Java中SnowFlake 雪花算法生成全局唯一id中的问题，时间不连续全为偶数解决

• Java实现

package com.example.mydemo.util;

/**
 * 描述: Twitter的分布式自增ID雪花算法snowflake (Java版)
 *
 * @author
 * @create 2018-03-13 12:37
 **/
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");
        }
        /**
         * 时间不连续出来全是偶数
         */

        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();
    }


    public static void main(String[] args) throws Exception {
        /**
         * 分布式数据中心id
         * 机器id
         */
        SnowFlake snowFlake = new SnowFlake(5, 6);
        System.out.println(snowFlake.nextId());
    }
}
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• 工具类：

package com.example.mydemo.util;

import java.util.Random;

public class SnowFlakeUtil {
    /**
     * 单例
     */
    private static SnowFlake snowFlake = new SnowFlake(5, 6);


    /**
     * 随机数生成器
     */
    private static Random random = new Random();

    /**
     * 通过循环一次或两次解决毫秒数不连续导致的全为偶数问题
     * 时间停顿 第一次一定是偶数 第二次一定是基数 随机 实现奇数偶数混合
     *
     * @return
     */
    public static Long getUid() {
        Long uid = null;
        for (int i = 0; i < random.nextInt(2) + 1; i++) {
            uid = snowFlake.nextId();
        }
        return uid;
    }
}
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• 使用：

/**
     * 测试雪花算法生成唯一id
     *
     * @return
     */
    @GetMapping("/snow")
    public Object snowUid() {
        return SnowFlakeUtil.getUid();
    }
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