目錄
snowflake算法源碼實現 - Scala版本 (Twitter官方原版)
snowflake算法原理
snowflake算法所生成的ID結構:
1位
,不用- 二進制中最高位爲1的都是負數,但是我們生成的id一般都使用整數,所以這個最高位固定是0
-
41位
,用來記錄時間戳(毫秒)- 41位可以表示 2^41 - 1 個數字,轉化成單位年則是 69 年
-
10位
,用來記錄工作機器id- 可以部署在 2^10 = 1024 個節點。高位5bit是數據中心ID(datacenterId),低位5bit是工作節點ID(workerId)
-
12位
,序列號,用來記錄同毫秒內產生的不同id。12位(bit)
可以表示的最大正整數是 2^12 - 1 = 4095,即一個節點在一毫秒內可以累加產生4095個ID序號
所以,SnowFlake算法在同一毫秒內可以生成全局唯一ID的數量是 1024 X 4096 = 4194304
這個數字在絕大多數併發場景下都是夠用的。
snowflake算法相比UUID的優勢
無序的UUID會導致入庫性能變差
爲什麼呢?
這就涉及到 B+樹索引的分裂:
衆所周知,關係型數據庫的索引大都是B+樹的結構,拿ID字段來舉例,索引樹的每一個節點都存儲着若干個ID。
如果我們的ID按遞增的順序來插入,比如陸續插入8,9,10,新的ID都只會插入到最後一個節點當中。當最後一個節點滿了,會裂變出新的節點。這樣的插入是性能比較高的插入,因爲這樣節點的分裂次數最少,而且充分利用了每一個節點的空間。
但是,如果我們的插入完全無序,不但會導致一些中間節點產生分裂,也會白白創造出很多不飽和的節點,這樣大大降低了數據庫插入的性能。
snowflake算法源碼實現 - Java版本
/**
* Twitter_Snowflake<br>
* SnowFlake的結構如下(每部分用-分開):<br>
* 0 - 0000000000 0000000000 0000000000 0000000000 0 - 00000 - 00000 - 000000000000 <br>
* 1位標識,由於long基本類型在Java中是帶符號的,最高位是符號位,正數是0,負數是1,所以id一般是正數,最高位是0<br>
* 41位時間截(毫秒級),注意,41位時間截不是存儲當前時間的時間截,而是存儲時間截的差值(當前時間截 - 開始時間截)
* 得到的值),這裏的的開始時間截,一般是我們的id生成器開始使用的時間,由我們程序來指定的(如下下面程序IdWorker類的startTime屬性)。41位的時間截,可以使用69年,年T = (1L << 41) / (1000L * 60 * 60 * 24 * 365) = 69<br>
* 10位的數據機器位,可以部署在1024個節點,包括5位datacenterId和5位workerId<br>
* 12位序列,毫秒內的計數,12位的計數順序號支持每個節點每毫秒(同一機器,同一時間截)產生4096個ID序號<br>
* 加起來剛好64位,爲一個Long型。<br>
* SnowFlake的優點是,整體上按照時間自增排序,並且整個分佈式系統內不會產生ID碰撞(由數據中心ID和機器ID作區分),並且效率較高,經測試,SnowFlake每秒能夠產生26萬ID左右。
*/
public class SnowflakeIdWorker {
// ==============================Fields===========================================
/** 開始時間截 (2015-01-01) */
private final long twepoch = 1420041600000L;
/** 機器id所佔的位數 */
private final long workerIdBits = 5L;
/** 數據標識id所佔的位數 */
private final long datacenterIdBits = 5L;
/** 支持的最大機器id,結果是31 (這個移位算法可以很快的計算出幾位二進制數所能表示的最大十進制數) */
private final long maxWorkerId = -1L ^ (-1L << workerIdBits);
/** 支持的最大數據標識id,結果是31 */
private final long maxDatacenterId = -1L ^ (-1L << datacenterIdBits);
/** 序列在id中佔的位數 */
private final long sequenceBits = 12L;
/** 機器ID向左移12位 */
private final long workerIdShift = sequenceBits;
/** 數據標識id向左移17位(12+5) */
private final long datacenterIdShift = sequenceBits + workerIdBits;
/** 時間截向左移22位(5+5+12) */
private final long timestampLeftShift = sequenceBits + workerIdBits + datacenterIdBits;
/** 生成序列的掩碼,這裏爲4095 (0b111111111111=0xfff=4095) */
private final long sequenceMask = -1L ^ (-1L << sequenceBits);
/** 工作機器ID(0~31) */
private long workerId;
/** 數據中心ID(0~31) */
private long datacenterId;
/** 毫秒內序列(0~4095) */
private long sequence = 0L;
/** 上次生成ID的時間截 */
private long lastTimestamp = -1L;
//==============================Constructors=====================================
/**
* 構造函數
* @param workerId 工作ID (0~31)
* @param datacenterId 數據中心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==========================================
/**
* 獲得下一個ID (該方法是線程安全的)
* @return SnowflakeId
*/
public synchronized long nextId() {
long timestamp = timeGen();
//如果當前時間小於上一次ID生成的時間戳,說明系統時鐘回退過這個時候應當拋出異常
if (timestamp < lastTimestamp) {
throw new RuntimeException(
String.format("Clock moved backwards. Refusing to generate id for %d milliseconds", lastTimestamp - timestamp));
}
//如果是同一時間生成的,則進行毫秒內序列
if (lastTimestamp == timestamp) {
sequence = (sequence + 1) & sequenceMask;
//毫秒內序列溢出
if (sequence == 0) {
//阻塞到下一個毫秒,獲得新的時間戳
timestamp = tilNextMillis(lastTimestamp);
}
}
//時間戳改變,毫秒內序列重置
else {
sequence = 0L;
}
//上次生成ID的時間截
lastTimestamp = timestamp;
//移位並通過或運算拼到一起組成64位的ID
return ((timestamp - twepoch) << timestampLeftShift) //
| (datacenterId << datacenterIdShift) //
| (workerId << workerIdShift) //
| sequence;
}
/**
* 阻塞到下一個毫秒,直到獲得新的時間戳
* @param lastTimestamp 上次生成ID的時間截
* @return 當前時間戳
*/
protected long tilNextMillis(long lastTimestamp) {
long timestamp = timeGen();
while (timestamp <= lastTimestamp) {
timestamp = timeGen();
}
return timestamp;
}
/**
* 返回以毫秒爲單位的當前時間
* @return 當前時間(毫秒)
*/
protected long timeGen() {
return System.currentTimeMillis();
}
//==============================Test=============================================
/** 測試 */
public static void main(String[] args) {
SnowflakeIdWorker idWorker = new SnowflakeIdWorker(0, 0);
for (int i = 0; i < 1000; i++) {
long id = idWorker.nextId();
System.out.println(Long.toBinaryString(id));
System.out.println(id);
}
}
}
snowflake算法源碼實現 - Scala版本 (Twitter官方原版)
/** Copyright 2010-2012 Twitter, Inc.*/
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
}
}