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‎LICENSE.md

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The MIT License (MIT)
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Copyright (c) 2016 Eugene Morozov
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎README.md

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# Anomaly Detection in Performance Test Data
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## Overview
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Example of Spring Boot, Cucumber, JMeter and R integration that demonstrates
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anomaly detection in performance test data.
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This demo was shown at DataScienceLab Data Science in FinTech meetup
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(http://www.meetup.com/data-science-lab/events/227113953).
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## Configuration
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Configuration is hardcoded to demo the integration, update JMeter and Rscript
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paths in `src/test/java/com/emorozov/datasciencelab/DataScienceLabDemoTestPerformanceAnomaliesSteps.java`
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before you start.
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## R Integration
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Once R is installed, install the packages manually prior to running Cucumeber files.
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This is a workaround for package installation failing from Java Runtime.exec().
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```
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install.packages('dplyr')
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install.packages('tidyr')
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install.packages('mvoutlier')
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install.packages('jsonlite')
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```
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## R Specifics
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Since sample is very small (only 50 runs taking about 10 seconds), CPU metrics
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tend to introduce significant number of outliers.
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In the current implementation cpu metrics are excluded in the
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`performance-anomalies.R` script.
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## Todo
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1. Create more generic Cucumber step definitions, so that mvoutlier
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parameters can be passed into the script from feature files.
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1. Make sure that dependencies are checked in R script and installed
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automatically.
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1. Refactor config, so paths are not hardcoded.

‎pom.xml

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<?xml version="1.0" encoding="UTF-8"?>
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<groupId>com.example</groupId>
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<artifactId>datasciencelab-demo</artifactId>
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<version>0.0.1-SNAPSHOT</version>
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<parent>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-starter-parent</artifactId>
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<version>1.3.1.RELEASE</version>
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</parent>
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<properties>
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<maven.compiler.plugin.version>3.3</maven.compiler.plugin.version>
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<lombok.version>1.16.6</lombok.version>
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<junit.version>4.12</junit.version>
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<hamcrest.version>1.3</hamcrest.version>
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<jmeter.version>2.13</jmeter.version>
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<cucumber.java.version>1.2.4</cucumber.java.version>
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</properties>
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<build>
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<plugins>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-compiler-plugin</artifactId>
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<version>${maven.compiler.plugin.version}</version>
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<configuration>
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<source>1.8</source>
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<target>1.8</target>
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</configuration>
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</plugin>
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</plugins>
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</build>
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<dependencies>
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<dependency>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-starter-web</artifactId>
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</dependency>
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<dependency>
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<groupId>org.projectlombok</groupId>
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<artifactId>lombok</artifactId>
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<version>${lombok.version}</version>
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<scope>provided</scope>
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</dependency>
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<dependency>
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<groupId>org.apache.jmeter</groupId>
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<artifactId>ApacheJMeter_monitors</artifactId>
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<version>${jmeter.version}</version>
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<scope>test</scope>
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<exclusions>
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<exclusion>
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<artifactId>commons-math3</artifactId>
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<groupId>commons-math3</groupId>
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</exclusion>
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<exclusion>
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<artifactId>commons-pool2</artifactId>
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<groupId>commons-pool2</groupId>
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</exclusion>
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</exclusions>
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</dependency>
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<dependency>
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<groupId>org.apache.jmeter</groupId>
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<artifactId>ApacheJMeter_java</artifactId>
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<version>${jmeter.version}</version>
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<scope>test</scope>
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<exclusions>
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<exclusion>
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<artifactId>commons-math3</artifactId>
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<groupId>commons-math3</groupId>
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</exclusion>
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<exclusion>
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<artifactId>commons-pool2</artifactId>
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<groupId>commons-pool2</groupId>
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</exclusion>
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</exclusions>
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</dependency>
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<dependency>
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<groupId>junit</groupId>
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<artifactId>junit</artifactId>
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<version>${junit.version}</version>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>org.hamcrest</groupId>
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<artifactId>hamcrest-all</artifactId>
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<version>${hamcrest.version}</version>
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</dependency>
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<dependency>
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<groupId>info.cukes</groupId>
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<artifactId>cucumber-java</artifactId>
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<version>${cucumber.java.version}</version>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>info.cukes</groupId>
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<artifactId>cucumber-junit</artifactId>
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<version>${cucumber.java.version}</version>
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<scope>test</scope>
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</dependency>
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</dependencies>
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</project>

‎src/main/java/com/emorozov/datasciencelab/DataScienceLabDemo.java

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package com.emorozov.datasciencelab;
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import org.springframework.boot.SpringApplication;
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import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
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import org.springframework.web.bind.annotation.RequestMapping;
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import org.springframework.web.bind.annotation.RestController;
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import java.util.Random;
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@RestController
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@EnableAutoConfiguration
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public class DataScienceLabDemo {
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public static final Random random = new Random();
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@RequestMapping("/users")
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public String users() throws Exception {
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Thread.sleep((long) (random.nextGaussian() * 20) + 100);
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// Comment out additional sleep statement below to see the tests passing
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if (random.nextInt(100) > 80) {
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Thread.sleep(200);
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}
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return "Return some users.";
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}
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@RequestMapping("/trades")
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public String trades() throws Exception {
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Thread.sleep((long) (random.nextGaussian() * 20) + 100);
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return "Return some trades.";
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}
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public static void main(String[] args) throws Exception {
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SpringApplication.run(DataScienceLabDemo.class, args);
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}
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}

‎src/test/java/com/emorozov/datasciencelab/DataScienceLabDemoTest.java

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package com.emorozov.datasciencelab;
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import org.junit.runner.RunWith;
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import cucumber.api.junit.Cucumber;
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@RunWith(Cucumber.class)
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public class DataScienceLabDemoTest {
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}

‎src/test/java/com/emorozov/datasciencelab/DataScienceLabDemoTestPerformanceAnomaliesSteps.java

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package com.emorozov.datasciencelab;
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import com.emorozov.datasciencelab.sampler.CpuSampler;
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import com.fasterxml.jackson.annotation.JsonCreator;
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import com.fasterxml.jackson.annotation.JsonProperty;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import cucumber.api.java.Before;
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import cucumber.api.java.en.Given;
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import cucumber.api.java.en.Then;
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import cucumber.api.java.en.When;
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import lombok.AllArgsConstructor;
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import lombok.Data;
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import org.apache.jmeter.control.LoopController;
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import org.apache.jmeter.engine.StandardJMeterEngine;
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import org.apache.jmeter.protocol.http.sampler.HTTPSampler;
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import org.apache.jmeter.reporters.ResultCollector;
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import org.apache.jmeter.testelement.TestPlan;
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import org.apache.jmeter.threads.ThreadGroup;
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import org.apache.jmeter.util.JMeterUtils;
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import org.apache.jorphan.collections.HashTree;
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import java.io.File;
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import java.nio.file.Files;
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import java.nio.file.Paths;
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import java.util.List;
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import java.util.stream.Stream;
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import static org.hamcrest.MatcherAssert.assertThat;
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import static org.hamcrest.number.OrderingComparison.lessThan;
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public class DataScienceLabDemoTestPerformanceAnomaliesSteps {
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@Data
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public class Endpoint {
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private String domain;
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private int port;
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private String path;
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private String method;
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}
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@Data
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@AllArgsConstructor
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private static class RInput {
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private String metrics;
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private Integer samplerCount;
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private Double criticalQiantile;
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}
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@Data
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private static class ROutput {
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private Integer outliers;
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@JsonCreator
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public ROutput(@JsonProperty("outliers") Integer outliers) {
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this.outliers = outliers;
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}
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}
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private int samplersCount = 0;
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@Before
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public void clearTemporaryFiles() throws Exception {
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Files.deleteIfExists(Paths.get("metrics.csv"));
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Files.deleteIfExists(Paths.get("input.json"));
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Files.deleteIfExists(Paths.get("output.json"));
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}
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@Given("^endpoints are up and running$")
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public void systemEndpointsAreUpAndRunning(final List<Endpoint> endpoints) throws Exception {
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// TODO Actually validate that endpoints are up and running
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}
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@When("^(.+) requests are submitted for endpoints$")
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public void requestsAreSubmitted(final Integer loops,
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final List<Endpoint> endpoints) {
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// Set status vars - number of endpoints and a CPU sampler
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this.samplersCount = endpoints.size() + 1;
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// Create JMeter engine
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StandardJMeterEngine jmeter = new StandardJMeterEngine();
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// Init JMeter engine
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// TODO Refactor config
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JMeterUtils.setJMeterHome("JMETER_HOME");
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JMeterUtils.loadJMeterProperties("JMETER_HOME/bin/jmeter.properties");
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JMeterUtils.initLocale();
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// Build samplers, use path for name of the sampler
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Stream<HTTPSampler> httpSamplers = endpoints.stream().map(endpoint -> {
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HTTPSampler httpSampler = new HTTPSampler();
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httpSampler.setName(endpoint.getPath());
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httpSampler.setDomain(endpoint.getDomain());
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httpSampler.setPort(endpoint.getPort());
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httpSampler.setPath(endpoint.getPath());
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httpSampler.setMethod(endpoint.getMethod());
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return httpSampler;
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});
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// Build a CPU sampler
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CpuSampler cpuSampler = new CpuSampler();
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cpuSampler.setName("cpu");
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// Loop Controller
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LoopController loopController = new LoopController();
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loopController.setName("Default Loop Controller");
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loopController.setLoops(loops);
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loopController.setFirst(true);
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loopController.initialize();
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// Thread Group
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org.apache.jmeter.threads.ThreadGroup threadGroup = new ThreadGroup();
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threadGroup.setName("Default Thread Group");
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threadGroup.setNumThreads(1);
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threadGroup.setRampUp(1);
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threadGroup.setSamplerController(loopController);
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// Create results collector
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ResultCollector logger = new ResultCollector();
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logger.setName("Default Results Collector");
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logger.setFilename("metrics.csv");
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// Create a test structure
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HashTree testPlanTree = new HashTree();
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// Add Test Plan
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TestPlan testPlan = new TestPlan("Sample R integration test plan");
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testPlanTree.add(testPlan);
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// Hang off Thread Group off Test Plan
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HashTree threadGroupHashTree = testPlanTree.add(testPlan, threadGroup);
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// Add samplers
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threadGroupHashTree.add(httpSamplers.toArray());
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threadGroupHashTree.add(cpuSampler);
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// Add logger
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testPlanTree.add(testPlan, logger);
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// Run Test Plan
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jmeter.configure(testPlanTree);
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jmeter.run();
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threadGroup.waitThreadsStopped();
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}
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@Then("^metrics outliers are below (.+) percent with critical quantile (.+)$")
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public void outliersAcrossInputAreBelowThreshold(final Integer outliersThreshold,
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final Double criticalQuantile)
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throws Exception {
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// Get the object mapper
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ObjectMapper mapper = new ObjectMapper();
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// Create inputs for analytics
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RInput input = new RInput("metrics.csv", this.samplersCount, criticalQuantile);
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mapper.writeValue(new File("input.json"), input);
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// Run analytics
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// TODO Refactor config
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Runtime rt = Runtime.getRuntime();
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Process pr = rt.exec("Rscript ./src/test/r/performance-anomalies.R");
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pr.waitFor();
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// Get the outputs
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ROutput output = mapper.readValue(new File("output.json"), ROutput.class);
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// Assert
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assertThat(output.getOutliers(), lessThan(outliersThreshold));
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}
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}

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