jihaozh closed pull request #3514: [TE] Percentage and absolute change rule filter URL: https://github.com/apache/incubator-pinot/pull/3514
This is a PR merged from a forked repository. As GitHub hides the original diff on merge, it is displayed below for the sake of provenance: As this is a foreign pull request (from a fork), the diff is supplied below (as it won't show otherwise due to GitHub magic): diff --git a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/AbsoluteChangeRuleAnomalyFilter.java b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/AbsoluteChangeRuleAnomalyFilter.java new file mode 100644 index 0000000000..9c7ce49202 --- /dev/null +++ b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/AbsoluteChangeRuleAnomalyFilter.java @@ -0,0 +1,97 @@ +/* + * Copyright (C) 2014-2018 LinkedIn Corp. ([email protected]) + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.linkedin.thirdeye.detection.components; + +import com.linkedin.thirdeye.dashboard.resources.v2.BaselineParsingUtils; +import com.linkedin.thirdeye.dataframe.DataFrame; +import com.linkedin.thirdeye.dataframe.util.MetricSlice; +import com.linkedin.thirdeye.datalayer.dto.MergedAnomalyResultDTO; +import com.linkedin.thirdeye.detection.InputDataFetcher; +import com.linkedin.thirdeye.detection.Pattern; +import com.linkedin.thirdeye.detection.annotation.Components; +import com.linkedin.thirdeye.detection.annotation.DetectionTag; +import com.linkedin.thirdeye.detection.spec.AbsoluteChangeRuleAnomalyFilterSpec; +import com.linkedin.thirdeye.detection.spi.components.AnomalyFilter; +import com.linkedin.thirdeye.detection.spi.model.InputDataSpec; +import com.linkedin.thirdeye.rootcause.impl.MetricEntity; +import com.linkedin.thirdeye.rootcause.timeseries.Baseline; +import java.util.ArrayList; +import java.util.List; +import java.util.Map; +import org.apache.commons.lang.StringUtils; + +import static com.linkedin.thirdeye.dataframe.util.DataFrameUtils.*; + +/** + * Absolute change anomaly filter. Check if the anomaly's absolute change compared to baseline is above the threshold. + * If not, filters the anomaly. + */ +@Components(type = "ABSOLUTE_CHANGE_FILTER", tags = {DetectionTag.RULE_FILTER}) +public class AbsoluteChangeRuleAnomalyFilter implements AnomalyFilter<AbsoluteChangeRuleAnomalyFilterSpec> { + private double threshold; + private InputDataFetcher dataFetcher; + private Baseline baseline; + private Pattern pattern; + + @Override + public boolean isQualified(MergedAnomalyResultDTO anomaly) { + MetricEntity me = MetricEntity.fromURN(anomaly.getMetricUrn()); + List<MetricSlice> slices = new ArrayList<>(); + MetricSlice currentSlice = + MetricSlice.from(me.getId(), anomaly.getStartTime(), anomaly.getEndTime(), me.getFilters()); + slices.add(currentSlice); + + // customize baseline offset + MetricSlice baselineSlice = null; + if (baseline != null) { + baselineSlice = this.baseline.scatter(currentSlice).get(0); + slices.add(baselineSlice); + } + + Map<MetricSlice, DataFrame> aggregates = + this.dataFetcher.fetchData(new InputDataSpec().withAggregateSlices(slices)).getAggregates(); + + double currentValue = getValueFromAggregates(currentSlice, aggregates); + double baselineValue = + baselineSlice == null ? anomaly.getAvgBaselineVal() : getValueFromAggregates(baselineSlice, aggregates); + // if inconsistent with up/down, filter the anomaly + if (!pattern.equals(Pattern.UP_OR_DOWN) && (currentValue < baselineValue && pattern.equals(Pattern.UP)) || ( + currentValue > baselineValue && pattern.equals(Pattern.DOWN))) { + return false; + } + if (Math.abs(currentValue - baselineValue) < this.threshold) { + return false; + } + return true; + } + + @Override + public void init(AbsoluteChangeRuleAnomalyFilterSpec spec, InputDataFetcher dataFetcher) { + this.dataFetcher = dataFetcher; + this.pattern = Pattern.valueOf(spec.getPattern().toUpperCase()); + // customize baseline offset + if (StringUtils.isNotBlank(spec.getOffset())) { + this.baseline = BaselineParsingUtils.parseOffset(spec.getOffset(), spec.getTimezone()); + } + this.threshold = spec.getThreshold(); + } + + private double getValueFromAggregates(MetricSlice slice, Map<MetricSlice, DataFrame> aggregates) { + return aggregates.get(slice).getDouble(COL_VALUE, 0); + } + +} diff --git a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleAnomalyFilter.java b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleAnomalyFilter.java new file mode 100644 index 0000000000..49f433174a --- /dev/null +++ b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleAnomalyFilter.java @@ -0,0 +1,96 @@ +/* + * Copyright (C) 2014-2018 LinkedIn Corp. ([email protected]) + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.linkedin.thirdeye.detection.components; + +import com.linkedin.thirdeye.dashboard.resources.v2.BaselineParsingUtils; +import com.linkedin.thirdeye.dataframe.DataFrame; +import com.linkedin.thirdeye.dataframe.util.MetricSlice; +import com.linkedin.thirdeye.datalayer.dto.MergedAnomalyResultDTO; +import com.linkedin.thirdeye.detection.InputDataFetcher; +import com.linkedin.thirdeye.detection.Pattern; +import com.linkedin.thirdeye.detection.annotation.Components; +import com.linkedin.thirdeye.detection.annotation.DetectionTag; +import com.linkedin.thirdeye.detection.spec.PercentageChangeRuleAnomalyFilterSpec; +import com.linkedin.thirdeye.detection.spi.components.AnomalyFilter; +import com.linkedin.thirdeye.detection.spi.model.InputDataSpec; +import com.linkedin.thirdeye.rootcause.impl.MetricEntity; +import com.linkedin.thirdeye.rootcause.timeseries.Baseline; +import java.util.ArrayList; +import java.util.List; +import java.util.Map; +import org.apache.commons.lang.StringUtils; + +import static com.linkedin.thirdeye.dataframe.util.DataFrameUtils.*; + +/** + * Percentage change anomaly filter. Check if the anomaly's percentage change compared to baseline is above the threshold. + * If not, filters the anomaly. + */ +@Components(type = "PERCENTAGE_CHANGE_FILTER", tags = {DetectionTag.RULE_FILTER}) +public class PercentageChangeRuleAnomalyFilter implements AnomalyFilter<PercentageChangeRuleAnomalyFilterSpec> { + private double threshold; + private InputDataFetcher dataFetcher; + private Baseline baseline; + private Pattern pattern; + + @Override + public boolean isQualified(MergedAnomalyResultDTO anomaly) { + MetricEntity me = MetricEntity.fromURN(anomaly.getMetricUrn()); + List<MetricSlice> slices = new ArrayList<>(); + MetricSlice currentSlice = + MetricSlice.from(me.getId(), anomaly.getStartTime(), anomaly.getEndTime(), me.getFilters()); + slices.add(currentSlice); + + // customize baseline offset + MetricSlice baselineSlice = null; + if (baseline != null) { + baselineSlice = this.baseline.scatter(currentSlice).get(0); + slices.add(baselineSlice); + } + + Map<MetricSlice, DataFrame> aggregates = + this.dataFetcher.fetchData(new InputDataSpec().withAggregateSlices(slices)).getAggregates(); + + double currentValue = getValueFromAggregates(currentSlice, aggregates); + double baselineValue = + baselineSlice == null ? anomaly.getAvgBaselineVal() : getValueFromAggregates(baselineSlice, aggregates); + // if inconsistent with up/down, filter the anomaly + if (!pattern.equals(Pattern.UP_OR_DOWN) && (currentValue < baselineValue && pattern.equals(Pattern.UP)) || ( + currentValue > baselineValue && pattern.equals(Pattern.DOWN))) { + return false; + } + if (baselineValue != 0 && Math.abs(currentValue / baselineValue - 1) < this.threshold) { + return false; + } + return true; + } + + @Override + public void init(PercentageChangeRuleAnomalyFilterSpec spec, InputDataFetcher dataFetcher) { + this.dataFetcher = dataFetcher; + this.pattern = Pattern.valueOf(spec.getPattern().toUpperCase()); + // customize baseline offset + if (StringUtils.isNotBlank(spec.getOffset())) { + this.baseline = BaselineParsingUtils.parseOffset(spec.getOffset(), spec.getTimezone()); + } + this.threshold = spec.getThreshold(); + } + + private double getValueFromAggregates(MetricSlice slice, Map<MetricSlice, DataFrame> aggregates) { + return aggregates.get(slice).getDouble(COL_VALUE, 0); + } +} 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 1eee883119..e5800b6a68 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 @@ -23,6 +23,7 @@ import java.util.Collections; import java.util.List; import java.util.Map; +import org.apache.commons.lang.StringUtils; import static com.linkedin.thirdeye.dataframe.util.DataFrameUtils.*; @@ -94,7 +95,7 @@ public void init(SitewideImpactRuleAnomalyFilterSpec spec, InputDataFetcher data this.pattern = Pattern.valueOf(spec.getPattern().toUpperCase()); // customize baseline offset - if (!Strings.isNullOrEmpty(spec.getOffset())){ + if (StringUtils.isNotBlank(spec.getOffset())){ this.baseline = BaselineParsingUtils.parseOffset(spec.getOffset(), spec.getTimezone()); } diff --git a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/spec/AbsoluteChangeRuleAnomalyFilterSpec.java b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/spec/AbsoluteChangeRuleAnomalyFilterSpec.java new file mode 100644 index 0000000000..138ca5045b --- /dev/null +++ b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/spec/AbsoluteChangeRuleAnomalyFilterSpec.java @@ -0,0 +1,56 @@ +/* + * Copyright (C) 2014-2018 LinkedIn Corp. ([email protected]) + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.linkedin.thirdeye.detection.spec; + +public class AbsoluteChangeRuleAnomalyFilterSpec extends AbstractSpec { + private String timezone = "UTC"; + private double threshold = Double.NaN; + private String offset; + private String pattern; + + public String getTimezone() { + return timezone; + } + + public void setTimezone(String timezone) { + this.timezone = timezone; + } + + public double getThreshold() { + return threshold; + } + + public void setThreshold(double threshold) { + this.threshold = threshold; + } + + public String getOffset() { + return offset; + } + + public void setOffset(String offset) { + this.offset = offset; + } + + public String getPattern() { + return pattern; + } + + public void setPattern(String pattern) { + this.pattern = pattern; + } +} diff --git a/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/spec/PercentageChangeRuleAnomalyFilterSpec.java b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/spec/PercentageChangeRuleAnomalyFilterSpec.java new file mode 100644 index 0000000000..3717bb6bba --- /dev/null +++ b/thirdeye/thirdeye-pinot/src/main/java/com/linkedin/thirdeye/detection/spec/PercentageChangeRuleAnomalyFilterSpec.java @@ -0,0 +1,56 @@ +/* + * Copyright (C) 2014-2018 LinkedIn Corp. ([email protected]) + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.linkedin.thirdeye.detection.spec; + +public class PercentageChangeRuleAnomalyFilterSpec extends AbstractSpec { + private String timezone = "UTC"; + private double threshold = Double.NaN; + private String offset; + private String pattern; + + public String getTimezone() { + return timezone; + } + + public void setTimezone(String timezone) { + this.timezone = timezone; + } + + public double getThreshold() { + return threshold; + } + + public void setThreshold(double threshold) { + this.threshold = threshold; + } + + public String getOffset() { + return offset; + } + + public void setOffset(String offset) { + this.offset = offset; + } + + public String getPattern() { + return pattern; + } + + public void setPattern(String pattern) { + this.pattern = pattern; + } +} diff --git a/thirdeye/thirdeye-pinot/src/test/java/com/linkedin/thirdeye/detection/components/AbsoluteChangeRuleAnomalyFilterTest.java b/thirdeye/thirdeye-pinot/src/test/java/com/linkedin/thirdeye/detection/components/AbsoluteChangeRuleAnomalyFilterTest.java new file mode 100644 index 0000000000..bc0bb29d0e --- /dev/null +++ b/thirdeye/thirdeye-pinot/src/test/java/com/linkedin/thirdeye/detection/components/AbsoluteChangeRuleAnomalyFilterTest.java @@ -0,0 +1,90 @@ +/* + * Copyright (C) 2014-2018 LinkedIn Corp. ([email protected]) + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.linkedin.thirdeye.detection.components; + +import com.linkedin.thirdeye.dataframe.DataFrame; +import com.linkedin.thirdeye.dataframe.util.MetricSlice; +import com.linkedin.thirdeye.datalayer.dto.MergedAnomalyResultDTO; +import com.linkedin.thirdeye.detection.DataProvider; +import com.linkedin.thirdeye.detection.DefaultInputDataFetcher; +import com.linkedin.thirdeye.detection.DetectionTestUtils; +import com.linkedin.thirdeye.detection.MockDataProvider; +import com.linkedin.thirdeye.detection.spec.AbsoluteChangeRuleAnomalyFilterSpec; +import com.linkedin.thirdeye.detection.spec.PercentageChangeRuleAnomalyFilterSpec; +import com.linkedin.thirdeye.detection.spi.components.AnomalyFilter; +import com.linkedin.thirdeye.rootcause.timeseries.Baseline; +import com.linkedin.thirdeye.rootcause.timeseries.BaselineAggregate; +import com.linkedin.thirdeye.rootcause.timeseries.BaselineAggregateType; +import java.util.Arrays; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.stream.Collectors; +import org.joda.time.DateTimeZone; +import org.testng.Assert; +import org.testng.annotations.BeforeMethod; +import org.testng.annotations.Test; + +import static com.linkedin.thirdeye.dataframe.util.DataFrameUtils.*; + + +public class AbsoluteChangeRuleAnomalyFilterTest { + private static final String METRIC_URN = "thirdeye:metric:123"; + + private DataProvider testDataProvider; + private Baseline baseline; + + @BeforeMethod + public void beforeMethod() { + this.baseline = BaselineAggregate.fromWeekOverWeek(BaselineAggregateType.MEDIAN, 1, 1, DateTimeZone.forID("UTC")); + + MetricSlice slice1 = MetricSlice.from(123L, 0, 2); + MetricSlice baselineSlice1 = this.baseline.scatter(slice1).get(0); + MetricSlice slice2 = MetricSlice.from(123L, 4, 6); + MetricSlice baselineSlice2 = this.baseline.scatter(slice2).get(0); + + Map<MetricSlice, DataFrame> aggregates = new HashMap<>(); + aggregates.put(slice1, new DataFrame().addSeries(COL_VALUE, 150)); + aggregates.put(baselineSlice1, new DataFrame().addSeries(COL_VALUE, 200)); + aggregates.put(slice2, new DataFrame().addSeries(COL_VALUE, 500)); + aggregates.put(baselineSlice2, new DataFrame().addSeries(COL_VALUE, 1000)); + + this.testDataProvider = new MockDataProvider().setAggregates(aggregates); + } + + @Test + public void testAbsoluteChangeFilter(){ + AbsoluteChangeRuleAnomalyFilterSpec spec = new AbsoluteChangeRuleAnomalyFilterSpec(); + spec.setOffset("median1w"); + spec.setThreshold(100); + spec.setPattern("up_or_down"); + AnomalyFilter filter = new AbsoluteChangeRuleAnomalyFilter(); + filter.init(spec, new DefaultInputDataFetcher(this.testDataProvider, 125L)); + List<Boolean> results = + Arrays.asList(makeAnomaly(0, 2), makeAnomaly(4, 6)).stream().map(anomaly -> filter.isQualified(anomaly)).collect( + Collectors.toList()); + Assert.assertEquals(results, Arrays.asList(false, true)); + } + + + private static MergedAnomalyResultDTO makeAnomaly(long start, long end) { + Map<String, String> dimensions = new HashMap<>(); + MergedAnomalyResultDTO anomaly = DetectionTestUtils.makeAnomaly(125L, start, end, dimensions); + anomaly.setMetricUrn(METRIC_URN); + return anomaly; + } +} diff --git a/thirdeye/thirdeye-pinot/src/test/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleAnomalyFilterTest.java b/thirdeye/thirdeye-pinot/src/test/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleAnomalyFilterTest.java new file mode 100644 index 0000000000..a4a65bbf86 --- /dev/null +++ b/thirdeye/thirdeye-pinot/src/test/java/com/linkedin/thirdeye/detection/components/PercentageChangeRuleAnomalyFilterTest.java @@ -0,0 +1,89 @@ +/* + * Copyright (C) 2014-2018 LinkedIn Corp. ([email protected]) + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package com.linkedin.thirdeye.detection.components; + +import com.linkedin.thirdeye.dataframe.DataFrame; +import com.linkedin.thirdeye.dataframe.util.MetricSlice; +import com.linkedin.thirdeye.datalayer.dto.MergedAnomalyResultDTO; +import com.linkedin.thirdeye.detection.DataProvider; +import com.linkedin.thirdeye.detection.DefaultInputDataFetcher; +import com.linkedin.thirdeye.detection.DetectionTestUtils; +import com.linkedin.thirdeye.detection.MockDataProvider; +import com.linkedin.thirdeye.detection.spec.PercentageChangeRuleAnomalyFilterSpec; +import com.linkedin.thirdeye.detection.spi.components.AnomalyFilter; +import com.linkedin.thirdeye.rootcause.timeseries.Baseline; +import com.linkedin.thirdeye.rootcause.timeseries.BaselineAggregate; +import com.linkedin.thirdeye.rootcause.timeseries.BaselineAggregateType; +import java.util.Arrays; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.stream.Collectors; +import org.joda.time.DateTimeZone; +import org.testng.Assert; +import org.testng.annotations.BeforeMethod; +import org.testng.annotations.Test; + +import static com.linkedin.thirdeye.dataframe.util.DataFrameUtils.*; + + +public class PercentageChangeRuleAnomalyFilterTest { + private static final String METRIC_URN = "thirdeye:metric:123"; + + private DataProvider testDataProvider; + private Baseline baseline; + + @BeforeMethod + public void beforeMethod() { + this.baseline = BaselineAggregate.fromWeekOverWeek(BaselineAggregateType.MEDIAN, 1, 1, DateTimeZone.forID("UTC")); + + MetricSlice slice1 = MetricSlice.from(123L, 0, 2); + MetricSlice baselineSlice1 = this.baseline.scatter(slice1).get(0); + MetricSlice slice2 = MetricSlice.from(123L, 4, 6); + MetricSlice baselineSlice2 = this.baseline.scatter(slice2).get(0); + + Map<MetricSlice, DataFrame> aggregates = new HashMap<>(); + aggregates.put(slice1, new DataFrame().addSeries(COL_VALUE, 150)); + aggregates.put(baselineSlice1, new DataFrame().addSeries(COL_VALUE, 200)); + aggregates.put(slice2, new DataFrame().addSeries(COL_VALUE, 500)); + aggregates.put(baselineSlice2, new DataFrame().addSeries(COL_VALUE, 1000)); + + this.testDataProvider = new MockDataProvider().setAggregates(aggregates); + } + + @Test + public void testPercentageChangeFilter(){ + PercentageChangeRuleAnomalyFilterSpec spec = new PercentageChangeRuleAnomalyFilterSpec(); + spec.setOffset("median1w"); + spec.setThreshold(0.5); + spec.setPattern("up_or_down"); + AnomalyFilter filter = new PercentageChangeRuleAnomalyFilter(); + filter.init(spec, new DefaultInputDataFetcher(this.testDataProvider, 125L)); + List<Boolean> results = + Arrays.asList(makeAnomaly(0, 2), makeAnomaly(4, 6)).stream().map(anomaly -> filter.isQualified(anomaly)).collect( + Collectors.toList()); + Assert.assertEquals(results, Arrays.asList(false, true)); + } + + + private static MergedAnomalyResultDTO makeAnomaly(long start, long end) { + Map<String, String> dimensions = new HashMap<>(); + MergedAnomalyResultDTO anomaly = DetectionTestUtils.makeAnomaly(125L, start, end, dimensions); + anomaly.setMetricUrn(METRIC_URN); + return anomaly; + } +} ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
