写在前面
传说自然界中并不存在两片完全一样的雪花的,每一片雪花都拥有自己漂亮独特的形状、独一无二;雪花算法也表示生成的ID如雪花般独一无二,该算法源自Twitter。
雪花算法主要用于解决分布式系统的唯一Id生成问题,在生产环境中可以部署一个单独的服务来运行雪花算法,然后通过请求该服务获取全局Id。
相对于UUID来说,其长度短,生成快,做数据库主键时方便建立索引,所以整体效率要高很多。
代码实现
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
public class IdWorker
{
//机器ID
private static long workerId;
private static long twepoch = 687888001020L; //唯一时间,这是一个避免重复的随机量,自行设定不要大于当前时间戳
private static long sequence = 0L;
private static int workerIdBits = 4; //机器码字节数。4个字节用来保存机器码(定义为Long类型会出现,最大偏移64位,所以左移64位没有意义)
public static long maxWorkerId = -1L ^ -1L << workerIdBits; //最大机器ID
private static int sequenceBits = 10; //计数器字节数,10个字节用来保存计数码
private static int workerIdShift = sequenceBits; //机器码数据左移位数,就是后面计数器占用的位数
private static int timestampLeftShift = sequenceBits + workerIdBits; //时间戳左移动位数就是机器码和计数器总字节数
public static long sequenceMask = -1L ^ -1L << sequenceBits; //一微秒内可以产生计数,如果达到该值则等到下一微妙在进行生成
private long lastTimestamp = -1L;
/// <summary>
/// 机器码
/// </summary>
/// <param name="workerId"></param>
public IdWorker(long workerId)
{
if (workerId > maxWorkerId || workerId < 0)
throw new Exception(string.Format("worker Id can't be greater than {0} or less than 0 ", workerId));
IdWorker.workerId = workerId;
}
public long nextId()
{
lock (this)
{
long timestamp = timeGen();
if (this.lastTimestamp == timestamp)
{ //同一微妙中生成ID
IdWorker.sequence = (IdWorker.sequence + 1) & IdWorker.sequenceMask; //用&运算计算该微秒内产生的计数是否已经到达上限
if (IdWorker.sequence == 0)
{
//一微妙内产生的ID计数已达上限,等待下一微妙
timestamp = tillNextMillis(this.lastTimestamp);
}
}
else
{ //不同微秒生成ID
IdWorker.sequence = 0; //计数清0
}
if (timestamp < lastTimestamp)
{ //如果当前时间戳比上一次生成ID时时间戳还小,抛出异常,因为不能保证现在生成的ID之前没有生成过
throw new Exception(string.Format("Clock moved backwards. Refusing to generate id for {0} milliseconds",
this.lastTimestamp - timestamp));
}
this.lastTimestamp = timestamp; //把当前时间戳保存为最后生成ID的时间戳
long nextId = (timestamp - twepoch << timestampLeftShift) | IdWorker.workerId << IdWorker.workerIdShift | IdWorker.sequence;
return nextId;
}
}
/// <summary>
/// 获取下一微秒时间戳
/// </summary>
/// <param name="lastTimestamp"></param>
/// <returns></returns>
private long tillNextMillis(long lastTimestamp)
{
long timestamp = timeGen();
while (timestamp <= lastTimestamp)
{
timestamp = timeGen();
}
return timestamp;
}
/// <summary>
/// 生成当前时间戳
/// </summary>
/// <returns></returns>
private long timeGen()
{
return (long)(DateTime.UtcNow - new DateTime(1970, 1, 1, 0, 0, 0, DateTimeKind.Utc)).TotalMilliseconds;
}
}
/// <summary>
/// 生成雪花ID
/// </summary>
public static class SnowFlake
{
private static long _workerId = 9;
private static IdWorker _idWorker = null;
public static string NewId()
{
if (_idWorker == null)
_idWorker = new IdWorker(_workerId);
return _idWorker.nextId().ToString();
}
}
调用示例
var id = SnowFlake.NewId();
MessageBox.Show(id.ToString());
注意事项
需要注意的是雪花算法严重依赖时间,所以当发生服务器时钟回拨的问题是会导致可能产生重复的id。当然实际基本不会发生这种情况,生产环境中很少会回调服务器系统时间,如果实在要回拨时间也可以通过调整步长参数来解决。