雪花算法(SnowflakeIdWorker)生成分布式唯一id

SpringUtil辅助类与SnowflakeIdWorkerID生成器
文章展示了SpringUtil工具类,它用于方便地从Spring上下文中获取Bean,包括检查Bean是否存在、获取单例或指定类型的Bean等。另外,还介绍了一个SnowflakeIdWorker类,用于生成基于Snowflake算法的分布式唯一ID,它包含了ID的结构、生成逻辑以及如何获取下一个ID的方法。

1.SpringUtil.java


import org.springframework.aop.framework.AopContext;
import org.springframework.beans.BeansException;
import org.springframework.beans.factory.NoSuchBeanDefinitionException;
import org.springframework.beans.factory.config.BeanFactoryPostProcessor;
import org.springframework.beans.factory.config.ConfigurableListableBeanFactory;
import org.springframework.stereotype.Component;

import java.lang.annotation.Annotation;
import java.util.Map;

@Component
public final class SpringUtils implements BeanFactoryPostProcessor
{
    /** Spring应用上下文环境 */
    private static ConfigurableListableBeanFactory beanFactory;

    @Override
    public void postProcessBeanFactory(ConfigurableListableBeanFactory beanFactory) throws BeansException
    {
        SpringUtils.beanFactory = beanFactory;
    }

    /**
     * 获取对象
     *
     * @param name
     * @return Object 一个以所给名字注册的bean的实例
     * @throws org.springframework.beans.BeansException
     *
     */
    @SuppressWarnings("unchecked")
    public static <T> T getBean(String name) throws BeansException
    {
        return (T) beanFactory.getBean(name);
    }

    /**
     * 获取类型为requiredType的对象
     *
     * @param clz
     * @return
     * @throws org.springframework.beans.BeansException
     *
     */
    public static <T> T getBean(Class<T> clz) throws BeansException
    {
        T result = (T) beanFactory.getBean(clz);
        return result;
    }

    /**
     * 如果BeanFactory包含一个与所给名称匹配的bean定义,则返回true
     *
     * @param name
     * @return boolean
     */
    public static boolean containsBean(String name)
    {
        return beanFactory.containsBean(name);
    }

    /**
     * 判断以给定名字注册的bean定义是一个singleton还是一个prototype。 如果与给定名字相应的bean定义没有被找到,将会抛出一个异常(NoSuchBeanDefinitionException)
     *
     * @param name
     * @return boolean
     * @throws org.springframework.beans.factory.NoSuchBeanDefinitionException
     *
     */
    public static boolean isSingleton(String name) throws NoSuchBeanDefinitionException
    {
        return beanFactory.isSingleton(name);
    }

    /**
     * @param name
     * @return Class 注册对象的类型
     * @throws org.springframework.beans.factory.NoSuchBeanDefinitionException
     *
     */
    public static Class<?> getType(String name) throws NoSuchBeanDefinitionException
    {
        return beanFactory.getType(name);
    }

    /**
     * 如果给定的bean名字在bean定义中有别名,则返回这些别名
     *
     * @param name
     * @return
     * @throws org.springframework.beans.factory.NoSuchBeanDefinitionException
     *
     */
    public static String[] getAliases(String name) throws NoSuchBeanDefinitionException
    {
        return beanFactory.getAliases(name);
    }

    /**
     * 获取aop代理对象
     *
     * @param invoker
     * @return
     */
    @SuppressWarnings("unchecked")
    public static <T> T getAopProxy(T invoker)
    {
        return (T) AopContext.currentProxy();
    }

    /**
     * 根据注解类型获取bean
     *
     * @param clz 注解类型
     * @return bean集合
     */
    public static Map<String, Object> getBeansByAnnotation(Class<? extends Annotation> clz) {
        return beanFactory.getBeansWithAnnotation(clz);
    }
}

2.SnowflakeIdWorker.java

public class SnowflakeIdWorker {
    // ==============================Fields==================
    /** 开始时间截 (2019-08-06) */
    private final long twepoch = 1565020800000L;

    /** 机器id所占的位数 */
    private final long workerIdBits = 5L;

    /** 数据标识id所占的位数 */
    private final long datacenterIdBits = 5L;

    /** 支持的最大机器id,结果是31 (这个移位算法可以很快的计算出几位二进制数所能表示的最大十进制数) */
    private final long maxWorkerId = -1L ^ (-1L << workerIdBits);

    /** 支持的最大数据标识id,结果是31 */
    private final long maxDatacenterId = -1L ^ (-1L << datacenterIdBits);

    /** 序列在id中占的位数 */
    private final long sequenceBits = 12L;

    /** 机器ID向左移12位 */
    private final long workerIdShift = sequenceBits;

    /** 数据标识id向左移17位(12+5) */
    private final long datacenterIdShift = sequenceBits + workerIdBits;

    /** 时间截向左移22位(5+5+12) */
    private final long timestampLeftShift = sequenceBits + workerIdBits + datacenterIdBits;

    /** 生成序列的掩码,这里为4095 (0b111111111111=0xfff=4095) */
    private final long sequenceMask = -1L ^ (-1L << sequenceBits);

    /** 工作机器ID(0~31) */
    private long workerId;

    /** 数据中心ID(0~31) */
    private long datacenterId;

    /** 毫秒内序列(0~4095) */
    private long sequence = 0L;

    /** 上次生成ID的时间截 */
    private long lastTimestamp = -1L;

    //==============================Constructors====================
    /**
     * 构造函数
     * @param workerId 工作ID (0~31)
     * @param datacenterId 数据中心ID (0~31)
     */
    public SnowflakeIdWorker(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;
    }

    // ==============================Methods=================================
    /**
     * 获得下一个ID (该方法是线程安全的)
     * @return SnowflakeId
     */
    public synchronized long nextId() {
        long timestamp = timeGen();

        //如果当前时间小于上一次ID生成的时间戳,说明系统时钟回退过这个时候应当抛出异常
        if (timestamp < lastTimestamp) {
            throw new RuntimeException(
                    String.format("Clock moved backwards.  Refusing to generate id for %d milliseconds", lastTimestamp - timestamp));
        }

        //如果是同一时间生成的,则进行毫秒内序列
        if (lastTimestamp == timestamp) {
            sequence = (sequence + 1) & sequenceMask;
            //毫秒内序列溢出
            if (sequence == 0) {
                //阻塞到下一个毫秒,获得新的时间戳
                timestamp = tilNextMillis(lastTimestamp);
            }
        }
        //时间戳改变,毫秒内序列重置
        else {
            sequence = 0L;
        }

        //上次生成ID的时间截
        lastTimestamp = timestamp;

        //移位并通过或运算拼到一起组成64位的ID
        return ((timestamp - twepoch) << timestampLeftShift) //
                | (datacenterId << datacenterIdShift) //
                | (workerId << workerIdShift) //
                | sequence;
    }

    /**
     * 阻塞到下一个毫秒,直到获得新的时间戳
     * @param lastTimestamp 上次生成ID的时间截
     * @return 当前时间戳
     */
    protected long tilNextMillis(long lastTimestamp) {
        long timestamp = timeGen();
        while (timestamp <= lastTimestamp) {
            timestamp = timeGen();
        }
        return timestamp;
    }

    /**
     * 返回以毫秒为单位的当前时间
     * @return 当前时间(毫秒)
     */
    protected long timeGen() {
        return System.currentTimeMillis();
    }

    //==============================Test=============================================
    /** 测试 */
    public static void main(String[] args) {
        SnowflakeIdWorker idWorker = new SnowflakeIdWorker(0, 0);
        for (int i = 0; i < 10; i++) {
            long id = idWorker.nextId();
            //System.out.println(Long.toBinaryString(id));
            System.out.println(id);
        }
    }
}

3.id生成工具类

public class IdGenerateUtils {
    private IdGenerateUtils() {}

    public static Long getId() {
        SnowflakeIdWorker worker = SpringUtils.getBean(SnowflakeIdWorker.class);
        return worker.nextId();
    }
}
高并发分布式系统中生成全局唯一Id汇总 数据在分片时,典型的是分库分表,就有一个全局ID生成的问题。 单纯的生成全局ID并不是什么难题,但是生成ID通常要满足分片的一些要求: 1 不能有单点故障。 2 以时间为序,或者ID里包含时间。这样一是可以少一个索引,二是冷热数据容易分离。 3 可以控制ShardingId。比如某一个用户的文章要放在同一个分片内,这样查询效率高,修改也容易。 4 不要太长,最好64bit。使用long比较好操作,如果是96bit,那就要各种移位相当的不方便,还有可能有些组件不能支持这么大的ID。 一 twitter twitter在把存储系统从MySQL迁移到Cassandra的过程中由于Cassandra没有顺序ID生成机制,于是自己开发了一套全局唯一ID生成服务:Snowflake。 1 41位的时间序列(精确到毫秒,41位的长度可以使用69年) 2 10位的机器标识(10位的长度最多支持部署1024个节点) 3 12位的计数顺序号(12位的计数顺序号支持每个节点每毫秒产生4096个ID序号) 最高位是符号位,始终为0。 优点:高性能,低延迟;独立的应用;按时间有序。 缺点:需要独立的开发和部署。 原理 java 实现代码 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 public class IdWorker { private final long workerId; private final static long twepoch = 1288834974657L; private long sequence = 0L; private final static long workerIdBits = 4L; public final static long maxWorkerId = -1L ^ -1L << workerIdBits; private final static long sequenceBits = 10L; private final static long workerIdShift = sequenceBits; private final static long timestampLeftShift = sequenceBits + workerIdBits; public final static long sequenceMask = -1L ^ -1L < this.maxWorkerId || workerId < 0) { throw new IllegalArgumentException(String.format( "worker Id can't be greater than %d or less than 0", this.maxWorkerId)); } this.workerId = workerId; } public synchronized long nextId() { long timestamp = this.timeGen(); if (this.lastTimestamp == timestamp) { this.sequence = (this.sequence + 1) & this.sequenceMask; if (this.sequence == 0) { System.out.println("###########" + sequenceMask); timestamp = this.tilNextMillis(this.lastTimestamp); } } else { this.sequence = 0; } if (timestamp < this.lastTimestamp) { try { throw new Exception( String.format( "Clock moved backwards. Refusing to generate id for %d milliseconds", this.lastTimestamp - timestamp)); } catch (Exception e) { e.printStackTrace(); } } this.lastTimestamp = timestamp; long nextId = ((timestamp - twepoch << timestampLeftShift)) | (this.workerId << this.workerIdShift) | (this.sequence); System.out.println("timestamp:" + timestamp + ",timestampLeftShift:" + timestampLeftShift + ",nextId:" + nextId + ",workerId:" + workerId + ",sequence:" + 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(); } public static void main(String[] args){ IdWorker worker2 = new IdWorker(2); System.out.println(worker2.nextId()); } }
### Java 实现雪花算法生成唯一ID #### 1. 雪花算法简介 雪花算法是一种用于分布式系统中高效生成全局唯一ID的方法。该方法由Twitter开源,能够生成不重复的、有序的64位整数型ID,在高并发场景下依然保持良好的性能[^3]。 #### 2. Snowflake ID结构解析 一个标准的Snowflake ID是由多个部分组成: - **时间戳(41 bit)**:记录的是从纪元(通常是2022年1月1日)到当前时刻经过了多少毫秒; - **数据中心ID (5 bit)**:用来区分不同的数据中心; - **机器节点ID (5 bit)**:在同一数据中心内进一步细分不同服务器实例; - **序列号(12 bit)** :同一台机器上每毫秒内的计数值; 这种设计使得即使在网络分区的情况下也能保证全球范围内的唯一性[^1]。 #### 3. Java代码实现 下面是一个简单的Java版本的SnowFlake类定义及其使用方式: ```java public class SnowflakeIdWorker { private final long workerId; private final long datacenterId; // 时间偏移量,默认设置为2022-01-01 private static final long twepoch = 1640995200000L; // 各个字段所占bit数 private static final int WORKER_ID_BITS = 5; private static final int DATACENTER_ID_BITS = 5; private static final int SEQUENCE_BITS = 12; // 最大支持machine数量=31, 即允许的最大dataCenter数量也是31 public static final long MAX_WORKER_ID = ~(-1L << WORKER_ID_BITS); public static final long MAX_DATACENTER_ID = ~(-1L << DATACENTER_ID_BITS); // 移动位置计算 private static final long WORKER_ID_SHIFT = SEQUENCE_BITS; private static final long DATACENTER_ID_SHIFT = SEQUENCE_BITS + WORKER_ID_BITS; private static final long TIMESTAMP_LEFT_SHIFT = SEQUENCE_BITS + WORKER_ID_BITS + DATACENTER_ID_BITS; private static final long SEQUENCE_MASK = ~(-1L << SEQUENCE_BITS); private long sequence = 0L; private long lastTimestamp = -1L; /** * 构造函数初始化worker id 和 data center id. */ public SnowflakeIdWorker(long workerId,long datacenterId){ if(workerId > MAX_WORKER_ID || workerId < 0){ throw new IllegalArgumentException(String.format("worker Id can't be greater than %d or less than 0",MAX_WORKER_ID)); } if(datacenterId > MAX_DATACENTER_ID || datacenterId < 0){ throw new IllegalArgumentException(String.format("datacenter Id can't be greater than %d or less than 0",MAX_DATACENTER_ID)); } this.workerId = workerId; this.datacenterId = datacenterId; } /** * 获取下一个ID */ synchronized public long nextId() { long timestamp = timeGen(); if(timestamp < lastTimestamp){ try{ throw new Exception("Clock moved backwards.Refusing to generate id for "+ (lastTimestamp-timestamp)+" milliseconds"); }catch(Exception e){ System.err.println(e.getMessage()); } } if(lastTimestamp == timestamp){ sequence = (sequence + 1) & SEQUENCE_MASK; if(sequence == 0){ timestamp = tilNextMillis(lastTimestamp); } }else{ sequence = 0L; } lastTimestamp = timestamp; return ((timestamp - twepoch) << TIMESTAMP_LEFT_SHIFT)| (datacenterId << DATACENTER_ID_SHIFT) | (workerId << WORKER_ID_SHIFT) | sequence; } protected long tilNextMillis(final long lastTimestamp) throws InterruptedException { long timestamp = timeGen(); while (timestamp <= lastTimestamp) { Thread.sleep(1); timestamp = timeGen(); } return timestamp; } protected long timeGen(){ return System.currentTimeMillis(); } } ``` 此段程序展示了如何创建`SnowflakeIdWorker`对象并调用其`nextId()`方法来获取新的唯一ID
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