雪花算法(分布式自增长ID)

港控/mmm° 2023-09-29 14:05 9阅读 0赞

[分布式ID生成][ID]  
[雪花算法(分布式自增长ID)][ID 1]

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## 一、简介 ##

snowflake是Twitter开源的分布式ID⽣成算法，结果是⼀个long型的ID。其核⼼思想是：使⽤41bit作为毫秒数，10bit作为机器的ID（5个bit是数据中⼼，5个bit的机器ID），12bit作为毫秒内的流⽔号（意味着每个节点在每毫秒可以产⽣ 4096 个 ID），最后还有⼀个符号位，永远是0。

![请添加图片描述][341999cad3d447de9f9506a1aed91f92.png]

## 二、文件 ##

[CSDN][]

https://download.csdn.net/download/weixin_44624117/85339346

## 三、代码 ##

package com.changgou.util;
 
 import java.lang.management.ManagementFactory;
 import java.net.InetAddress;
 import java.net.NetworkInterface;
 
 /**
 * 名称：IdWorker.java
 * 描述：分布式自增长ID
 * <pre>
 * Twitter的 Snowflake　JAVA实现方案
 * </pre>
 * 核心代码为其IdWorker这个类实现，其原理结构如下，我分别用一个0表示一位，用—分割开部分的作用：
 * 1||0---0000000000 0000000000 0000000000 0000000000 0 --- 00000 ---00000 ---000000000000
 * 在上面的字符串中，第一位为未使用（实际上也可作为long的符号位），接下来的41位为毫秒级时间，
 * 然后5位datacenter标识位，5位机器ID（并不算标识符，实际是为线程标识），
 * 然后12位该毫秒内的当前毫秒内的计数，加起来刚好64位，为一个Long型。
 * 这样的好处是，整体上按照时间自增排序，并且整个分布式系统内不会产生ID碰撞（由datacenter和机器ID作区分），
 * 并且效率较高，经测试，snowflake每秒能够产生26万ID左右，完全满足需要。
 * 
 * 64位ID (42(毫秒)+5(机器ID)+5(业务编码)+12(重复累加))
 *
 * @author Polim
 */
 public class IdWorker {
 
 // 时间起始标记点，作为基准，一般取系统的最近时间（一旦确定不能变动）
 private final static long twepoch = 1288834974657L;
 // 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;
 // 机器ID最大值
 private final static long maxWorkerId = -1L ^ (-1L << workerIdBits);
 // 数据中心ID最大值
 private final static long maxDatacenterId = -1L ^ (-1L << datacenterIdBits);
 // 毫秒内自增位
 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;
 
 private final static long sequenceMask = -1L ^ (-1L << sequenceBits);
 /* 上次生产id时间戳 */
 private static long lastTimestamp = -1L;
 // 0，并发控制
 private long sequence = 0L;
 
 private final long workerId;
 // 数据标识id部分
 private final long datacenterId;
 
 public IdWorker(){
 
 this.datacenterId = getDatacenterId(maxDatacenterId);
 this.workerId = getMaxWorkerId(datacenterId, maxWorkerId);
 }
 /**
 * @param workerId
 * 工作机器ID
 * @param datacenterId
 * 序列号
 */
 public IdWorker(long workerId, long datacenterId) {
 
 if (workerId > maxWorkerId || workerId < 0) {
 
 throw new IllegalArgumentException(String.format("worker Id can't be greater than %d or less than 0", maxWorkerId));
 }
 if (datacenterId > maxDatacenterId || datacenterId < 0) {
 
 throw new IllegalArgumentException(String.format("datacenter Id can't be greater than %d or less than 0", maxDatacenterId));
 }
 this.workerId = workerId;
 this.datacenterId = datacenterId;
 }
 /**
 * 获取下一个ID
 *
 * @return
 */
 public synchronized long nextId() {
 
 long timestamp = timeGen();
 if (timestamp < lastTimestamp) {
 
 throw new RuntimeException(String.format("Clock moved backwards. Refusing to generate id for %d milliseconds", lastTimestamp - timestamp));
 }
 
 if (lastTimestamp == timestamp) {
 
 // 当前毫秒内，则+1
 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 = 0L;
 }
 lastTimestamp = timestamp;
 // ID偏移组合生成最终的ID，并返回ID
 long nextId = ((timestamp - twepoch) << timestampLeftShift)
 | (datacenterId << datacenterIdShift)
 | (workerId << workerIdShift) | sequence;
 
 return nextId;
 }
 
 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 maxWorkerId
 * 
 */
 protected static long getMaxWorkerId(long datacenterId, long maxWorkerId) {
 
 StringBuffer mpid = new StringBuffer();
 mpid.append(datacenterId);
 String name = ManagementFactory.getRuntimeMXBean().getName();
 if (!name.isEmpty()) {
 
 /*
 * GET jvmPid
 */
 mpid.append(name.split("@")[0]);
 }
 /*
 * MAC + PID 的 hashcode 获取16个低位
 */
 return (mpid.toString().hashCode() & 0xffff) % (maxWorkerId + 1);
 }
 
 /**
 * 
 * 数据标识id部分
 * 
 */
 protected static long getDatacenterId(long maxDatacenterId) {
 
 long id = 0L;
 try {
 
 InetAddress ip = InetAddress.getLocalHost();
 NetworkInterface network = NetworkInterface.getByInetAddress(ip);
 if (network == null) {
 
 id = 1L;
 } else {
 
 byte[] mac = network.getHardwareAddress();
 id = ((0x000000FF & (long) mac[mac.length - 1])
 | (0x0000FF00 & (((long) mac[mac.length - 2]) << 8))) >> 6;
 id = id % (maxDatacenterId + 1);
 }
 } catch (Exception e) {
 
 System.out.println(" getDatacenterId: " + e.getMessage());
 }
 return id;
 }
 
 
 public static void main(String[] args) {
 
 //推特 26万个不重复的ID
 IdWorker idWorker = new IdWorker(0,0);
 for (int i = 0; i <2600 ; i++) {
 
 System.out.println(idWorker.nextId());
 }
 }
 
 }

[ID]: https://blog.csdn.net/lydms/article/details/125382642
[ID 1]: https://blog.csdn.net/lydms/article/details/124696135
[341999cad3d447de9f9506a1aed91f92.png]: https://img-blog.csdnimg.cn/341999cad3d447de9f9506a1aed91f92.png
[CSDN]: https://download.csdn.net/download/weixin_44624117/85339346