性能测试框架

Posted 2021-04-28 FunTester

之前写过一个性能测试框架，只是针对单一的HTTP接口的测试，对于业务接口和非HTTP接口还无非适配，刚好前端时间工作中用到了，就更新了自己的测试框架，这次不再以请求为基础，而是以方法为基础，这样就可以避免了单一性，有一个base类，然后其他的各种单一性请求在单独写一个适配类就好了，如果只是临时用，直接重新实现base即可。下面分享：

package com.fun.frame.thead;
import com.fun.frame.SourceCode;import com.fun.frame.excute.Concurrent;import org.slf4j.Logger;import org.slf4j.LoggerFactory;
import java.util.ArrayList;import java.util.List;import java.util.concurrent.CountDownLatch;
import static com.fun.utils.Time.getTimeStamp;
/** * 多线程任务基类，可单独使用 */public abstract class ThreadBase<T> extends SourceCode implements Runnable {
 private static final Logger logger = LoggerFactory.getLogger(ThreadBase.class);
 /** * 任务请求执行次数 */ public int times;
 /** * 计数锁 * <p> * 会在concurrent类里面根据线程数自动设定 * </p> */ CountDownLatch countDownLatch;
 /** * 用于设置访问资源 */ public T t;
 public ThreadBase(T t) { this(); this.t = t; }
 public ThreadBase() { super(); }
 /** * groovy无法直接访问t，所以写了这个方法 * * @return */ public String getT() { return t.toString(); }
 @Override public void run() { try { before(); List<Long> t = new ArrayList<>(); long ss = getTimeStamp(); for (int i = 0; i < times; i++) { long s = getTimeStamp(); doing(); long e = getTimeStamp(); t.add(e - s); } long ee = getTimeStamp(); logger.info("执行次数：{}，总耗时：{}", times, ee - ss); Concurrent.allTimes.addAll(t); } catch (Exception e) { logger.warn("执行任务失败！", e); } finally { after(); if (countDownLatch != null) countDownLatch.countDown(); } }
 /** * 运行待测方法的之前的准备 */ protected abstract void before();
 /** * 待测方法 * * @throws Exception */ protected abstract void doing() throws Exception;
 /** * 运行待测方法后的处理 */ protected abstract void after();
 public void setCountDownLatch(CountDownLatch countDownLatch) { this.countDownLatch = countDownLatch; }
 public void setTimes(int times) { this.times = times; }
}

下面是几个实现过的基础类：

package com.fun.frame.thead;
import com.fun.httpclient.ClientManage;import com.fun.httpclient.FanLibrary;import com.fun.httpclient.GCThread;import org.apache.http.HttpStatus;import org.apache.http.client.methods.CloseableHttpResponse;import org.apache.http.client.methods.HttpRequestBase;import org.slf4j.Logger;import org.slf4j.LoggerFactory;
import java.io.IOException;
/** * http请求多线程类 */public class RequestThread extends ThreadBase {
 static Logger logger = LoggerFactory.getLogger(RequestThread.class);
 /** * 请求 */ public HttpRequestBase request;
 /** * 单请求多线程多次任务构造方法 * * @param request 被执行的请求 * @param times 每个线程运行的次数 */ public RequestThread(HttpRequestBase request, int times) { this.request = request; this.times = times; }
 @Override public void before() { request.setConfig(FanLibrary.requestConfig); GCThread.starts(); }
 @Override protected void doing() throws Exception { getResponse(request); }
 @Override protected void after() { GCThread.stop(); }
 /** * 多次执行某个请求，但是不记录日志，记录方法用 loglong * <p>此方法只适应与单个请求的重复请求，对于有业务联系的请求暂时不能适配</p> * * @param request 请求 * @throws IOException */ void getResponse(HttpRequestBase request) throws IOException { CloseableHttpResponse response = ClientManage.httpsClient.execute(request); String content = FanLibrary.getContent(response); if (response.getStatusLine().getStatusCode() != HttpStatus.SC_OK) logger.warn("响应状态码：{},响应内容：{}", content, response.getStatusLine()); if (response != null) response.close(); }}

下面是数据库的：

package com.fun.frame.thead;
import com.fun.interfaces.ImysqlBasic;import org.slf4j.Logger;import org.slf4j.LoggerFactory;
import java.sql.SQLException;
/** * 数据库多线程类 */public class QuerySqlThread extends ThreadBase {
 private static Logger logger = LoggerFactory.getLogger(QuerySqlThread.class);
 String sql;
 IMySqlBasic base;
 public QuerySqlThread(IMySqlBasic base, String sql, int times) { this.times = times; this.sql = sql; this.base = base; }
 @Override public void before() { base.getConnection(); }
 @Override protected void doing() throws SQLException { base.excuteQuerySql(sql); }
 @Override protected void after() { base.mySqlOver(); }}

下面是concurrent类：

package com.fun.frame.excute;
import com.fun.bean.PerformanceResultBean;import com.fun.frame.Save;import com.fun.frame.SourceCode;import com.fun.frame.thead.ThreadBase;import com.fun.profile.Constant;import com.fun.utils.Time;import com.fun.utils.WriteRead;import org.slf4j.Logger;import org.slf4j.LoggerFactory;
import java.util.List;import java.util.Vector;import java.util.concurrent.CountDownLatch;import java.util.concurrent.ExecutorService;import java.util.concurrent.Executors;
public class Concurrent {
 private static Logger logger = LoggerFactory.getLogger(Concurrent.class);
 /** * 线程任务 */ public ThreadBase thread;
 public List<ThreadBase> threads;
 public int num;
 public static Vector<Long> allTimes = new Vector<>();
 ExecutorService executorService;
 CountDownLatch countDownLatch;
 /** * @param thread 线程任务 * @param num 线程数 */ public Concurrent(ThreadBase thread, int num) { this(num); this.thread = thread; }
 /** * @param threads 线程组 */ public Concurrent(List<ThreadBase> threads) { this(threads.size()); this.threads = threads; }
 public Concurrent(int num) { this.num = num; executorService = Executors.newFixedThreadPool(num); countDownLatch = new CountDownLatch(num); } /** * 执行多线程任务 */ public PerformanceResultBean start() { long start = Time.getTimeStamp(); for (int i = 0; i < num; i++) { ThreadBase thread = getThread(i); thread.setCountDownLatch(countDownLatch); executorService.execute(thread); } shutdownService(executorService, countDownLatch); long end = Time.getTimeStamp(); logger.info("总计" + num + "个线程，共用时：" + Time.getTimeDiffer(start, end) + "秒！"); return over(); }
 private static void shutdownService(ExecutorService executorService, CountDownLatch countDownLatch) { try { countDownLatch.await(); executorService.shutdown(); } catch (InterruptedException e) { logger.warn("线程池关闭失败！", e); } }
 private PerformanceResultBean over() { Save.saveLongList(allTimes, num); return countQPS(num); }
 ThreadBase getThread(int i) { if (threads == null) return thread; return threads.get(i); }
 /** * 计算结果 * <p>此结果仅供参考</p> * * @param name 线程数 */ public static PerformanceResultBean countQPS(int name) { List<String> strings = WriteRead.readTxtFileByLine(Constant.LONG_Path + name + Constant.FILE_TYPE_LOG); int size = strings.size(); int sum = 0; for (int i = 0; i < size; i++) { int time = SourceCode.changeStringToInt(strings.get(i)); sum += time; } double v = 1000.0 * size * name / sum; PerformanceResultBean performanceResultBean = new PerformanceResultBean(name, size, sum / size, v); performanceResultBean.print(); return performanceResultBean; }}

redis实现类缺失，因为没有遇到需要单独实现的需求。

关于用代码还是用工具实现并发，我个人看法所有所长，单究其根本，必然是代码胜于工具，原因如下：门槛高，适应性强；贴近开发，利于调优。性能测试，并发只是开始，只有一个好的开始才能进行性能数据分析，性能参数调优。所以不必拘泥于到底使用哪个工具那种语言，据我经验来说：基本的测试需求都是能满足的，只是实现的代价不同。

groovy是一种基于JVM的动态语言，我觉得最大的优势有两点，第一：于java兼容性非常好，大部分时候吧groovy的文件后缀改成java直接可以用，反之亦然。java的绝大部分库，groovy都是可以直接拿来就用的。这还带来了另外一个有点，学习成本低，非常低，直接上手没问题，可以慢慢学习groovy不同于Java的语法；第二：编译器支持变得更好，现在用的intellij的ide，总体来说已经比较好的支持groovy语言了，写起代码来也是比较顺滑了，各种基于groovy的框架工具也比较溜，特别是Gradle构建工具，比Maven爽很多。----此段文字为了撑字数强加的，与内容无关。

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