java – ThreadLocalRandom与共享静态随机实例性能比较测试

来自规格：

When applicable,use of ThreadLocalRandom rather than shared Random objects in concurrent programs will typically encounter much less overhead and contention. Use of ThreadLocalRandom is particularly appropriate when multiple tasks (for example,each a ForkJoinTask) use random numbers in parallel in thread pools.

并且：

When all usages are of this form,it is never possible to accidently share a ThreadLocalRandom across multiple threads.

所以我做了一个小测试：

public class ThreadLocalRandomTest {

private static final int THREAD_COUNT = 100;
private static final int GENERATED_NUMBER_COUNT = 1000;
private static final int INT_RIGHT_BORDER = 5000;
private static final int EXPERIMENTS_COUNT = 5000;

public static void main(String[] args) throws InterruptedException {
    System.out.println("Number of threads: " + THREAD_COUNT);
    System.out.println("Length of generated numbers chain for each thread: " + GENERATED_NUMBER_COUNT);
    System.out.println("Right border integer: " + INT_RIGHT_BORDER);
    System.out.println("Count of experiments: " + EXPERIMENTS_COUNT);

    int repeats = 0;
    int workingTime = 0;
    long startTime = 0;
    long endTime = 0;

    for (int i = 0; i < EXPERIMENTS_COUNT; i++) {
        startTime = System.currentTimeMillis();
        repeats += calculateRepeatsForSharedRandom();
        endTime = System.currentTimeMillis();
        workingTime += endTime - startTime;
    }
    System.out.println("Average repeats for shared Random instance: " + repeats / EXPERIMENTS_COUNT
            + ". Average working time: " + workingTime / EXPERIMENTS_COUNT + " ms.");

    repeats = 0;
    workingTime = 0;
    for (int i = 0; i < EXPERIMENTS_COUNT; i++) {
        startTime = System.currentTimeMillis();
        repeats += calculateRepeatsForTheadLocalRandom();
        endTime = System.currentTimeMillis();
        workingTime += endTime - startTime;
    }
    System.out.println("Average repeats for ThreadLocalRandom: " + repeats / EXPERIMENTS_COUNT
            + ". Average working time: " + workingTime / EXPERIMENTS_COUNT + " ms.");
}

private static int calculateRepeatsForSharedRandom() throws InterruptedException {
    final Random rand = new Random();
    final Map<Integer,Integer> counts = new HashMap<>();

    for (int i = 0; i < THREAD_COUNT; i++) {
        Thread thread = new Thread() {
            @Override
            public void run() {

                for (int j = 0; j < GENERATED_NUMBER_COUNT; j++) {
                    int random = rand.nextInt(INT_RIGHT_BORDER);
                    if (!counts.containsKey(random)) {
                        counts.put(random,0);
                    }
                    counts.put(random,counts.get(random) + 1);
                }
            }
        };
        thread.start();
        thread.join();
    }

    int repeats = 0;
    for (Integer value : counts.values()) {
        if (value > 1) {
            repeats += value;
        }
    }

    return repeats;
}

private static int calculateRepeatsForTheadLocalRandom() throws InterruptedException {
    final Map<Integer,Integer> counts = new HashMap<>();

    for (int i = 0; i < THREAD_COUNT; i++) {
        Thread thread = new Thread() {
            @Override
            public void run() {

                for (int j = 0; j < GENERATED_NUMBER_COUNT; j++) {
                    int random = ThreadLocalRandom.current().nextInt(INT_RIGHT_BORDER);
                    if (!counts.containsKey(random)) {
                        counts.put(random,counts.get(random) + 1);
                }
            }
        };
        thread.start();
        thread.join();
    }

    int repeats = 0;
    for (Integer value : counts.values()) {
        if (value > 1) {
            repeats += value;
        }
    }

    return repeats;
}

}

我还添加了非共享随机测试,得到了下一个结果：

Number of threads: 100
Length of generated numbers chain for each thread: 100
Right border integer: 5000
Count of experiments: 10000
Average repeats for non-shared Random instance: 8646. Average working time: 13 ms.
Average repeats for shared Random instance: 8646. Average working time: 13 ms.
Average repeats for ThreadLocalRandom: 8646. Average working time: 13 ms.

至于我,这有点奇怪,我预计至少在使用ThreadLocalRandom与共享的Random实例相比时速度会提高,但看起来没什么区别.

有人可以解释为什么它的工作方式,也许我不明白的东西.提前致谢.