分库分表场景下如何选择主键
数据库本身有自己的自增id,但在分库分表场景下,则无法保证主键的唯一,这时就需要可以替代的东西;
常见的分布式id生成方案有:UUID、Redis的incr命令、Zookeeper的顺序节点、雪花算法;
实现原理
SnowFlake算法,是Twitter开源的分布式id生成算法。其核心思想:使用一个64bit的long型的数字作为全局唯一id。
实现
import java.lang.management.ManagementFactory;
import java.lang.management.RuntimeMXBean;
import java.net.NetworkInterface;
import java.net.SocketException;
import java.util.Enumeration;
/**
* 雪花算法
*/
public class SnowFlake {
//初始时间值
private final static long twepoch = 12888349746579L;
// 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;
// 毫秒内自增位数
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;
//sequence掩码,确保sequnce不会超出上限
private final static long sequenceMask = -1L ^ (-1L << sequenceBits);
//上次时间戳
private static long lastTimestamp = -1L;
//序列
private long sequence = 0L;
//服务器ID
private long workerId = 1L;
private static long workerMask = -1L ^ (-1L << workerIdBits);
//进程编码
private long processId = 1L;
private static long processMask = -1L ^ (-1L << datacenterIdBits);
private static SnowFlake snowFlake = null;
static{
snowFlake = new SnowFlake();
}
public static long nextId(){
return snowFlake.getNextId();
}
private SnowFlake() {
//获取机器编码
this.workerId=this.getMachineNum();
//获取进程编码
RuntimeMXBean runtimeMXBean = ManagementFactory.getRuntimeMXBean();
this.processId=Long.valueOf(runtimeMXBean.getName().split("@")[0]).longValue();
//避免编码超出最大值
this.workerId=workerId & workerMask;
this.processId=processId & processMask;
}
public long getNextId() {
//获取时间戳
long timestamp = timeGen();
//如果时间戳小于上次时间戳则报错
if (timestamp < lastTimestamp) {
try {
throw new Exception("Clock moved backwards. Refusing to generate id for " + (lastTimestamp - timestamp) + " milliseconds");
} catch (Exception e) {
e.printStackTrace();
}
}
//如果时间戳与上次时间戳相同
if (lastTimestamp == timestamp) {
// 当前毫秒内,则+1,与sequenceMask确保sequence不会超出上限
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 = 0;
}
lastTimestamp = timestamp;
// ID偏移组合生成最终的ID,并返回ID
long nextId = ((timestamp - twepoch) << timestampLeftShift) | (processId << datacenterIdShift) | (workerId << workerIdShift) | sequence;
return nextId;
}
/**
* 再次获取时间戳直到获取的时间戳与现有的不同
* @param lastTimestamp
* @return 下一个时间戳
*/
private long tilNextMillis(final long lastTimestamp) {
long timestamp = this.timeGen();
while (timestamp <= lastTimestamp) {
timestamp = this.timeGen();
}
return timestamp;
}
private long timeGen() {
return System.currentTimeMillis();
}
/**
* 获取机器编码
* @return
*/
private long getMachineNum(){
long machinePiece;
StringBuilder sb = new StringBuilder();
Enumeration<NetworkInterface> e = null;
try {
e = NetworkInterface.getNetworkInterfaces();
} catch (SocketException e1) {
e1.printStackTrace();
}
while (e.hasMoreElements()) {
NetworkInterface ni = e.nextElement();
sb.append(ni.toString());
}
machinePiece = sb.toString().hashCode();
return machinePiece;
}
}
缺点
依赖与系统时间的一致性,如果系统时间被回调,可能会造成冲突。
其它的分布式id生成方式
1、Leaf美团点评分布式ID生成系统
https://tech.meituan.com/2017/04/21/mt-
https://github.com/Meituan-Dianping/Leaf/blob/master/README_CN.md
2、Tinyid滴滴分布式ID生成算法
https://github.com/didi/tinyid
3、UidGenerator百度分布式ID生成算法
https://github.com/baidu/uid-generator
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