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  • SnowFlake分布式ID生成及反解析

    概述

    分布式id生成算法的有很多种,Twitter的SnowFlake就是其中经典的一种,SnowFlake算法生成id的结果是一个64bit大小的整数,它的结构如下图:

    • 1位,不用。二进制中最高位为1的都是负数,但是我们生成的id一般都使用整数,所以这个最高位固定是0
    • 41位,用来记录时间戳(毫秒)。

      • 41位可以表示$2^{41}-1$个数字,
      • 如果只用来表示正整数(计算机中正数包含0),可以表示的数值范围是:0 至 $2^{41}-1$,减1是因为可表示的数值范围是从0开始算的,而不是1。
      • 也就是说41位可以表示$2^{41}-1$个毫秒的值,转化成单位年则是$(2^{41}-1) / (1000 * 60 * 60 * 24 * 365) = 69$年
    • 10位,用来记录工作机器id。

      • 可以部署在$2^{10} = 1024$个节点,包括5位datacenterId5位workerId
      • 5位(bit)可以表示的最大正整数是$2^{5}-1 = 31$,即可以用0、1、2、3、....31这32个数字,来表示不同的datecenterId或workerId
    • 12位,序列号,用来记录同毫秒内产生的不同id。

      • 12位(bit)可以表示的最大正整数是$2^{12}-1 = 4095$,即可以用0、1、2、3、....4094这4095个数字,来表示同一机器同一时间截(毫秒)内产生的4095个ID序号

    由于在Java中64bit的整数是long类型,所以在Java中SnowFlake算法生成的id就是long来存储的。

    SnowFlake可以保证:

    • 所有生成的id按时间趋势递增
    • 整个分布式系统内不会产生重复id(因为有datacenterId和workerId来做区分)

    以下是Twitter官方原版的,用Scala写的

    package com.twitter.service.snowflake
    
    import com.twitter.ostrich.stats.Stats
    import com.twitter.service.snowflake.gen._
    import java.util.Random
    import com.twitter.logging.Logger
    
    /**
     * An object that generates IDs.
     * This is broken into a separate class in case
     * we ever want to support multiple worker threads
     * per process
     */
    class IdWorker(val workerId: Long, val datacenterId: Long, private val reporter: Reporter, var sequence: Long = 0L)
    extends Snowflake.Iface {
      private[this] def genCounter(agent: String) = {
        Stats.incr("ids_generated")
        Stats.incr("ids_generated_%s".format(agent))
      }
      private[this] val exceptionCounter = Stats.getCounter("exceptions")
      private[this] val log = Logger.get
      private[this] val rand = new Random
    
      val twepoch = 1288834974657L
    
      private[this] val workerIdBits = 5L
      private[this] val datacenterIdBits = 5L
      private[this] val maxWorkerId = -1L ^ (-1L << workerIdBits)
      private[this] val maxDatacenterId = -1L ^ (-1L << datacenterIdBits)
      private[this] val sequenceBits = 12L
    
      private[this] val workerIdShift = sequenceBits
      private[this] val datacenterIdShift = sequenceBits + workerIdBits
      private[this] val timestampLeftShift = sequenceBits + workerIdBits + datacenterIdBits
      private[this] val sequenceMask = -1L ^ (-1L << sequenceBits)
    
      private[this] var lastTimestamp = -1L
    
      // sanity check for workerId
      if (workerId > maxWorkerId || workerId < 0) {
        exceptionCounter.incr(1)
        throw new IllegalArgumentException("worker Id can't be greater than %d or less than 0".format(maxWorkerId))
      }
    
      if (datacenterId > maxDatacenterId || datacenterId < 0) {
        exceptionCounter.incr(1)
        throw new IllegalArgumentException("datacenter Id can't be greater than %d or less than 0".format(maxDatacenterId))
      }
    
      log.info("worker starting. timestamp left shift %d, datacenter id bits %d, worker id bits %d, sequence bits %d, workerid %d",
        timestampLeftShift, datacenterIdBits, workerIdBits, sequenceBits, workerId)
    
      def get_id(useragent: String): Long = {
        if (!validUseragent(useragent)) {
          exceptionCounter.incr(1)
          throw new InvalidUserAgentError
        }
    
        val id = nextId()
        genCounter(useragent)
    
        reporter.report(new AuditLogEntry(id, useragent, rand.nextLong))
        id
      }
    
      def get_worker_id(): Long = workerId
      def get_datacenter_id(): Long = datacenterId
      def get_timestamp() = System.currentTimeMillis
    
      protected[snowflake] def nextId(): Long = synchronized {
        var timestamp = timeGen()
    
        if (timestamp < lastTimestamp) {
          exceptionCounter.incr(1)
          log.error("clock is moving backwards.  Rejecting requests until %d.", lastTimestamp);
          throw new InvalidSystemClock("Clock moved backwards.  Refusing to generate id for %d milliseconds".format(
            lastTimestamp - timestamp))
        }
    
        if (lastTimestamp == timestamp) {
          sequence = (sequence + 1) & sequenceMask
          if (sequence == 0) {
            timestamp = tilNextMillis(lastTimestamp)
          }
        } else {
          sequence = 0
        }
    
        lastTimestamp = timestamp
        ((timestamp - twepoch) << timestampLeftShift) |
          (datacenterId << datacenterIdShift) |
          (workerId << workerIdShift) | 
          sequence
      }
    
      protected def tilNextMillis(lastTimestamp: Long): Long = {
        var timestamp = timeGen()
        while (timestamp <= lastTimestamp) {
          timestamp = timeGen()
        }
        timestamp
      }
    
      protected def timeGen(): Long = System.currentTimeMillis()
    
      val AgentParser = """([a-zA-Z][a-zA-Z-0-9]*)""".r
    
      def validUseragent(useragent: String): Boolean = useragent match {
        case AgentParser(_) => true
        case _ => false
      }
    }

    Sharding-jdbc基于Java版的实现:

    /*
     * Copyright 1999-2015 dangdang.com.
     * <p>
     * Licensed under the Apache License, Version 2.0 (the "License");
     * you may not use this file except in compliance with the License.
     * You may obtain a copy of the License at
     *
     *      http://www.apache.org/licenses/LICENSE-2.0
     *
     * Unless required by applicable law or agreed to in writing, software
     * distributed under the License is distributed on an "AS IS" BASIS,
     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     * See the License for the specific language governing permissions and
     * limitations under the License.
     * </p>
     */
    
    package io.shardingjdbc.core.keygen;
    
    import com.google.common.base.Preconditions;
    import lombok.Setter;
    import lombok.extern.slf4j.Slf4j;
    
    import java.text.SimpleDateFormat;
    import java.util.Calendar;
    import java.util.Date;
    
    /**
     * Default distributed primary key generator.
     * 
     * <p>
     * Use snowflake algorithm. Length is 64 bit.
     * </p>
     * 
     * <pre>
     * 1bit   sign bit.
     * 41bits timestamp offset from 2016.11.01(Sharding-JDBC distributed primary key published data) to now.
     * 10bits worker process id.
     * 12bits auto increment offset in one mills
     * </pre>
     * 
     * <p>
     * Call @{@code DefaultKeyGenerator.setWorkerId} to set.
     * </p>
     * 
     * @author gaohongtao
     */
    @Slf4j
    public final class DefaultKeyGenerator implements KeyGenerator {
        
        public static final long EPOCH;
        
        private static final long SEQUENCE_BITS = 12L;
        
        private static final long WORKER_ID_BITS = 10L;
        
        private static final long SEQUENCE_MASK = (1 << SEQUENCE_BITS) - 1;
        
        private static final long WORKER_ID_LEFT_SHIFT_BITS = SEQUENCE_BITS;
        
        private static final long TIMESTAMP_LEFT_SHIFT_BITS = WORKER_ID_LEFT_SHIFT_BITS + WORKER_ID_BITS;
        
        private static final long WORKER_ID_MAX_VALUE = 1L << WORKER_ID_BITS;
        
        @Setter
        private static TimeService timeService = new TimeService();
        
        private static long workerId;
        
        static {
            Calendar calendar = Calendar.getInstance();
            calendar.set(2016, Calendar.NOVEMBER, 1);
            calendar.set(Calendar.HOUR_OF_DAY, 0);
            calendar.set(Calendar.MINUTE, 0);
            calendar.set(Calendar.SECOND, 0);
            calendar.set(Calendar.MILLISECOND, 0);
            EPOCH = calendar.getTimeInMillis();
        }
        
        private long sequence;
        
        private long lastTime;
        
        /**
         * Set work process id.
         * 
         * @param workerId work process id
         */
        public static void setWorkerId(final long workerId) {
            Preconditions.checkArgument(workerId >= 0L && workerId < WORKER_ID_MAX_VALUE);
            DefaultKeyGenerator.workerId = workerId;
        }
        
        /**
         * Generate key.
         * 
         * @return key type is @{@link Long}.
         */
        @Override
        public synchronized Number generateKey() {
            long currentMillis = timeService.getCurrentMillis();
            Preconditions.checkState(lastTime <= currentMillis, "Clock is moving backwards, last time is %d milliseconds, current time is %d milliseconds", lastTime, currentMillis);
            if (lastTime == currentMillis) {
                if (0L == (sequence = ++sequence & SEQUENCE_MASK)) {
                    currentMillis = waitUntilNextTime(currentMillis);
                }
            } else {
                sequence = 0;
            }
            lastTime = currentMillis;
            if (log.isDebugEnabled()) {
                log.debug("{}-{}-{}", new SimpleDateFormat("yyyy-MM-dd HH:mm:ss.SSS").format(new Date(lastTime)), workerId, sequence);
            }
            return ((currentMillis - EPOCH) << TIMESTAMP_LEFT_SHIFT_BITS) | (workerId << WORKER_ID_LEFT_SHIFT_BITS) | sequence;
        }
        
        private long waitUntilNextTime(final long lastTime) {
            long time = timeService.getCurrentMillis();
            while (time <= lastTime) {
                time = timeService.getCurrentMillis();
            }
            return time;
        }
    }

    写个测试,把参数都写死,并运行打印信息,方便后面来核对计算结果:

    public static void main(String[] args) {
        
        long timestamp = 1505914988849L;
        long twepoch = 1288834974657L;
        long datacenterId = 17L;
        long workerId = 25L;
        long sequence = 0L;
    
        System.out.printf("
    timestamp: %d 
    ",timestamp);
        System.out.printf("twepoch: %d 
    ",twepoch);
        System.out.printf("datacenterId: %d 
    ",datacenterId);
        System.out.printf("workerId: %d 
    ",workerId);
        System.out.printf("sequence: %d 
    ",sequence);
        System.out.println();
        System.out.printf("(timestamp - twepoch): %d 
    ",(timestamp - twepoch));
        System.out.printf("((timestamp - twepoch) << 22L): %d 
    ",((timestamp - twepoch) << 22L));
        System.out.printf("(datacenterId << 17L): %d 
    " ,(datacenterId << 17L));
        System.out.printf("(workerId << 12L): %d 
    ",(workerId << 12L));
        System.out.printf("sequence: %d 
    ",sequence);
    
        long result = ((timestamp - twepoch) << 22L) |
            (datacenterId << 17L) |
            (workerId << 12L) |
            sequence;
        System.out.println(result);
        
    }

    SnowFlake ID 反向解析

    我们将生成的ID(353337843935870976)转换为2进制:

    11011111101000001100100111100101010000001001111000000000000
    将其进行拆分
    1101111110100001110010000011011001 00000 00010001 000000000000

    然后在将各个位置的二进制编码转换为10进制就OK

    实例代码:

    import java.util.Calendar;
    import java.util.Date;
    
    import com.alibaba.fastjson.JSONObject;
    
    import io.shardingjdbc.core.keygen.DefaultKeyGenerator;
    
    public class SonwFlakeId {
    
        private static long twepoch = 1288834974657L;
    
        private long workerIdBits = 5L;
        private long datacenterIdBits = 5L;
    
        private static final long sequenceBits = 12L;
    
        private long workerIdShift = sequenceBits;
        private long dataCenterIdShift = sequenceBits + workerIdBits;
        private long timestampLeftShift = sequenceBits + workerIdBits + datacenterIdBits;
    
        static {
            Calendar calendar = Calendar.getInstance();
            calendar.set(2016, Calendar.NOVEMBER, 1);
            calendar.set(Calendar.HOUR_OF_DAY, 0);
            calendar.set(Calendar.MINUTE, 0);
            calendar.set(Calendar.SECOND, 0);
            calendar.set(Calendar.MILLISECOND, 0);
            twepoch = calendar.getTimeInMillis();
        }
        
        public JSONObject parseInfo(long id) {
            String sonwFlakeId = Long.toBinaryString(id);
            int len = sonwFlakeId.length();
            JSONObject jsonObject = new JSONObject();
            int sequenceStart = (int) (len < workerIdShift ? 0 : len - workerIdShift);
            int workerStart = (int) (len < dataCenterIdShift ? 0 : len - dataCenterIdShift);
            int timeStart = (int) (len < timestampLeftShift ? 0 : len - timestampLeftShift);
            String sequence = sonwFlakeId.substring(sequenceStart, len);
            String workerId = sequenceStart == 0 ? "0" : sonwFlakeId.substring(workerStart, sequenceStart);
            String dataCenterId = workerStart == 0 ? "0" : sonwFlakeId.substring(timeStart, workerStart);
            String time = timeStart == 0 ? "0" : sonwFlakeId.substring(0, timeStart);
            int sequenceInt = Integer.valueOf(sequence, 2);
            jsonObject.put("sequence", sequenceInt);
            int workerIdInt = Integer.valueOf(workerId, 2);
            jsonObject.put("workerId", workerIdInt);
            int dataCenterIdInt = Integer.valueOf(dataCenterId, 2);
            jsonObject.put("dataCenter", dataCenterIdInt);
            long diffTime = Long.parseLong(time, 2);
            long timeLong = diffTime + twepoch;
            Date date = fromatTime(timeLong);
            jsonObject.put("date", date);
            return jsonObject;
        }
    
        public static Date getSonwFlakeDate(long id) {
            SonwFlakeId sonwFlakeId = new SonwFlakeId();
            JSONObject jsonObject = sonwFlakeId.parseInfo(id);
            Object dateObj = jsonObject.get("date");
            return (Date) dateObj;
        }
    
        private static Date fromatTime(long date) {
            Calendar calendar = Calendar.getInstance();
            calendar.setTimeInMillis(date);
            return calendar.getTime();
        }
    
        public static void main(String[] args) {
            DefaultKeyGenerator defaultKeyGenerator = new DefaultKeyGenerator();
            long id = defaultKeyGenerator.generateKey().longValue();
            SonwFlakeId sonwFlakeId = new SonwFlakeId();
            JSONObject jsonObject = sonwFlakeId.parseInfo(id);
            System.out.println("------------------------------------------");
            System.out.println(jsonObject);
            Object dateObj = jsonObject.get("date");
            System.out.println("date:" + dateObj);
            System.out.println("------------------------------------------");
        }
    
    }

     扩展

    在理解了这个算法之后,其实还有一些扩展的事情可以做:

    1. 根据自己业务修改每个位段存储的信息。算法是通用的,可以根据自己需求适当调整每段的大小以及存储的信息。
    2. 解密id,由于id的每段都保存了特定的信息,所以拿到一个id,应该可以尝试反推出原始的每个段的信息。反推出的信息可以帮助我们分析。比如作为订单,可以知道该订单的生成日期,负责处理的数据中心等等。
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  • 原文地址:https://www.cnblogs.com/rinack/p/11127040.html
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