java 生成分布式Id ---- 雪花算法

测试：

用 setnx 往 redis 里插 100万条 看是否有重复的   后面又往数据库插 100万，id为主键

package com...uitl;
import java.lang.management.ManagementFactory;
import java.lang.management.RuntimeMXBean;
import java.net.NetworkInterface;
import java.net.SocketException;
import java.util.Enumeration;/**
 * id自增器（雪花算法）
 *
 * @author renjie
 * @version 1.0.0
 */
public class SnowFlake {



    private final static long twepoch = 12888349746579L;
    // 机器标识位数
    private final static long workerIdBits = 5L;
    // 数据中心标识位数
    private final static long datacenterIdBits = 5L;

    // 毫秒内自增位数
    private final static long sequenceBits = 12L;
    // 机器ID偏左移12位
    private final static long workerIdShift = sequenceBits;
    // 数据中心ID左移17位
    private final static long datacenterIdShift = sequenceBits + workerIdBits;
    // 时间毫秒左移22位
    private final static long timestampLeftShift = sequenceBits + workerIdBits + datacenterIdBits;
    //sequence掩码，确保sequnce不会超出上限
    private final static long sequenceMask = -1L ^ (-1L << sequenceBits);
    //上次时间戳
    private static long lastTimestamp = -1L;
    //序列
    private long sequence = 0L;
    //服务器ID
    private long workerId = 1L;
    private static long workerMask = -1L ^ (-1L << workerIdBits);
    //进程编码
    private long processId = 1L;
    private static long processMask = -1L ^ (-1L << datacenterIdBits);

    private static SnowFlake snowFlake = null;

    static{
        snowFlake = new SnowFlake();
    }
    public static synchronized long nextId(){
        return snowFlake.getNextId();
    }

    private SnowFlake() {

        //获取机器编码
        this.workerId=this.getMachineNum();
        //获取进程编码
        RuntimeMXBean runtimeMXBean = ManagementFactory.getRuntimeMXBean();
        this.processId=Long.valueOf(runtimeMXBean.getName().split("@")[0]).longValue();

        //避免编码超出最大值
        this.workerId=workerId & workerMask;
        this.processId=processId & processMask;
    }

    public synchronized long getNextId() {
        //获取时间戳
        long timestamp = timeGen();
        //如果时间戳小于上次时间戳则报错
        if (timestamp < lastTimestamp) {
            try {
                throw new Exception("Clock moved backwards.  Refusing to generate id for " + (lastTimestamp - timestamp) + " milliseconds");
            } catch (Exception e) {
                e.printStackTrace();
            }
        }
        //如果时间戳与上次时间戳相同
        if (lastTimestamp == timestamp) {
            // 当前毫秒内，则+1，与sequenceMask确保sequence不会超出上限
            sequence = (sequence + 1) & sequenceMask;
            if (sequence == 0) {
                // 当前毫秒内计数满了，则等待下一秒
                timestamp = tilNextMillis(lastTimestamp);
            }
        } else {
            sequence = 0;
        }
        lastTimestamp = timestamp;
        // ID偏移组合生成最终的ID，并返回ID
        long nextId = ((timestamp - twepoch) << timestampLeftShift) | (processId << datacenterIdShift) | (workerId << workerIdShift) | sequence;
        return nextId;
    }

    /**
     * 再次获取时间戳直到获取的时间戳与现有的不同
     * @param lastTimestamp
     * @return 下一个时间戳
     */
    private long tilNextMillis(final long lastTimestamp) {
        long timestamp = this.timeGen();
        while (timestamp <= lastTimestamp) {
            timestamp = this.timeGen();
        }
        return timestamp;
    }

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

    /**
     * 获取机器编码
     * @return
     */
    private long getMachineNum(){
        long machinePiece;
        StringBuilder sb = new StringBuilder();
        Enumeration<NetworkInterface> e = null;
        try {
            e = NetworkInterface.getNetworkInterfaces();
        } catch (SocketException e1) {
            e1.printStackTrace();
        }
        while (e.hasMoreElements()) {
            NetworkInterface ni = e.nextElement();
            sb.append(ni.toString());
        }
        machinePiece = sb.toString().hashCode();
        return machinePiece;
    }

    public static void main(String[] args) {
        for(int i=0;i<1000000;i++){
            Long userId = SnowFlake.nextId();
//            System.out.println(userId);
            String id = userId.toString();
            int n = i;
            if(id.length()!=19){
                System.out.println(id);
            }
            if(n==999999){
                System.out.println("999999: "+id);
            }
            try {
                //用 setnx 往 redis 里插 100万条 看是否有重复的
                boolean serchRedis = RedisUtil.setnx(userId.toString(),userId.toString());
            } catch (Exception e) {

                e.printStackTrace();
                System.out.println(userId);
            }
        }
      }
    }

测试结果： 

redis 100万条整  

数据库 ：