前言
-
暂时不深入研究该类，不做过多解读，功能比较单一，就是生生一个随机数字（伪随机）。有空研究一下随机数生成算法，以及为什么是伪随机。
-
此类的实例用于生成伪随机数流。
-
该类使用48位种子，可以使用线性同余公式对其进行修改。
-
（请参见Donald Knuth，计算机编程艺术，第2卷，第3.2.1节）。
-
如果使用相同的种子创建了两个{@code Random}实例，并且对每个实例进行了相同的方法调用序列，则它们将生成并返回相同的数字序列。
-
为了保证此属性，为类{@code Random}指定了特定的算法。
-
为了实现Java代码的绝对可移植性，Java实现必须将此处显示的所有算法用于{@code Random}类。
-
但是，{@code Random}类的子类可以使用其他算法，只要它们遵守所有方法的常规协定即可。
-
由{@code Random}类实现的算法使用{@code protected}实用程序方法，该方法在每次调用时最多可以提供32个伪随机生成的位。
-
{@code java.util.Random}的实例是线程安全的。
-
但是，跨线程同时使用同一{@code java.util.Random}实例可能会引起争用并因此导致性能下降。
-
考虑在多线程设计中改用{@link java.util.concurrent.ThreadLocalRandom}。
-
{@code java.util.Random}的实例不是加密安全的。
-
考虑改为使用{@link java.security.SecureRandom}来获取加密安全的伪随机数生成器，以供对安全敏感的应用程序使用。
源码
package java.util;
*/
public
class Random implements java.io.Serializable {
/** use serialVersionUID from JDK 1.1 for interoperability */
static final long serialVersionUID = 3905348978240129619L;
private final AtomicLong seed;
private static final long multiplier = 0x5DEECE66DL;
private static final long addend = 0xBL;
private static final long mask = (1L << 48) - 1;
private static final double DOUBLE_UNIT = 0x1.0p-53; // 1.0 / (1L << 53)
static final String BadBound = "bound must be positive";
static final String BadRange = "bound must be greater than origin";
static final String BadSize = "size must be non-negative";
/**
* 创建一个新的随机数生成器。
* 该构造函数将随机数生成器的种子设置为一个很有可能与该构造函数的任何其他调用不同的值。
*/
public Random() {
this(seedUniquifier() ^ System.nanoTime());
}
private static long seedUniquifier() {
for (;;) {
long current = seedUniquifier.get();
long next = current * 181783497276652981L;
if (seedUniquifier.compareAndSet(current, next))
return next;
}
}
private static final AtomicLong seedUniquifier
= new AtomicLong(8682522807148012L);
/**
* Creates a new random number generator using a single {@code long} seed.
* The seed is the initial value of the internal state of the pseudorandom
* number generator which is maintained by method {@link #next}.
*
* <p>The invocation {@code new Random(seed)} is equivalent to:
* <pre> {@code
* Random rnd = new Random();
* rnd.setSeed(seed);}</pre>
*
* @param seed the initial seed
* @see #setSeed(long)
*/
public Random(long seed) {
if (getClass() == Random.class)
this.seed = new AtomicLong(initialScramble(seed));
else {
// subclass might have overriden setSeed
this.seed = new AtomicLong();
setSeed(seed);
}
}
private static long initialScramble(long seed) {
return (seed ^ multiplier) & mask;
}
/**
* Sets the seed of this random number generator using a single
* {@code long} seed. The general contract of {@code setSeed} is
* that it alters the state of this random number generator object
* so as to be in exactly the same state as if it had just been
* created with the argument {@code seed} as a seed. The method
* {@code setSeed} is implemented by class {@code Random} by
* atomically updating the seed to
* <pre>{@code (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)}</pre>
* and clearing the {@code haveNextNextGaussian} flag used by {@link
* #nextGaussian}.
*
* <p>The implementation of {@code setSeed} by class {@code Random}
* happens to use only 48 bits of the given seed. In general, however,
* an overriding method may use all 64 bits of the {@code long}
* argument as a seed value.
*
* @param seed the initial seed
*/
synchronized public void setSeed(long seed) {
this.seed.set(initialScramble(seed));
haveNextNextGaussian = false;
}
/**
* Generates the next pseudorandom number. Subclasses should
* override this, as this is used by all other methods.
*
* <p>The general contract of {@code next} is that it returns an
* {@code int} value and if the argument {@code bits} is between
* {@code 1} and {@code 32} (inclusive), then that many low-order
* bits of the returned value will be (approximately) independently
* chosen bit values, each of which is (approximately) equally
* likely to be {@code 0} or {@code 1}. The method {@code next} is
* implemented by class {@code Random} by atomically updating the seed to
* <pre>{@code (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)}</pre>
* and returning
* <pre>{@code (int)(seed >>> (48 - bits))}.</pre>
*
* This is a linear congruential pseudorandom number generator, as
* defined by D. H. Lehmer and described by Donald E. Knuth in
* <i>The Art of Computer Programming,</i> Volume 3:
* <i>Seminumerical Algorithms</i>, section 3.2.1.
*
* @param bits random bits
* @return the next pseudorandom value from this random number
* generator's sequence
* @since 1.1
*/
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));
}
/**
* Generates random bytes and places them into a user-supplied
* byte array. The number of random bytes produced is equal to
* the length of the byte array.
*
* <p>The method {@code nextBytes} is implemented by class {@code Random}
* as if by:
* <pre> {@code
* public void nextBytes(byte[] bytes) {
* for (int i = 0; i < bytes.length; )
* for (int rnd = nextInt(), n = Math.min(bytes.length - i, 4);
* n-- > 0; rnd >>= 8)
* bytes[i++] = (byte)rnd;
* }}</pre>
*
* @param bytes the byte array to fill with random bytes
* @throws NullPointerException if the byte array is null
* @since 1.1
*/
public void nextBytes(byte[] bytes) {
for (int i = 0, len = bytes.length; i < len; )
for (int rnd = nextInt(),
n = Math.min(len - i, Integer.SIZE/Byte.SIZE);
n-- > 0; rnd >>= Byte.SIZE)
bytes[i++] = (byte)rnd;
}
/**
* The form of nextLong used by LongStream Spliterators. If
* origin is greater than bound, acts as unbounded form of
* nextLong, else as bounded form.
*
* @param origin the least value, unless greater than bound
* @param bound the upper bound (exclusive), must not equal origin
* @return a pseudorandom value
*/
final long internalNextLong(long origin, long bound) {
long r = nextLong();
if (origin < bound) {
long n = bound - origin, m = n - 1;
if ((n & m) == 0L) // power of two
r = (r & m) + origin;
else if (n > 0L) { // reject over-represented candidates
for (long u = r >>> 1; // ensure nonnegative
u + m - (r = u % n) < 0L; // rejection check
u = nextLong() >>> 1) // retry
;
r += origin;
}
else { // range not representable as long
while (r < origin || r >= bound)
r = nextLong();
}
}
return r;
}
final int internalNextInt(int origin, int bound) {
if (origin < bound) {
int n = bound - origin;
if (n > 0) {
return nextInt(n) + origin;
}
else { // range not representable as int
int r;
do {
r = nextInt();
} while (r < origin || r >= bound);
return r;
}
}
else {
return nextInt();
}
}
final double internalNextDouble(double origin, double bound) {
double r = nextDouble();
if (origin < bound) {
r = r * (bound - origin) + origin;
if (r >= bound) // correct for rounding
r = Double.longBitsToDouble(Double.doubleToLongBits(bound) - 1);
}
return r;
}
public int nextInt() {
return next(32);
}
public int nextInt(int bound) {
if (bound <= 0)
throw new IllegalArgumentException(BadBound);
int r = next(31);
int m = bound - 1;
if ((bound & m) == 0) // i.e., bound is a power of 2
r = (int)((bound * (long)r) >> 31);
else {
for (int u = r;
u - (r = u % bound) + m < 0;
u = next(31))
;
}
return r;
}
public long nextLong() {
// it's okay that the bottom word remains signed.
return ((long)(next(32)) << 32) + next(32);
}
public boolean nextBoolean() {
return next(1) != 0;
}
public float nextFloat() {
return next(24) / ((float)(1 << 24));
}
public double nextDouble() {
return (((long)(next(26)) << 27) + next(27)) * DOUBLE_UNIT;
}
private double nextNextGaussian;
private boolean haveNextNextGaussian = false;
synchronized public double nextGaussian() {
// See Knuth, ACP, Section 3.4.1 Algorithm C.
if (haveNextNextGaussian) {
haveNextNextGaussian = false;
return nextNextGaussian;
} else {
double v1, v2, s;
do {
v1 = 2 * nextDouble() - 1; // between -1 and 1
v2 = 2 * nextDouble() - 1; // between -1 and 1
s = v1 * v1 + v2 * v2;
} while (s >= 1 || s == 0);
double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s);
nextNextGaussian = v2 * multiplier;
haveNextNextGaussian = true;
return v1 * multiplier;
}
}
public IntStream ints(long streamSize) {
if (streamSize < 0L)
throw new IllegalArgumentException(BadSize);
return StreamSupport.intStream
(new RandomIntsSpliterator
(this, 0L, streamSize, Integer.MAX_VALUE, 0),
false);
}
public IntStream ints() {
return StreamSupport.intStream
(new RandomIntsSpliterator
(this, 0L, Long.MAX_VALUE, Integer.MAX_VALUE, 0),
false);
}
public IntStream ints(long streamSize, int randomNumberOrigin,
int randomNumberBound) {
if (streamSize < 0L)
throw new IllegalArgumentException(BadSize);
if (randomNumberOrigin >= randomNumberBound)
throw new IllegalArgumentException(BadRange);
return StreamSupport.intStream
(new RandomIntsSpliterator
(this, 0L, streamSize, randomNumberOrigin, randomNumberBound),
false);
}
public IntStream ints(int randomNumberOrigin, int randomNumberBound) {
if (randomNumberOrigin >= randomNumberBound)
throw new IllegalArgumentException(BadRange);
return StreamSupport.intStream
(new RandomIntsSpliterator
(this, 0L, Long.MAX_VALUE, randomNumberOrigin, randomNumberBound),
false);
}
public LongStream longs(long streamSize) {
if (streamSize < 0L)
throw new IllegalArgumentException(BadSize);
return StreamSupport.longStream
(new RandomLongsSpliterator
(this, 0L, streamSize, Long.MAX_VALUE, 0L),
false);
}
public LongStream longs() {
return StreamSupport.longStream
(new RandomLongsSpliterator
(this, 0L, Long.MAX_VALUE, Long.MAX_VALUE, 0L),
false);
}
public LongStream longs(long streamSize, long randomNumberOrigin,
long randomNumberBound) {
if (streamSize < 0L)
throw new IllegalArgumentException(BadSize);
if (randomNumberOrigin >= randomNumberBound)
throw new IllegalArgumentException(BadRange);
return StreamSupport.longStream
(new RandomLongsSpliterator
(this, 0L, streamSize, randomNumberOrigin, randomNumberBound),
false);
}
public LongStream longs(long randomNumberOrigin, long randomNumberBound) {
if (randomNumberOrigin >= randomNumberBound)
throw new IllegalArgumentException(BadRange);
return StreamSupport.longStream
(new RandomLongsSpliterator
(this, 0L, Long.MAX_VALUE, randomNumberOrigin, randomNumberBound),
false);
}
public DoubleStream doubles(long streamSize) {
if (streamSize < 0L)
throw new IllegalArgumentException(BadSize);
return StreamSupport.doubleStream
(new RandomDoublesSpliterator
(this, 0L, streamSize, Double.MAX_VALUE, 0.0),
false);
}
public DoubleStream doubles() {
return StreamSupport.doubleStream
(new RandomDoublesSpliterator
(this, 0L, Long.MAX_VALUE, Double.MAX_VALUE, 0.0),
false);
}
public DoubleStream doubles(long streamSize, double randomNumberOrigin,
double randomNumberBound) {
if (streamSize < 0L)
throw new IllegalArgumentException(BadSize);
if (!(randomNumberOrigin < randomNumberBound))
throw new IllegalArgumentException(BadRange);
return StreamSupport.doubleStream
(new RandomDoublesSpliterator
(this, 0L, streamSize, randomNumberOrigin, randomNumberBound),
false);
}
public DoubleStream doubles(double randomNumberOrigin, double randomNumberBound) {
if (!(randomNumberOrigin < randomNumberBound))
throw new IllegalArgumentException(BadRange);
return StreamSupport.doubleStream
(new RandomDoublesSpliterator
(this, 0L, Long.MAX_VALUE, randomNumberOrigin, randomNumberBound),
false);
}
static final class RandomIntsSpliterator implements Spliterator.OfInt {
final Random rng;
long index;
final long fence;
final int origin;
final int bound;
RandomIntsSpliterator(Random rng, long index, long fence,
int origin, int bound) {
this.rng = rng; this.index = index; this.fence = fence;
this.origin = origin; this.bound = bound;
}
public RandomIntsSpliterator trySplit() {
long i = index, m = (i + fence) >>> 1;
return (m <= i) ? null :
new RandomIntsSpliterator(rng, i, index = m, origin, bound);
}
public long estimateSize() {
return fence - index;
}
public int characteristics() {
return (Spliterator.SIZED | Spliterator.SUBSIZED |
Spliterator.NONNULL | Spliterator.IMMUTABLE);
}
public boolean tryAdvance(IntConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(rng.internalNextInt(origin, bound));
index = i + 1;
return true;
}
return false;
}
public void forEachRemaining(IntConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
Random r = rng;
int o = origin, b = bound;
do {
consumer.accept(r.internalNextInt(o, b));
} while (++i < f);
}
}
}
static final class RandomLongsSpliterator implements Spliterator.OfLong {
final Random rng;
long index;
final long fence;
final long origin;
final long bound;
RandomLongsSpliterator(Random rng, long index, long fence,
long origin, long bound) {
this.rng = rng; this.index = index; this.fence = fence;
this.origin = origin; this.bound = bound;
}
public RandomLongsSpliterator trySplit() {
long i = index, m = (i + fence) >>> 1;
return (m <= i) ? null :
new RandomLongsSpliterator(rng, i, index = m, origin, bound);
}
public long estimateSize() {
return fence - index;
}
public int characteristics() {
return (Spliterator.SIZED | Spliterator.SUBSIZED |
Spliterator.NONNULL | Spliterator.IMMUTABLE);
}
public boolean tryAdvance(LongConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(rng.internalNextLong(origin, bound));
index = i + 1;
return true;
}
return false;
}
public void forEachRemaining(LongConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
Random r = rng;
long o = origin, b = bound;
do {
consumer.accept(r.internalNextLong(o, b));
} while (++i < f);
}
}
}
static final class RandomDoublesSpliterator implements Spliterator.OfDouble {
final Random rng;
long index;
final long fence;
final double origin;
final double bound;
RandomDoublesSpliterator(Random rng, long index, long fence,
double origin, double bound) {
this.rng = rng; this.index = index; this.fence = fence;
this.origin = origin; this.bound = bound;
}
public RandomDoublesSpliterator trySplit() {
long i = index, m = (i + fence) >>> 1;
return (m <= i) ? null :
new RandomDoublesSpliterator(rng, i, index = m, origin, bound);
}
public long estimateSize() {
return fence - index;
}
public int characteristics() {
return (Spliterator.SIZED | Spliterator.SUBSIZED |
Spliterator.NONNULL | Spliterator.IMMUTABLE);
}
public boolean tryAdvance(DoubleConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(rng.internalNextDouble(origin, bound));
index = i + 1;
return true;
}
return false;
}
public void forEachRemaining(DoubleConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
Random r = rng;
double o = origin, b = bound;
do {
consumer.accept(r.internalNextDouble(o, b));
} while (++i < f);
}
}
}
/**
* Serializable fields for Random.
*
* @serialField seed long
* seed for random computations
* @serialField nextNextGaussian double
* next Gaussian to be returned
* @serialField haveNextNextGaussian boolean
* nextNextGaussian is valid
*/
private static final ObjectStreamField[] serialPersistentFields = {
new ObjectStreamField("seed", Long.TYPE),
new ObjectStreamField("nextNextGaussian", Double.TYPE),
new ObjectStreamField("haveNextNextGaussian", Boolean.TYPE)
};
/**
* Reconstitute the {@code Random} instance from a stream (that is,
* deserialize it).
*/
private void readObject(java.io.ObjectInputStream s)
throws java.io.IOException, ClassNotFoundException {
ObjectInputStream.GetField fields = s.readFields();
// The seed is read in as {@code long} for
// historical reasons, but it is converted to an AtomicLong.
long seedVal = fields.get("seed", -1L);
if (seedVal < 0)
throw new java.io.StreamCorruptedException(
"Random: invalid seed");
resetSeed(seedVal);
nextNextGaussian = fields.get("nextNextGaussian", 0.0);
haveNextNextGaussian = fields.get("haveNextNextGaussian", false);
}
/**
* Save the {@code Random} instance to a stream.
*/
synchronized private void writeObject(ObjectOutputStream s)
throws IOException {
// set the values of the Serializable fields
ObjectOutputStream.PutField fields = s.putFields();
// The seed is serialized as a long for historical reasons.
fields.put("seed", seed.get());
fields.put("nextNextGaussian", nextNextGaussian);
fields.put("haveNextNextGaussian", haveNextNextGaussian);
// save them
s.writeFields();
}
// Support for resetting seed while deserializing
private static final Unsafe unsafe = Unsafe.getUnsafe();
private static final long seedOffset;
static {
try {
seedOffset = unsafe.objectFieldOffset
(Random.class.getDeclaredField("seed"));
} catch (Exception ex) { throw new Error(ex); }
}
private void resetSeed(long seedVal) {
unsafe.putObjectVolatile(this, seedOffset, new AtomicLong(seedVal));
}
}
```
#### 问题记录
* SecureRandom 如何保证安全？
* Random ThreadLocalRandom 如何实现？
* 为什么叫伪随机数？随机数生成算法？
