https://www.cnblogs.com/shiningrise/p/5727895.html
http://blog.csdn.net/w200221626/article/details/52064976
/// <summary>
/// 动态生产有规律的ID Snowflake算法是Twitter的工程师为实现递增而不重复的ID实现的
/// http://blog.csdn.net/w200221626/article/details/52064976
/// C# 实现 Snowflake算法
/// </summary>
public class Snowflake
{
private static long machineId;//机器ID
private static long datacenterId = 0L;//数据ID
private static long sequence = 0L;//计数从零开始
private static long twepoch = 687888001020L; //唯一时间随机量
private static long machineIdBits = 5L; //机器码字节数
private static long datacenterIdBits = 5L;//数据字节数
public static long maxMachineId = -1L ^ -1L << (int)machineIdBits; //最大机器ID
private static long maxDatacenterId = -1L ^ (-1L << (int)datacenterIdBits);//最大数据ID
private static long sequenceBits = 12L; //计数器字节数，12个字节用来保存计数码
private static long machineIdShift = sequenceBits; //机器码数据左移位数，就是后面计数器占用的位数
private static long datacenterIdShift = sequenceBits + machineIdBits;
private static long timestampLeftShift = sequenceBits + machineIdBits + datacenterIdBits; //时间戳左移动位数就是机器码+计数器总字节数+数据字节数
public static long sequenceMask = -1L ^ -1L << (int)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 static long lastTimestamp = -1L;//最后时间戳
private static object syncRoot = new object();//加锁对象
static Snowflake snowflake;
public static Snowflake Instance()
{
if (snowflake == null)
snowflake = new Snowflake();
return snowflake;
}
public Snowflake()
{
Snowflakes(0L, -1);
}
public Snowflake(long machineId)
{
Snowflakes(machineId, -1);
}
public Snowflake(long machineId, long datacenterId)
{
Snowflakes(machineId, datacenterId);
}
private void Snowflakes(long machineId, long datacenterId)
{
if (machineId >= 0)
{
if (machineId > maxMachineId)
{
throw new Exception("机器码ID非法");
}
Snowflake.machineId = machineId;
}
if (datacenterId >= 0)
{
if (datacenterId > maxDatacenterId)
{
throw new Exception("数据中心ID非法");
}
Snowflake.datacenterId = datacenterId;
}
}
/// <summary>
/// 生成当前时间戳
/// </summary>
/// <returns>毫秒</returns>
private static long GetTimestamp()
{
//让他2000年开始
return (long)(DateTime.UtcNow - new DateTime(2000, 1, 1, 0, 0, 0, DateTimeKind.Utc)).TotalMilliseconds;
}
/// <summary>
/// 获取下一微秒时间戳
/// </summary>
/// <param name="lastTimestamp"></param>
/// <returns></returns>
private static long GetNextTimestamp(long lastTimestamp)
{
long timestamp = GetTimestamp();
int count = 0;
while (timestamp <= lastTimestamp)//这里获取新的时间,可能会有错,这算法与comb一样对机器时间的要求很严格
{
count++;
if (count > 10)
throw new Exception("机器的时间可能不对");
Thread.Sleep(1);
timestamp = GetTimestamp();
}
return timestamp;
}
/// <summary>
/// 获取长整形的ID
/// </summary>
/// <returns></returns>
public long GetId()
{
lock (syncRoot)
{
long timestamp = GetTimestamp();
if (Snowflake.lastTimestamp == timestamp)
{ //同一微妙中生成ID
sequence = (sequence + 1) & sequenceMask; //用&运算计算该微秒内产生的计数是否已经到达上限
if (sequence == 0)
{
//一微妙内产生的ID计数已达上限，等待下一微妙
timestamp = GetNextTimestamp(Snowflake.lastTimestamp);
}
}
else
{
//不同微秒生成ID
sequence = 0L;
}
if (timestamp < lastTimestamp)
{
throw new Exception("时间戳比上一次生成ID时时间戳还小，故异常");
}
Snowflake.lastTimestamp = timestamp; //把当前时间戳保存为最后生成ID的时间戳
long Id = ((timestamp - twepoch) << (int)timestampLeftShift)
| (datacenterId << (int)datacenterIdShift)
| (machineId << (int)machineIdShift)
| sequence;
return Id;
}
}
}
[TestClass]
public class SnowflakeUnitTest1
{
/// <summary>
/// 动态生产有规律的ID Snowflake算法是Twitter的工程师为实现递增而不重复的ID实现的
/// </summary>
[TestMethod]
public void SnowflakeTestMethod1()
{
var ids = new List<long>();
for (int i = 0; i < 1000000; i++)//测试同时100W有序ID
{
ids.Add(Snowflake.Instance().GetId());
}
for (int i = 0; i < ids.Count - 1; i++)
{
Assert.IsTrue(ids[i] < ids[i+1]);
}
}
}
namespace ConsoleApplicationTester
{
class Program
{
static void Main(string[] args)
{
for (int i = 0; i < 1000; i++)
{
Console.WriteLine("开始执行 " + DateTime.Now.ToString("yyyy-MM-dd HH:mm:ss:ffffff") + " " + Snowflake.Instance().GetId());
Console.WriteLine("Snowflake.maxMachineId:" + Snowflake.maxMachineId);
}
}
}
}
