dev@pinot.apache.org by GitBox <gi...@apache.org> on 2018/11/19 18:30:26 UTC
[GitHub] jihaozh closed pull request #3510: [TE] detection - add two side
pattern in rule filters
jihaozh closed pull request #3510: [TE] detection - add two side pattern in rule filters
URL: https://github.com/apache/incubator-pinot/pull/3510
This is a PR merged from a forked repository.
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diff --git a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/Pattern.java b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/Pattern.java
index 40b14bf03d..d89db1233a 100644
--- a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/Pattern.java
+++ b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/Pattern.java
@@ -21,5 +21,6 @@
*/
public enum Pattern {
UP,
- DOWN
+ DOWN,
+ UP_OR_DOWN
}
diff --git a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/AbsoluteChangeRuleDetector.java b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/AbsoluteChangeRuleDetector.java
index 0c812c7cba..1838cedbe4 100644
--- a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/AbsoluteChangeRuleDetector.java
+++ b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/AbsoluteChangeRuleDetector.java
@@ -83,10 +83,14 @@
// defaults
df.addSeries(COL_ANOMALY, BooleanSeries.fillValues(df.size(), false));
-
// absolute change
if (!Double.isNaN(this.absoluteChange)) {
- df.addSeries(COL_PATTERN, this.pattern.equals(Pattern.UP) ? df.getDoubles(COL_DIFF).gt(0) : df.getDoubles(COL_DIFF).lt(0));
+ // consistent with pattern
+ if (pattern.equals(Pattern.UP_OR_DOWN) ) {
+ df.addSeries(COL_PATTERN, BooleanSeries.fillValues(df.size(), true));
+ } else {
+ df.addSeries(COL_PATTERN, this.pattern.equals(Pattern.UP) ? df.getDoubles(COL_DIFF).gt(0) : df.getDoubles(COL_DIFF).lt(0));
+ }
df.addSeries(COL_DIFF_VIOLATION, df.getDoubles(COL_DIFF).abs().gte(this.absoluteChange));
df.mapInPlace(BooleanSeries.ALL_TRUE, COL_ANOMALY, COL_PATTERN, COL_DIFF_VIOLATION);
}
diff --git a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleDetector.java b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleDetector.java
index 14f09d5c71..be35f7d711 100644
--- a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleDetector.java
+++ b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleDetector.java
@@ -94,7 +94,12 @@
// relative change
if (!Double.isNaN(this.percentageChange)) {
- df.addSeries(COL_PATTERN, this.pattern.equals(Pattern.UP) ? df.getDoubles(COL_CHANGE).gt(0) : df.getDoubles(COL_CHANGE).lt(0));
+ // consistent with pattern
+ if (pattern.equals(Pattern.UP_OR_DOWN) ) {
+ df.addSeries(COL_PATTERN, BooleanSeries.fillValues(df.size(), true));
+ } else {
+ df.addSeries(COL_PATTERN, this.pattern.equals(Pattern.UP) ? df.getDoubles(COL_CHANGE).gt(0) : df.getDoubles(COL_CHANGE).lt(0));
+ }
df.addSeries(COL_CHANGE_VIOLATION, df.getDoubles(COL_CHANGE).abs().gte(this.percentageChange));
df.mapInPlace(BooleanSeries.ALL_TRUE, COL_ANOMALY, COL_PATTERN, COL_CHANGE_VIOLATION);
}
diff --git a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/SitewideImpactRuleAnomalyFilter.java b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/SitewideImpactRuleAnomalyFilter.java
index 5f85d18e67..1eee883119 100644
--- a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/SitewideImpactRuleAnomalyFilter.java
+++ b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/SitewideImpactRuleAnomalyFilter.java
@@ -75,8 +75,7 @@ public boolean isQualified(MergedAnomalyResultDTO anomaly) {
double siteWideBaselineValue = getValueFromAggregates(siteWideSlice, aggregates);
// if inconsistent with up/down, filter the anomaly
- if ((currentValue < baselineValue && pattern.equals(Pattern.UP)) || (currentValue > baselineValue && pattern.equals(
- Pattern.DOWN))) {
+ if (!pattern.equals(Pattern.UP_OR_DOWN) && (currentValue < baselineValue && pattern.equals(Pattern.UP)) || (currentValue > baselineValue && pattern.equals(Pattern.DOWN))) {
return false;
}
// if doesn't pass the threshold, filter the anomaly
diff --git a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/spec/AbsoluteChangeRuleDetectorSpec.java b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/spec/AbsoluteChangeRuleDetectorSpec.java
index c6b25aa512..26f5d662fe 100644
--- a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/spec/AbsoluteChangeRuleDetectorSpec.java
+++ b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/spec/AbsoluteChangeRuleDetectorSpec.java
@@ -16,9 +16,6 @@
package com.linkedin.thirdeye.detection.spec;
-import com.linkedin.thirdeye.detection.Pattern;
-
-
public class AbsoluteChangeRuleDetectorSpec extends AbstractSpec {
private double absoluteChange = Double.NaN;
private String offset = "wo1w";
diff --git a/thirdeye/thirdeye-pinot/src/test/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleDetectorTest.java b/thirdeye/thirdeye-pinot/src/test/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleDetectorTest.java
index d3f4e6dcd3..016f8e2d6c 100644
--- a/thirdeye/thirdeye-pinot/src/test/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleDetectorTest.java
+++ b/thirdeye/thirdeye-pinot/src/test/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleDetectorTest.java
@@ -125,4 +125,27 @@ public void testThreeWeekMedianChangeDown() {
Assert.assertEquals(anomalies.get(0).getStartTime(), 2181600000L);
Assert.assertEquals(anomalies.get(0).getEndTime(), 2185200000L);
}
+
+ @Test
+ public void testThreeWeekMedianChangeUporDown() {
+ PercentageChangeRuleDetector detector = new PercentageChangeRuleDetector();
+ PercentageChangeRuleDetectorSpec spec = new PercentageChangeRuleDetectorSpec();
+ spec.setPercentageChange(0.3);
+ spec.setOffset("median3w");
+ spec.setPattern("up_or_down");
+ detector.init(spec, new DefaultInputDataFetcher(this.provider, -1));
+ List<MergedAnomalyResultDTO> anomalies = detector.runDetection(new Interval(1814400000L, 2419200000L), "thirdeye:metric:1");
+ Assert.assertEquals(anomalies.size(), 5);
+ Assert.assertEquals(anomalies.get(0).getStartTime(), 2005200000L);
+ Assert.assertEquals(anomalies.get(0).getEndTime(), 2008800000L);
+ Assert.assertEquals(anomalies.get(1).getStartTime(), 2134800000L);
+ Assert.assertEquals(anomalies.get(1).getEndTime(), 2138400000L);
+ Assert.assertEquals(anomalies.get(2).getStartTime(), 2152800000L);
+ Assert.assertEquals(anomalies.get(2).getEndTime(), 2156400000L);
+ Assert.assertEquals(anomalies.get(3).getStartTime(), 2181600000L);
+ Assert.assertEquals(anomalies.get(3).getEndTime(), 2185200000L);
+ Assert.assertEquals(anomalies.get(4).getStartTime(), 2322000000L);
+ Assert.assertEquals(anomalies.get(4).getEndTime(), 2325600000L);
+ }
+
}
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