分布式雪花算法生成Id

看到一个比较好的生产纯数字的id工具类

/**
 * 雪花算法
 */
public class SnowFlake {

    /**
     * 起始的时间戳
     */
    private final static long START_STAMP = 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 DATA_CENTER_BIT = 5;//数据中心占用的位数

    /**
     * 每一部分的最大值
     */
    private final static long MAX_DATA_CENTER_NUM = -1L ^ (-1L << DATA_CENTER_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 DATA_CENTER_LEFT = SEQUENCE_BIT + MACHINE_BIT;
    private final static long TIMESTAMP_LEFT = DATA_CENTER_LEFT + DATA_CENTER_BIT;

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

    public SnowFlake(long dataCenterId, long machineId) {
        if (dataCenterId > MAX_DATA_CENTER_NUM || dataCenterId < 0) {
            throw new IllegalArgumentException("dataCenterId can't be greater than MAX_DATA_CENTER_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");
        }
        SnowFlake.dataCenterId = dataCenterId;
        SnowFlake.machineId = machineId;
    }

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

        if (currStamp == lastStamp) {
            //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) {
                currStamp = getNextMill();
            }
        } else {
            //不同毫秒内，序列号置为0
            sequence = 0L;
        }

        lastStamp = currStamp;

        return (currStamp - START_STAMP) << TIMESTAMP_LEFT //时间戳部分
                | dataCenterId << DATA_CENTER_LEFT       //数据中心部分
                | machineId << MACHINE_LEFT             //机器标识部分
                | sequence;                             //序列号部分
    }

//    public static void main(String[] args) {
//        HashSet ids = new HashSet<>();
//        SnowFlake snowFlake = new SnowFlake(2,3);
//        int i = 0;
//        while(true){
//            if(i > 100000000){
//                break;
//            }
//            long temp = snowFlake.nextId();
//
//            if(ids.contains(temp)){
//                System.out.println("存在");
//            }
//            ids.add(temp);
//
//            i++;
//
//        }
//
//        System.out.println("结束" + snowFlake.nextId());
//    }

    private static long getNextMill() {
        long mill = getNewStamp();
        while (mill <= lastStamp) {
            mill = getNewStamp();
        }
        return mill;
    }

    private static long getNewStamp() {
        return System.currentTimeMillis();
    }

//    public static void main(String[] args) {
//        SnowFlake snowFlake = new SnowFlake(2, 3);
//
//        long start = System.currentTimeMillis();
//        for (int i = 0; i < 1000; i++) {
//            System.out.println(snowFlake.nextId());
//        }
//
//        System.out.println("总共耗时："+(System.currentTimeMillis() - start));
//    }
}