java实现分布式ID自增算法snowflake

前言

snowflake可以生成全局唯一且有序的Id，相对来说UUID也可以实现，但是无序且长度太长，为36位。

• 第一位固定为0，表示正数
• 41位表示时间戳，一共可以使用69年
• 5位表示数据中心节点，5位表示机器标识，一共可以支持1024个节点
• 12位表示一毫秒内的序列号，共4096个

代码实现

/**
 * 分布式Id生成器-雪花算法
 */
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 << DATACENTER_BIT);
  private final static long MAX_MACHINE_NUM = ~(-1L << MACHINE_BIT);
  private final static long MAX_SEQUENCE = ~(-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
   */
  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4096
      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();
  }
}

测试代码

public class Main {

  public static void main(String[] args) {
    SnowFlake snowFlake = new SnowFlake(0, 0);
    for (int i = 0; i < 10; i++) {
      System.out.println(snowFlake.nextId());
    }
  }

}

输出结果

545435039291146240
545435039291146241
545435039291146242
545435039291146243
545435039291146244
545435039291146245
545435039291146246
545435039291146247
545435039291146248
545435039291146249

参考

Twitter的分布式自增ID算法snowflake (Java版)
【Java】分布式自增ID算法---雪花算法 (snowflake，Java版)
开源实现