下面的代码测试了将www.google.com读入BufferedReader的响应时间。我计划使用此代码来测试Intranet中其他站点和Web服务的响应时间。以下测试运行20秒，每秒打开4个请求：
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.net.URL;
import java.net.URLConnection;
import java.util.Map.Entry;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.TimeUnit;
import org.junit.Test;
public class ResponseTimeTest {
private static final int NUMBER_REQUESTS_PER_SECOND = 4;
private static final int TEST_EXECUTION_TIME = 20000;
private static final ConcurrentHashMap<Long, Long> timingMap = new ConcurrentHashMap<Long, Long>();
@Test
public void testResponseTime() throws InterruptedException {
ScheduledExecutorService scheduler = Executors.newScheduledThreadPool(10);
scheduler.scheduleAtFixedRate(new RequestThreadCreator(), 0, 1, TimeUnit.SECONDS);
Thread.sleep(TEST_EXECUTION_TIME);
System.out.println("Start Time, End Time, Total Time");
for (Entry<Long, Long> entry : timingMap.entrySet())
{
System.out.println(entry.getKey() + "," + entry.getValue() +","+(entry.getValue() - entry.getKey()));
}
}
private final class RequestThreadCreator implements Runnable {
public void run() {
ExecutorService es = Executors.newCachedThreadPool();
for (int i = 1; i <= NUMBER_REQUESTS_PER_SECOND; i++) {
es.execute(new RequestThread());
}
es.shutdown();
}
}
private final class RequestThread implements Runnable {
public void run() {
long startTime = System.currentTimeMillis();
try {
URL oracle = new URL("http://www.google.com/");
URLConnection yc = oracle.openConnection();
BufferedReader in = new BufferedReader(new InputStreamReader(yc.getInputStream()));
while ((in.readLine()) != null) {
}
in.close();
} catch (Exception e) {
e.printStackTrace();
}
long endTime = System.currentTimeMillis();
timingMap.put(startTime, endTime);
}
}
}
输出结果为：
Start Time, End Time, Total Time
1417692221531,1417692221956,425
1417692213530,1417692213869,339
1417692224530,1417692224983,453
1417692210534,1417692210899,365
1417692214530,1417692214957,427
1417692220530,1417692221041,511
1417692209530,1417692209949,419
1417692215532,1417692215950,418
1417692214533,1417692215075,542
1417692213531,1417692213897,366
1417692212530,1417692212924,394
1417692219530,1417692219897,367
1417692226532,1417692226876,344
1417692211530,1417692211955,425
1417692209529,1417692209987,458
1417692222531,1417692222967,436
1417692215533,1417692215904,371
1417692219531,1417692219954,423
1417692215530,1417692215870,340
1417692217531,1417692218035,504
1417692207547,1417692207882,335
1417692208535,1417692208898,363
1417692207544,1417692208095,551
1417692208537,1417692208958,421
1417692226533,1417692226899,366
1417692224531,1417692224951,420
1417692225529,1417692225957,428
1417692216530,1417692216963,433
1417692223541,1417692223884,343
1417692223546,1417692223959,413
1417692222530,1417692222954,424
1417692208532,1417692208871,339
1417692207536,1417692207988,452
1417692226538,1417692226955,417
1417692220531,1417692220992,461
1417692209531,1417692209953,422
1417692226531,1417692226959,428
1417692217532,1417692217944,412
1417692210533,1417692210964,431
1417692221530,1417692221870,340
1417692216531,1417692216959,428
1417692207535,1417692208021,486
1417692223548,1417692223957,409
1417692216532,1417692216904,372
1417692214535,1417692215071,536
1417692217530,1417692217835,305
1417692213529,1417692213954,425
1417692210531,1417692210964,433
1417692212529,1417692212993,464
1417692213532,1417692213954,422
1417692215531,1417692215957,426
1417692210529,1417692210868,339
1417692218531,1417692219102,571
1417692225530,1417692225907,377
1417692208536,1417692208966,430
1417692218533,1417692219168,635
由于System.out.println为synchronized，为了不扭曲结果，我将时序添加到ConcurrentHashMap，并且不在RequestThread本身内输出时序。在上面的代码中我应该注意其他问题，以免扭曲结果。或者是否有我应该专注的区域以提高准确度，或者是否足够精确到足够精确到100毫秒。