我认为您需要测量任务类本身（XMPTask）中的时间。在该任务中，您应该能够提取正在执行它的线程的 id 并记录它。使用这种方法需要阅读日志并对它们进行一些计算。
另一种方法是随着时间的推移保持运行总计和平均值。为此，您可以编写一个简单的类，将其传递给每个任务，该任务具有一些静态（每个 jvm）变量，用于跟踪每个线程正在做什么。然后你可以在 Threadpool 之外有一个单独的线程来进行计算。所以如果你想报告每个线程每秒的平均cpu时间，这个计算线程可以休眠一秒钟，然后计算并记录所有平均时间，然后休眠一秒钟......
编辑：重新阅读要求后，您不需要后台线程，但不确定我们是在跟踪每个线程的平均时间还是每个任务的平均时间。我假设了每个线程的总时间和平均时间，并在下面的代码中充实了这个想法。它尚未经过测试或调试，但应该让您对如何开始有一个很好的了解：
public class Runner
{
public void startRunning()
{
// Create your thread pool
ExecutorService service = Executors.newFixedThreadPool(noOfThreads);
readPropertyFiles();
MeasureTime measure = new MeasureTime();
// queue some tasks
for (int i = 0, nextId = startRange; i < noOfThreads; i++, nextId += noOfTasks)
{
service.submit(new XMPTask(nextId, noOfTasks, tableList, measure));
}
service.shutdown();
service.awaitTermination(Long.MAX_VALUE, TimeUnit.DAYS);
measure.printTotalsAndAverages();
}
}
public class MeasureTime
{
HashMap<Long, Long> threadIdToTotalCPUTimeNanos = new HashMap<Long, Long>();
HashMap<Long, Long> threadIdToStartTimeMillis = new HashMap<Long, Long>();
HashMap<Long, Long> threadIdToStartTimeNanos = new HashMap<Long, Long>();
private void addThread(Long threadId)
{
threadIdToTotalCPUTimeNanos.put(threadId, 0L);
threadIdToStartTimeMillis.put(threadId, 0L);
}
public void startTimeCount(Long threadId)
{
synchronized (threadIdToStartTimeNanos)
{
if (!threadIdToStartTimeNanos.containsKey(threadId))
{
addThread(threadId);
}
long nanos = System.nanoTime();
threadIdToStartTimeNanos.put(threadId, nanos);
}
}
public void endTimeCount(long threadId)
{
synchronized (threadIdToStartTimeNanos)
{
long endNanos = System.nanoTime();
long startNanos = threadIdToStartTimeNanos.get(threadId);
long nanos = threadIdToTotalCPUTimeNanos.get(threadId);
nanos = nanos + (endNanos - startNanos);
threadIdToTotalCPUTimeNanos.put(threadId, nanos);
}
}
public void printTotalsAndAverages()
{
long totalForAllThreadsNanos = 0L;
int numThreads = 0;
long totalWallTimeMillis = 0;
synchronized (threadIdToStartTimeNanos)
{
numThreads = threadIdToStartTimeMillis.size();
for (Long threadId: threadIdToStartTimeNanos.keySet())
{
totalWallTimeMillis += System.currentTimeMillis() - threadIdToStartTimeMillis.get(threadId);
long totalCPUTimeNanos = threadIdToTotalCPUTimeNanos.get(threadId);
totalForAllThreadsNanos += totalCPUTimeNanos;
}
}
long totalCPUMillis = (totalForAllThreadsNanos)/1000000;
System.out.println("Total milli-seconds for all threads: " + totalCPUMillis);
double averageMillis = totalCPUMillis/numThreads;
System.out.println("Average milli-seconds for all threads: " + averageMillis);
double averageCPUUtilisation = totalCPUMillis/totalWallTimeMillis;
System.out.println("Average CPU utilisation for all threads: " + averageCPUUtilisation);
}
}
public class XMPTask implements Callable<String>
{
private final MeasureTime measure;
public XMPTask(// your parameters first
MeasureTime measure)
{
// Save your things first
this.measure = measure;
}
@Override
public String call() throws Exception
{
measure.startTimeCount(Thread.currentThread().getId());
try
{
// do whatever work here that burns some CPU.
}
finally
{
measure.endTimeCount(Thread.currentThread().getId());
}
return "Your return thing";
}
}
写完这一切之后，有一件事情似乎有点奇怪，因为 XMPTask 似乎对任务列表了解太多，我认为你应该为你拥有的每个任务创建一个 XMPTask，给它足够的信息完成这项工作，并在创建它们时将它们提交给服务。