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Merge pull request #855 from msvinaykumar/getDataToGenRecommendation
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Get data to generate recommendation
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@dinogun
dinogun authored Aug 14, 2023
2 parents 2ae36cd + 780f615 commit 18ca637
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Showing 13 changed files with 200 additions and 235 deletions.
46 changes: 15 additions & 31 deletions src/main/java/com/autotune/analyzer/experiment/ExperimentInitiator.java
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Original file line number Diff line number Diff line change
Expand Up @@ -15,17 +15,17 @@
*******************************************************************************/
package com.autotune.analyzer.experiment;

import com.autotune.analyzer.kruizeObject.KruizeObject;
import com.autotune.analyzer.performanceProfiles.PerformanceProfile;
import com.autotune.analyzer.performanceProfiles.PerformanceProfileInterface.PerfProfileInterface;
import com.autotune.analyzer.utils.AnalyzerConstants;
import com.autotune.common.data.ValidationOutputData;
import com.autotune.common.data.result.ExperimentResultData;
import com.autotune.analyzer.kruizeObject.KruizeObject;
import com.autotune.analyzer.performanceProfiles.PerformanceProfile;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import javax.servlet.http.HttpServletResponse;
import java.lang.reflect.InvocationTargetException;
import java.sql.Timestamp;
import java.util.List;
import java.util.Map;

Expand Down Expand Up @@ -99,34 +99,18 @@ public ValidationOutputData validateAndUpdateResults(
}

// Generate recommendations and add it to the kruize object
public boolean generateAndAddRecommendations(Map<String, KruizeObject> experimentsMap, List<ExperimentResultData> experimentResultDataList) {
if (null == experimentResultDataList)
return false;
if (experimentResultDataList.size() == 0)
return false;
for (ExperimentResultData experimentResultData: experimentResultDataList) {
// TODO: Log the list of invalid experiments and return the error instead of bailing out completely
if (!experimentsMap.containsKey(experimentResultData.getExperiment_name())) {
LOGGER.error("Trying to locate Recommendation for non existent experiment: " +
experimentResultData.getExperiment_name());
continue;
}
KruizeObject kruizeObject = experimentsMap.get(experimentResultData.getExperiment_name());
if (AnalyzerConstants.PerformanceProfileConstants.perfProfileInstances.containsKey(kruizeObject.getPerformanceProfile())) {
try {
PerfProfileInterface perfProfileInstance =
(PerfProfileInterface) AnalyzerConstants.PerformanceProfileConstants
.perfProfileInstances.get(kruizeObject.getPerformanceProfile())
.getDeclaredConstructor().newInstance();
perfProfileInstance.generateRecommendation(kruizeObject, experimentResultData);
} catch (InstantiationException | IllegalAccessException | InvocationTargetException | NoSuchMethodException e ) {
e.printStackTrace();
}
} else {
LOGGER.error("No Recommendation Engine mapping found for performance profile: " +
kruizeObject.getPerformanceProfile() + ". Cannot process recommendations for the experiment");
}
public void generateAndAddRecommendations(KruizeObject kruizeObject, List<ExperimentResultData> experimentResultDataList, Timestamp interval_start_time, Timestamp interval_end_time) throws Exception {
if (AnalyzerConstants.PerformanceProfileConstants.perfProfileInstances.containsKey(kruizeObject.getPerformanceProfile())) {
PerfProfileInterface perfProfileInstance =
(PerfProfileInterface) AnalyzerConstants.PerformanceProfileConstants
.perfProfileInstances.get(kruizeObject.getPerformanceProfile())
.getDeclaredConstructor().newInstance();
perfProfileInstance.generateRecommendation(kruizeObject, experimentResultDataList, interval_start_time, interval_end_time);
} else {
throw new Exception("No Recommendation Engine mapping found for performance profile: " +
kruizeObject.getPerformanceProfile() + ". Cannot process recommendations for the experiment");
}
return true;
}


}
41 changes: 11 additions & 30 deletions src/main/java/com/autotune/analyzer/experiment/ExperimentResultValidation.java
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Expand Up @@ -15,16 +15,14 @@
*******************************************************************************/
package com.autotune.analyzer.experiment;

import com.autotune.analyzer.utils.AnalyzerErrorConstants;
import com.autotune.analyzer.performanceProfiles.utils.PerformanceProfileUtil;
import com.autotune.common.data.ValidationOutputData;
import com.autotune.common.data.result.ContainerData;
import com.autotune.common.data.result.ExperimentResultData;
import com.autotune.analyzer.kruizeObject.KruizeObject;
import com.autotune.analyzer.performanceProfiles.PerformanceProfile;
import com.autotune.analyzer.performanceProfiles.utils.PerformanceProfileUtil;
import com.autotune.analyzer.utils.AnalyzerConstants;
import com.autotune.analyzer.utils.AnalyzerErrorConstants;
import com.autotune.common.data.ValidationOutputData;
import com.autotune.common.data.result.ExperimentResultData;
import com.autotune.common.data.result.IntervalResults;
import com.autotune.common.k8sObjects.K8sObject;
import com.autotune.database.service.ExperimentDBService;
import com.autotune.utils.KruizeConstants;
import org.slf4j.Logger;
Expand All @@ -44,7 +42,7 @@ public class ExperimentResultValidation {
private Map<String, KruizeObject> mainKruizeExperimentMAP;
private Map<String, PerformanceProfile> performanceProfileMap;

public ExperimentResultValidation(Map<String, KruizeObject> mainKruizeExperimentMAP,Map<String, PerformanceProfile> performanceProfileMap) {
public ExperimentResultValidation(Map<String, KruizeObject> mainKruizeExperimentMAP, Map<String, PerformanceProfile> performanceProfileMap) {
this.mainKruizeExperimentMAP = mainKruizeExperimentMAP;
this.performanceProfileMap = performanceProfileMap;
}
Expand All @@ -57,7 +55,7 @@ public void validate(List<ExperimentResultData> experimentResultDataList, Map<St
String expName = resultData.getExperiment_name();
if (null != expName && !expName.isEmpty() && null != resultData.getIntervalEndTime() && null != resultData.getIntervalStartTime()) {
try {
new ExperimentDBService().loadExperimentAndResultsFromDBByName(mainKruizeExperimentMAP, expName);
new ExperimentDBService().loadExperimentFromDBByName(mainKruizeExperimentMAP, expName);
} catch (Exception e) {
LOGGER.error("Loading saved experiment {} failed: {} ", expName, e.getMessage());
}
Expand All @@ -76,12 +74,12 @@ public void validate(List<ExperimentResultData> experimentResultDataList, Map<St
Double durationInSeconds = intervalResults.getDuration_in_seconds();
String measurementDurationInMins = kruizeObject.getTrial_settings().getMeasurement_durationMinutes();
LOGGER.debug("Duration in seconds = {}", intervalResults.getDuration_in_seconds());
if ( durationInSeconds < 0) {
if (durationInSeconds < 0) {
errorMsg = errorMsg.concat(AnalyzerErrorConstants.AutotuneObjectErrors.WRONG_TIMESTAMP);
resultData.setValidationOutputData(new ValidationOutputData(false, errorMsg, HttpServletResponse.SC_BAD_REQUEST));
break;
} else {
Double parsedMeasurementDuration = Double.parseDouble(measurementDurationInMins.substring(0, measurementDurationInMins.length()-3));
Double parsedMeasurementDuration = Double.parseDouble(measurementDurationInMins.substring(0, measurementDurationInMins.length() - 3));
// Calculate the lower and upper bounds for the acceptable range i.e. +-5 seconds
double lowerRange = Math.abs((parsedMeasurementDuration * KruizeConstants.TimeConv.NO_OF_SECONDS_PER_MINUTE) - (KruizeConstants.TimeConv.MEASUREMENT_DURATION_THRESHOLD_SECONDS));
double upperRange = (parsedMeasurementDuration * KruizeConstants.TimeConv.NO_OF_SECONDS_PER_MINUTE) + (KruizeConstants.TimeConv.MEASUREMENT_DURATION_THRESHOLD_SECONDS);
Expand Down Expand Up @@ -141,24 +139,6 @@ public void validate(List<ExperimentResultData> experimentResultDataList, Map<St
resultData.setValidationOutputData(new ValidationOutputData(false, errorMsg, HttpServletResponse.SC_BAD_REQUEST));
break;
}

// check if resultData is present
boolean isExist = false;
for (K8sObject k8sObject : kruizeObject.getKubernetes_objects()) {
for (ContainerData containerData : k8sObject.getContainerDataMap().values()) {
if (null != containerData.getResults()) {
if (null != containerData.getResults().get(resultData.getIntervalEndTime())) {
isExist = true;
break;
}
}
}
}
if (isExist) {
errorMsg = errorMsg.concat(String.format("Experiment name : %s already contains result for timestamp : %s", resultData.getExperiment_name(), resultData.getIntervalEndTime()));
resultData.setValidationOutputData(new ValidationOutputData(false, errorMsg, HttpServletResponse.SC_CONFLICT));
break;
}
/*
Fetch the performance profile from the Map corresponding to the name in the kruize object,
and then validate the Performance Profile data
Expand All @@ -181,8 +161,8 @@ public void validate(List<ExperimentResultData> experimentResultDataList, Map<St
resultData.setValidationOutputData(new ValidationOutputData(false, errorMsg, HttpServletResponse.SC_BAD_REQUEST));
break;
}
} catch (Exception e) {
LOGGER.error("Caught Exception: {}",e);
} catch (Exception e) {
LOGGER.error("Caught Exception: {}", e);
errorMsg = "Validation failed: " + e.getMessage();
proceed = false;
resultData.setValidationOutputData(new ValidationOutputData(false, errorMsg, HttpServletResponse.SC_INTERNAL_SERVER_ERROR));
Expand Down Expand Up @@ -211,6 +191,7 @@ public void validate(List<ExperimentResultData> experimentResultDataList, Map<St
setErrorMessage("Validation failed: " + e.getMessage());
}
}

public void markFailed(String message) {
setSuccess(false);
setErrorMessage(message);
Expand Down
22 changes: 10 additions & 12 deletions ...va/com/autotune/analyzer/performanceProfiles/PerformanceProfileInterface/DefaultImpl.java
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Original file line number Diff line number Diff line change
Expand Up @@ -16,19 +16,16 @@
package com.autotune.analyzer.performanceProfiles.PerformanceProfileInterface;

import com.autotune.analyzer.kruizeObject.KruizeObject;
import com.autotune.analyzer.performanceProfiles.PerformanceProfile;
import com.autotune.analyzer.performanceProfiles.utils.PerformanceProfileUtil;
import com.autotune.analyzer.recommendations.engine.KruizeRecommendationEngine;
import com.autotune.analyzer.utils.AnalyzerConstants;
import com.autotune.common.data.metrics.Metric;
import com.autotune.common.data.metrics.MetricResults;
import com.autotune.common.data.result.*;
import com.autotune.common.data.result.ContainerData;
import com.autotune.analyzer.recommendations.engine.KruizeRecommendationEngine;
import com.autotune.common.data.result.ExperimentResultData;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.lang.reflect.InvocationTargetException;
import java.util.*;
import java.sql.Timestamp;
import java.util.HashMap;
import java.util.List;

/**
* Util class to validate the performance profile metrics with the experiment results metrics.
Expand All @@ -43,10 +40,6 @@ private String validateValues(HashMap<String, MetricResults> funcVar, List<Strin
return "";
}

@Override
public void generateRecommendation(KruizeObject kruizeObject, ExperimentResultData experimentResultData) {

}

// TODO: Update these based on requirements, currently leaving Invalid as Default impl doesn't need engine
@Override
Expand All @@ -59,4 +52,9 @@ public AnalyzerConstants.RegisterRecommendationEngineStatus registerEngine(Kruiz
public List<KruizeRecommendationEngine> getEngines() {
return null;
}

@Override
public void generateRecommendation(KruizeObject kruizeObject, List<ExperimentResultData> experimentResultDataList, Timestamp interval_start_time, Timestamp interval_end_time) {

}
}
12 changes: 7 additions & 5 deletions ...totune/analyzer/performanceProfiles/PerformanceProfileInterface/PerfProfileInterface.java
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Original file line number Diff line number Diff line change
@@ -1,12 +1,9 @@
/*******************************************************************************
* Copyright (c) 2022 Red Hat, IBM Corporation and others.
*
* 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.
Expand All @@ -20,12 +17,17 @@
import com.autotune.analyzer.performanceProfiles.PerformanceProfile;
import com.autotune.common.data.result.ExperimentResultData;

import java.sql.Timestamp;
import java.util.List;

/**
* Abstraction layer containing methods for the validation of the Performance Profiles with respect to the updated experiment.
* and to parse the objective function data.
*/
public interface PerfProfileInterface {
// name, validateResults, validateProfile, recommend
// name, validateResults, validateProfile, recommend
String getName(PerformanceProfile profile);
void generateRecommendation(KruizeObject kruizeObject, ExperimentResultData experimentResultData);

void generateRecommendation(KruizeObject kruizeObject, List<ExperimentResultData> experimentResultDataList, Timestamp interval_start_time, Timestamp interval_end_time) throws Exception;

}
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