高效随机数算法Java实现

心已赠人 2022-03-18 02:50 212阅读 0赞

## 前言 ##

事情起源于一位网友分享了一个有趣的面试题：

> 生成由六位数字组成的ID，要求随机数字，不排重，不可自增，且数字不重复。ID总数为几十万。

## 初次解答 ##

我一开始想到的办法是

1.  生成一个足够大的ID池（其实就是需要多少就生成多少）
2.  对ID池中的数字进行随机排序
3.  依次消费ID池中的数字  
    可惜这个方法十分浪费空间，且性能很差。

## 初遇梅森旋转算法 ##

后面咨询了网友后得知了一个高效的随机数算法：**梅森旋转（Mersenne Twister/MT）**。通过搜索资料得知：

> 梅森旋转算法（Mersenne twister）是一个伪随机数发生算法。由松本真和西村拓士在1997年开发，基于有限二进制字段上的矩阵线性递归。可以快速产生高质量的伪随机数，修正了古典随机数发生算法的很多缺陷。

> 最为广泛使用Mersenne Twister的一种变体是MT19937，可以产生32位整数序列。

*PS：此算法依然无法完美解决面试题，但是也算学到了新知识*

## MT19937算法实现 ##

后面通过Google，找到了一个高效的**MT19937**的Java版本代码。原代码链接为http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/VERSIONS/JAVA/MTRandom.java

import java.util.Random;
 
 /**
 * MT19937的Java实现
 */
 public class MTRandom extends Random {
 
 // Constants used in the original C implementation
 private final static int UPPER_MASK = 0x80000000;
 private final static int LOWER_MASK = 0x7fffffff;
 
 private final static int N = 624;
 private final static int M = 397;
 private final static int MAGIC[] = { 0x0, 0x9908b0df };
 private final static int MAGIC_FACTOR1 = 1812433253;
 private final static int MAGIC_FACTOR2 = 1664525;
 private final static int MAGIC_FACTOR3 = 1566083941;
 private final static int MAGIC_MASK1 = 0x9d2c5680;
 private final static int MAGIC_MASK2 = 0xefc60000;
 private final static int MAGIC_SEED = 19650218;
 private final static long DEFAULT_SEED = 5489L;
 
 // Internal state
 private transient int[] mt;
 private transient int mti;
 private transient boolean compat = false;
 
 // Temporary buffer used during setSeed(long)
 private transient int[] ibuf;
 
 /**
 * The default constructor for an instance of MTRandom. This invokes
 * the no-argument constructor for java.util.Random which will result
 * in the class being initialised with a seed value obtained by calling
 * System.currentTimeMillis().
 */
 public MTRandom() { }
 
 /**
 * This version of the constructor can be used to implement identical
 * behaviour to the original C code version of this algorithm including
 * exactly replicating the case where the seed value had not been set
 * prior to calling genrand_int32.
 * 
 * If the compatibility flag is set to true, then the algorithm will be
 * seeded with the same default value as was used in the original C
 * code. Furthermore the setSeed() method, which must take a 64 bit
 * long value, will be limited to using only the lower 32 bits of the
 * seed to facilitate seamless migration of existing C code into Java
 * where identical behaviour is required.
 * 
 * Whilst useful for ensuring backwards compatibility, it is advised
 * that this feature not be used unless specifically required, due to
 * the reduction in strength of the seed value.
 *
 * @param compatible Compatibility flag for replicating original
 * behaviour.
 */
 public MTRandom(boolean compatible) {
 super(0L);
 compat = compatible;
 setSeed(compat?DEFAULT_SEED:System.currentTimeMillis());
 }
 
 /**
 * This version of the constructor simply initialises the class with
 * the given 64 bit seed value. For a better random number sequence
 * this seed value should contain as much entropy as possible.
 *
 * @param seed The seed value with which to initialise this class.
 */
 public MTRandom(long seed) {
 super(seed);
 }
 
 /**
 * This version of the constructor initialises the class with the
 * given byte array. All the data will be used to initialise this
 * instance.
 *
 * @param buf The non-empty byte array of seed information.
 * @throws NullPointerException if the buffer is null.
 * @throws IllegalArgumentException if the buffer has zero length.
 */
 public MTRandom(byte[] buf) {
 super(0L);
 setSeed(buf);
 }
 
 /**
 * This version of the constructor initialises the class with the
 * given integer array. All the data will be used to initialise
 * this instance.
 *
 * @param buf The non-empty integer array of seed information.
 * @throws NullPointerException if the buffer is null.
 * @throws IllegalArgumentException if the buffer has zero length.
 */
 public MTRandom(int[] buf) {
 super(0L);
 setSeed(buf);
 }
 
 // Initializes mt[N] with a simple integer seed. This method is
 // required as part of the Mersenne Twister algorithm but need
 // not be made public.
 private final void setSeed(int seed) {
 
 // Annoying runtime check for initialisation of internal data
 // caused by java.util.Random invoking setSeed() during init.
 // This is unavoidable because no fields in our instance will
 // have been initialised at this point, not even if the code
 // were placed at the declaration of the member variable.
 if (mt == null) mt = new int[N];
 
 // ---- Begin Mersenne Twister Algorithm ----
 mt[0] = seed;
 for (mti = 1; mti < N; mti++) {
 mt[mti] = (MAGIC_FACTOR1 * (mt[mti-1] ^ (mt[mti-1] >>> 30)) + mti);
 }
 // ---- End Mersenne Twister Algorithm ----
 }
 
 /**
 * This method resets the state of this instance using the 64
 * bits of seed data provided. Note that if the same seed data
 * is passed to two different instances of MTRandom (both of
 * which share the same compatibility state) then the sequence
 * of numbers generated by both instances will be identical.
 * 
 * If this instance was initialised in 'compatibility' mode then
 * this method will only use the lower 32 bits of any seed value
 * passed in and will match the behaviour of the original C code
 * exactly with respect to state initialisation.
 *
 * @param seed The 64 bit value used to initialise the random
 * number generator state.
 */
 public final synchronized void setSeed(long seed) {
 if (compat) {
 setSeed((int)seed);
 } else {
 
 // Annoying runtime check for initialisation of internal data
 // caused by java.util.Random invoking setSeed() during init.
 // This is unavoidable because no fields in our instance will
 // have been initialised at this point, not even if the code
 // were placed at the declaration of the member variable.
 if (ibuf == null) ibuf = new int[2];
 
 ibuf[0] = (int)seed;
 ibuf[1] = (int)(seed >>> 32);
 setSeed(ibuf);
 }
 }
 
 /**
 * This method resets the state of this instance using the byte
 * array of seed data provided. Note that calling this method
 * is equivalent to calling "setSeed(pack(buf))" and in particular
 * will result in a new integer array being generated during the
 * call. If you wish to retain this seed data to allow the pseudo
 * random sequence to be restarted then it would be more efficient
 * to use the "pack()" method to convert it into an integer array
 * first and then use that to re-seed the instance. The behaviour
 * of the class will be the same in both cases but it will be more
 * efficient.
 *
 * @param buf The non-empty byte array of seed information.
 * @throws NullPointerException if the buffer is null.
 * @throws IllegalArgumentException if the buffer has zero length.
 */
 public final void setSeed(byte[] buf) {
 setSeed(pack(buf));
 }
 
 /**
 * This method resets the state of this instance using the integer
 * array of seed data provided. This is the canonical way of
 * resetting the pseudo random number sequence.
 *
 * @param buf The non-empty integer array of seed information.
 * @throws NullPointerException if the buffer is null.
 * @throws IllegalArgumentException if the buffer has zero length.
 */
 public final synchronized void setSeed(int[] buf) {
 int length = buf.length;
 if (length == 0) throw new IllegalArgumentException("Seed buffer may not be empty");
 // ---- Begin Mersenne Twister Algorithm ----
 int i = 1, j = 0, k = (N > length ? N : length);
 setSeed(MAGIC_SEED);
 for (; k > 0; k--) {
 mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >>> 30)) * MAGIC_FACTOR2)) + buf[j] + j;
 i++; j++;
 if (i >= N) { mt[0] = mt[N-1]; i = 1; }
 if (j >= length) j = 0;
 }
 for (k = N-1; k > 0; k--) {
 mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >>> 30)) * MAGIC_FACTOR3)) - i;
 i++;
 if (i >= N) { mt[0] = mt[N-1]; i = 1; }
 }
 mt[0] = UPPER_MASK; // MSB is 1; assuring non-zero initial array
 // ---- End Mersenne Twister Algorithm ----
 }
 
 /**
 * This method forms the basis for generating a pseudo random number
 * sequence from this class. If given a value of 32, this method
 * behaves identically to the genrand_int32 function in the original
 * C code and ensures that using the standard nextInt() function
 * (inherited from Random) we are able to replicate behaviour exactly.
 * 
 * Note that where the number of bits requested is not equal to 32
 * then bits will simply be masked out from the top of the returned
 * integer value. That is to say that:
 * <pre>
 * mt.setSeed(12345);
 * int foo = mt.nextInt(16) + (mt.nextInt(16) << 16);</pre>
 * will not give the same result as
 * <pre>
 * mt.setSeed(12345);
 * int foo = mt.nextInt(32);</pre>
 *
 * @param bits The number of significant bits desired in the output.
 * @return The next value in the pseudo random sequence with the
 * specified number of bits in the lower part of the integer.
 */
 protected final synchronized int next(int bits) {
 // ---- Begin Mersenne Twister Algorithm ----
 int y, kk;
 if (mti >= N) { // generate N words at one time
 
 // In the original C implementation, mti is checked here
 // to determine if initialisation has occurred; if not
 // it initialises this instance with DEFAULT_SEED (5489).
 // This is no longer necessary as initialisation of the
 // Java instance must result in initialisation occurring
 // Use the constructor MTRandom(true) to enable backwards
 // compatible behaviour.
 
 for (kk = 0; kk < N-M; kk++) {
 y = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK);
 mt[kk] = mt[kk+M] ^ (y >>> 1) ^ MAGIC[y & 0x1];
 }
 for (;kk < N-1; kk++) {
 y = (mt[kk] & UPPER_MASK) | (mt[kk+1] & LOWER_MASK);
 mt[kk] = mt[kk+(M-N)] ^ (y >>> 1) ^ MAGIC[y & 0x1];
 }
 y = (mt[N-1] & UPPER_MASK) | (mt[0] & LOWER_MASK);
 mt[N-1] = mt[M-1] ^ (y >>> 1) ^ MAGIC[y & 0x1];
 
 mti = 0;
 }
 
 y = mt[mti++];
 
 // Tempering
 y ^= (y >>> 11);
 y ^= (y << 7) & MAGIC_MASK1;
 y ^= (y << 15) & MAGIC_MASK2;
 y ^= (y >>> 18);
 // ---- End Mersenne Twister Algorithm ----
 return (y >>> (32-bits));
 }
 
 // This is a fairly obscure little code section to pack a
 // byte[] into an int[] in little endian ordering.
 
 /**
 * This simply utility method can be used in cases where a byte
 * array of seed data is to be used to repeatedly re-seed the
 * random number sequence. By packing the byte array into an
 * integer array first, using this method, and then invoking
 * setSeed() with that; it removes the need to re-pack the byte
 * array each time setSeed() is called.
 * 
 * If the length of the byte array is not a multiple of 4 then
 * it is implicitly padded with zeros as necessary. For example:
 * <pre> byte[] { 0x01, 0x02, 0x03, 0x04, 0x05, 0x06 }</pre>
 * becomes
 * <pre> int[] { 0x04030201, 0x00000605 }</pre>
 * 
 * Note that this method will not complain if the given byte array
 * is empty and will produce an empty integer array, but the
 * setSeed() method will throw an exception if the empty integer
 * array is passed to it.
 *
 * @param buf The non-null byte array to be packed.
 * @return A non-null integer array of the packed bytes.
 * @throws NullPointerException if the given byte array is null.
 */
 public static int[] pack(byte[] buf) {
 int k, blen = buf.length, ilen = ((buf.length+3) >>> 2);
 int[] ibuf = new int[ilen];
 for (int n = 0; n < ilen; n++) {
 int m = (n+1) << 2;
 if (m > blen) m = blen;
 for (k = buf[--m]&0xff; (m & 0x3) != 0; k = (k << 8) | buf[--m]&0xff);
 ibuf[n] = k;
 }
 return ibuf;
 }
 }

## 测试 ##

### 测试代码 ###

// MT19937的Java实现
 MTRandom mtRandom=new MTRandom();
 Map<Integer,Integer> map=new HashMap<>();
 //循环次数
 int times=1000000;
 long startTime=System.currentTimeMillis();
 for(int i=0;i<times;i++){
 //使用Map去重
 map.put(mtRandom.next(32),0);
 }
 //打印循环次数
 System.out.println("times:"+times);
 //打印Map的个数
 System.out.println("num:"+map.size());
 //打印非重复比率
 System.out.println("proportion:"+map.size()/(double)times);
 //花费的时间(单位为毫秒)
 System.out.println("time:"+(System.currentTimeMillis()-startTime));

### 测试结果 ###

times:1000000
    num:999886
    proportion:0.999886
    time:374

高效随机数算法Java实现

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