twitter的雪花算法实现(Java) - 朗度云

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源码

/ twitter的snowflake算法 -- java实现
 @author rock
* @date 2016/11/26
*/
public class SnowFlake {

    / 起始的时间戳
    */
    private final static long START_STMP = 1480166465631L;

    / 每一部分占用的位数
    */
    private final static long SEQUENCE_BIT = 12; //序列号占用的位数
    private final static long MACHINE_BIT = 5;  //机器标识占用的位数
    private final static long DATACENTER_BIT = 5;//数据中心占用的位数

    / 每一部分的最大值
    */
    private final static long MAX_DATACENTER_NUM = -1L ^ (-1L << DATACENTER_BIT);
    private final static long MAX_MACHINE_NUM = -1L ^ (-1L << MACHINE_BIT);
    private final static long MAX_SEQUENCE = -1L ^ (-1L << SEQUENCE_BIT);

    / 每一部分向左的位移
    */
    private final static long MACHINE_LEFT = SEQUENCE_BIT;
    private final static long DATACENTER_LEFT = SEQUENCE_BIT + MACHINE_BIT;
    private final static long TIMESTMP_LEFT = DATACENTER_LEFT + DATACENTER_BIT;

    private long datacenterId;  //数据中心
    private long machineId;    //机器标识
    private long sequence = 0L; //序列号
    private long lastStmp = -1L;//上一次时间戳

    public SnowFlake(long datacenterId, long machineId) {
        if (datacenterId > MAX_DATACENTER_NUM || datacenterId < 0) {
            throw new IllegalArgumentException("datacenterId can't be greater than MAX_DATACENTER_NUM or less than 0");
        }
        if (machineId > MAX_MACHINE_NUM || machineId < 0) {
            throw new IllegalArgumentException("machineId can't be greater than MAX_MACHINE_NUM or less than 0");
        }
        this.datacenterId = datacenterId;
        this.machineId = machineId;
    }

    / 产生下一个ID
     @return
    */
    public synchronized long nextId() {
        long currStmp = getNewstmp();
        if (currStmp < lastStmp) {
            throw new RuntimeException("Clock moved backwards.  Refusing to generate id");
        }

        if (currStmp == lastStmp) {
            //相同毫秒内,序列号自增
            sequence = (sequence + 1) & MAX_SEQUENCE;
            //同一毫秒的序列数已经达到最大
            if (sequence == 0L) {
                currStmp = getNextMill();
            }
        } else {
            //不同毫秒内,序列号置为0
            sequence = 0L;
        }

        lastStmp = currStmp;

        return (currStmp - START_STMP) << TIMESTMP_LEFT //时间戳部分
                | datacenterId << DATACENTER_LEFT      //数据中心部分
                | machineId << MACHINE_LEFT            //机器标识部分
                | sequence;                            //序列号部分
    }

    private long getNextMill() {
        long mill = getNewstmp();
        while (mill <= lastStmp) {
            mill = getNewstmp();
        }
        return mill;
    }

    private long getNewstmp() {
        return System.currentTimeMillis();
    }

}

可以写一代码测试一下,如下所示:

public static void main(String[] args) {
        SnowFlake snowFlake = new SnowFlake(2, 3);
        for (int i = 0; i < (1 << 12); i++) {
            System.out.println(snowFlake.nextId());
        }

    }

循环生成2^12个ID,运行结果如下:

...
2099698216995
2099698216996
2099698216997
2099698216998
2099698216999
2099698217000
2099698217001
2099698217002
2099698217003
2099698217004
2099698217005
2099698217006
2099698217007
2099698217008
2099698217009
2099698217010
2099698217011
2099698217012
2099698217013
2099698217014
2099698217015
2099698217016
2099698217017
2099698217018
2099698217019
2099698217020
2099698217021
2099698217022
2099698217023
2099698217024
2099698217025
2099698217026
2099698217027
2099698217028
2099698217029
2099698217030
2099698217031
2099702411264
2099702411265
2099702411266
2099702411267
2099702411268
2099702411269
2099702411270
2099702411271
2099702411272
2099702411273
2099702411274
2099702411275
2099702411276
2099702411277
...

可以看到生成的ID都是递增的,而且都是唯一的。

服务器的实现可以参考: 基于twitter雪花算法的分布式ID —— 服务器篇

源码已经提交在GitHub: https://github.com/beyondfengyu/SnowFlake

参考
https://github.com/beyondfengyu/SnowFlake
http://www.wolfbe.com/detail/201701/386.html

https://github.com/twitter/snowflake