为什么要使用ThreadLocalRandom代替Random生成随机数

时间:2021-11-27 17:36:08
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java里有伪随机型和安全型两种随机数生成器,伪随机生成器根据特定公式将seed转换成新的伪随机数据的一部分,安全随机生成器在底层依赖到操作系统提供的随机事件来生成数据。

安全随机生成器

  • 需要生成加密性强的随机数据的时候才用它
  • 生成速度慢
  • 如果需要生成大量的随机数据,可能会产生阻塞需要等待外部中断事件

而伪随机生成器,只依赖于“seed”的初始值,如果给生成算法提供相同的seed,可以得到一样的伪随机序列。一般情况下,由于它是计算密集型的(不依赖于任何IO设备),因此生成速度更快。以下是伪随机生成器的进化史。

java.util.Random 
自1.0就已经存在,是一个线程安全类,理论上可以通过它同时在多个线程中获得互不相同的随机数,这样的线程安全是通过AtomicLong实现的。 
Random使用AtomicLong CAS(compare and set)操作来更新它的seed,尽管在很多非阻塞式算法中使用了非阻塞式原语,CAS在资源高度竞争时的表现依然糟糕,后面的测试结果中可以看到它的糟糕表现。

java.util.concurrent.ThreadLocalRandom 
1.7增加该类,企图将它和Random结合以克服所有的性能问题,该类继承自Random。

ThreadLocalRandom的主要实现细节:

  • 使用一个普通的long而不是使用Random中的AtomicLong作为seed
  • 不能自己创建ThreadLocalRandom实例,因为它的构造函数是私有的,可以使用它的静态工厂ThreadLocalRandom.current()
  • 它是CPU缓存感知式的,使用8个long虚拟域来填充64位L1高速缓存行

测试

下面进行5种测试:

  1. 一个单独的Random被N个线程共享
  2. ThreadLocal<Random>
  3. ThreadLocalRandom
  4. Random[], 其中每个线程N使用一个数组下标为N的Random
  5. Random[], 其中每个线程N使用一个数组下标为N * 2的Random

所有的测试都使用封装在RandomTask类里的方法,每个方案都说明了如何使用随机生成器。

import java.util.Random;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ThreadLocalRandom; public class Test_Random { private static final long COUNT = 10000000;
private static final int THREADS = 2;
public static void main(String[] args) {
// TODO Auto-generated method stub
System.out.println("Shared Random");
testRandom(THREADS, COUNT);
/*System.out.println("ThreadLocal<Random>");
testThreadLocal_Random(THREADS, COUNT);
System.out.println("ThreadLocalRandom");
testThreadLocalRandom(THREADS, COUNT);
System.out.println("Shared Random[] with no padding");
testRandomArray(THREADS, COUNT, 1);
System.out.println("Shared Random[] with padding");
testRandomArray(THREADS, COUNT, 2);*/
} private static class RandomTask implements Runnable {
private final Random rnd;
protected final int id;
private final long cnt;
private final CountDownLatch latch; private RandomTask(Random rnd, int id, long cnt,
CountDownLatch latch) {
super();
this.rnd = rnd;
this.id = id;
this.cnt = cnt;
this.latch = latch;
} protected Random getRandom() {
return rnd;
} @Override
public void run() {
try {
final Random r = getRandom();
latch.countDown();
latch.await();
final long start = System.currentTimeMillis();
int sum = 0;
for (long j = 0; j < cnt; j++) {
sum += r.nextInt();
}
final long time = System.currentTimeMillis() - start;
System.out.println("Thread #" + id + " Time = " + time / 1000.0 + " sec, sum = " + sum);
} catch (InterruptedException e) {}
}
} private static void testRandom(final int threads, final long cnt) {
final CountDownLatch latch = new CountDownLatch(threads);
final Random r = new Random(100);
for (int i = 0; i < threads; ++i) {
final Thread thread = new Thread(new RandomTask(r, i, cnt, latch));
thread.start();
}
} private static void testRandomArray(final int threads, final long cnt, final int padding) {
final CountDownLatch latch = new CountDownLatch(threads);
final Random[] rnd = new Random[threads * padding];
for (int i = 0; i < threads * padding; ++i) {
rnd[i] = new Random(100);
}
for (int i = 0; i < threads; ++i) {
final Thread thread = new Thread(new RandomTask(rnd[i * padding], i, cnt, latch));
thread.start();
}
} private static void testThreadLocalRandom(final int threads, final long cnt) {
final CountDownLatch latch = new CountDownLatch(threads);
for (int i = 0; i < threads; ++i) {
final Thread thread = new Thread(new RandomTask(null, i, cnt, latch) {
@Override
protected Random getRandom() {
// TODO Auto-generated method stub
return ThreadLocalRandom.current();
}
});
thread.start();
}
} private static void testThreadLocal_Random(final int threads, final long cnt) {
final CountDownLatch latch = new CountDownLatch(threads);
final ThreadLocal<Random> rnd = new ThreadLocal<Random>() { @Override
protected Random initialValue() {
// TODO Auto-generated method stub
return new Random(100);
} };
for (int i = 0; i < threads; ++i) {
final Thread thread = new Thread(new RandomTask(null, i, cnt, latch) { @Override
protected Random getRandom() {
// TODO Auto-generated method stub
return rnd.get();
} });
thread.start();
}
}
}

总结:

  • 任何情况下都不要在多个线程间共享一个Random实例,而该把它放入ThreadLocal之中
  • java7在所有情形下都更推荐使用ThreadLocalRandom,它向下兼容已有的代码且运营成本更低