原文地址：http://www.cnblogs.com/relucent/p/4955340.html
概述
分佈式系統中，有一些需要使用全局唯一ID的場景，這種時候爲了防止ID衝突可以使用36位的UUID，但是UUID有一些缺點，首先他相對比較長，另外UUID一般是無序的。
有些時候我們希望能使用一種簡單一些的ID，並且希望ID能夠按照時間有序生成。
而twitter的snowflake解決了這種需求，最初Twitter把存儲系統從MySQL遷移到Cassandra，因爲Cassandra沒有順序ID生成機制，所以開發了這樣一套全局唯一ID生成服務。
結構
snowflake的結構如下(每部分用-分開):
0 - 0000000000 0000000000 0000000000 0000000000 0 - 00000 - 00000 - 000000000000
第一位爲未使用，接下來的41位爲毫秒級時間(41位的長度可以使用69年)，然後是5位datacenterId和5位workerId(10位的長度最多支持部署1024個節點） ，最後12位是毫秒內的計數（12位的計數順序號支持每個節點每毫秒產生4096個ID序號）
一共加起來剛好64位，爲一個Long型。(轉換成字符串長度爲18)
snowflake生成的ID整體上按照時間自增排序，並且整個分佈式系統內不會產生ID碰撞（由datacenter和workerId作區分），並且效率較高。據說：snowflake每秒能夠產生26萬個ID。
源碼
(JAVA版本的源碼)
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/**
Snowflake */public class IdWorker
{ private final long twepoch
= 1288834974657L; private final long workerIdBits
= 5L; private final long datacenterIdBits
= 5L; private final long maxWorkerId
= -1L ^ (-1L << workerIdBits); private final long maxDatacenterId
= -1L ^ (-1L << datacenterIdBits); private final long sequenceBits
= 12L; private final long workerIdShift
= sequenceBits; private final long datacenterIdShift
= sequenceBits + workerIdBits; private final long timestampLeftShift
= sequenceBits + workerIdBits + datacenterIdBits; private final long sequenceMask
= -1L ^ (-1L << sequenceBits); private long workerId; private long datacenterId; private long sequence
= 0L; private long lastTimestamp
= -1L; public IdWorker(long workerId, long datacenterId)
{ if (workerId
> maxWorkerId || workerId < 0)
{ throw new IllegalArgumentException(String.format("worker
Id can't be greater than %d or less than 0",
maxWorkerId)); } if (datacenterId
> maxDatacenterId || datacenterId < 0)
{ throw new IllegalArgumentException(String.format("datacenter
Id can't be greater than %d or less than 0",
maxDatacenterId)); } this.workerId
= workerId; this.datacenterId
= datacenterId; } public synchronized long nextId()
{ long timestamp
= timeGen(); if (timestamp
< lastTimestamp) { throw new RuntimeException(String.format("Clock
moved backwards. Refusing to generate id for %d milliseconds",
lastTimestamp - timestamp)); } if (lastTimestamp
== timestamp) { sequence
= (sequence + 1)
& sequenceMask; if (sequence
== 0)
{ timestamp
= tilNextMillis(lastTimestamp); } } else { sequence
= 0L; } lastTimestamp
= timestamp; return ((timestamp
- twepoch) << timestampLeftShift) | (datacenterId << datacenterIdShift) | (workerId << workerIdShift) | sequence; } protected long tilNextMillis(long lastTimestamp)
{ long timestamp
= timeGen(); while (timestamp
<= lastTimestamp) { timestamp
= timeGen(); } return timestamp; } protected long timeGen()
{ return System.currentTimeMillis(); } public static void main(String[]
args) { IdWorker
idWorker = new IdWorker(0, 0); for (int i
= 0;
i < 1000;
i++) { long id
= idWorker.nextId(); System.out.println(id); } }} |
參考
https://github.com/twitter/snowflake