最快的摘要算法XXHash算法的JAVA实现

xxHash是一个非常快的哈希算法，能在限制速度的RAM上运行。 它成功完成了SMHasher测试套件，它可以评估散列函数的冲突，色散和随机性。 代码非常便于携带，所有平台上的散列都相同（小/大）。测试对比参考：https://blog.csdn.net/tianshan2010/article/details/115775292

public class XXHash {
	
	private static final int PRIME1 = (int) 2654435761L;
	private static final int PRIME2 = (int) 2246822519L;
	private static final int PRIME3 = (int) 3266489917L;
	private static final int PRIME4 = 668265263;
	private static final int PRIME5 = 0x165667b1;
	
	public static int digestSmall(byte[] data, int seed, boolean bigendian) {
		
		final EndianReader er = bigendian ? EncodeUtils.BEReader : EncodeUtils.LEReader;
		final int len = data.length;
		final int bEnd = len;
		final int limit = bEnd - 4;
		
		int idx = seed + PRIME1;
		int crc = PRIME5;
		int i = 0;
		
		while (i < limit) {
			crc += er.toInt(data, i) + (idx++);
			crc += Integer.rotateLeft(crc, 17) * PRIME4;
			crc *= PRIME1;
			i += 4;
		}
		
		while (i < bEnd) {
			crc += (data[i] & 0xFF) + (idx++);
			crc *= PRIME1;
			i++;
		}
		
		crc += len;
		
		crc ^= crc >>> 15;
		crc *= PRIME2;
		crc ^= crc >>> 13;
		crc *= PRIME3;
		crc ^= crc >>> 16;
		
		return crc;
		
	}
	
	public static int digestFast32(byte[] data, int seed, boolean bigendian) {
		
		final int len = data.length;
		
		if (len < 16) {
			return digestSmall(data, seed, bigendian);
		}
		
		final EndianReader er = bigendian ? EncodeUtils.BEReader : EncodeUtils.LEReader;
		final int bEnd = len;
		final int limit = bEnd - 16;
		int v1 = seed + PRIME1;
		int v2 &