Random类取随机数的原理是什么？

首先在初始化Random实例的时候就会根据当前的时间戳生成一个种子数seed。 ```java public Random() { this(seedUniquifier() ^ System.nanoTime()); } private static long seedUniquifier() { // L'Ecuyer, "Tables of Linear Congruential Generators of // Different Sizes and Good Lattice Structure", 1999 for (;;) { long current = seedUniquifier.get(); long next = current * 181783497276652981L; if (seedUniquifier.compareAndSet(current, next)) return next; } } ``` 然后每次取随机数时是拿seed乘以一个固定值multiplier，作为随机数。 ```java protected int next(int bits) { long oldseed, nextseed; AtomicLong seed = this.seed; do { oldseed = seed.get(); nextseed = (oldseed * multiplier + addend) & mask; } while (!seed.compareAndSet(oldseed, nextseed)); return (int)(nextseed >>> (48 - bits)); } ``` 但是这样的话，多线程并发使用Math.random取随机数时，同一个时间点取到的随机数一样的概率会比较大。所以可以使用ThreadLocalRandom.current().nextInt()方法去取随机数。每个线程第一次调用ThreadLocalRandomd的current()方法时，会为这个线程生成一个线程独立的种子数seed，这样多线程并发读取随机数时，可以保证取到的随机数都是不一样的。 ```java public static ThreadLocalRandom current() { //判断这个线程是否生成种子 if (UNSAFE.getInt(Thread.currentThread(), PROBE) == 0) localInit(); return instance; } //为这个线程生成一个种子seed，并且将种子seed，和线程已生成种子的标志 存储到Unsafe类中 static final void localInit() { int p = probeGenerator.addAndGet(PROBE_INCREMENT); int probe = (p == 0) ? 1 : p; // skip 0 long seed = mix64(seeder.getAndAdd(SEEDER_INCREMENT)); Thread t = Thread.currentThread(); UNSAFE.putLong(t, SEED, seed); UNSAFE.putInt(t, PROBE, probe); } //获取随机数，根据当前种子计算随机数 public int nextInt(int origin, int bound) { if (origin >= bound) throw new IllegalArgumentException(BadRange); return internalNextInt(origin, bound); } final int internalNextInt(int origin, int bound) { int r = mix32(nextSeed()); if (origin < bound) { int n = bound - origin, m = n - 1; if ((n & m) == 0) r = (r & m) + origin; else if (n > 0) { for (int u = r >>> 1; u + m - (r = u % n) < 0; u = mix32(nextSeed()) >>> 1) ; r += origin; } else { while (r < origin || r >= bound) r = mix32(nextSeed()); } } return r; } ```