手写分布式负载均衡算法

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负载均衡在实际工作项目中是很普遍的,主要分为硬件负载均衡和软件负载均衡。硬件负载均衡主要有F5、Array等。都是一些商用的负载均衡器。软件负载均衡主要包括耳熟能详的nginx、LVS、Tengine等,使用起来成本比较低,但是也要去维护。

今天讨论的是常用的负载均衡算法。

随机算法:顾名思义 根据服务器列表大小值随机选取一台服务器访问。

带权重的随机算法实现:

通过生成的随机数,计算这个随机数所落入的区间,即可知道选中哪台服务器,比如如果随机数3,则在区间[0,5)选中服务器A,随机数为7则选中B服务器。

  

import java.util.HashMap;import java.util.Map;
public class IpMap { static Map<String,Integer> ipAddrs = new HashMap(); static { ipAddrs.put("A",5); ipAddrs.put("B",3); ipAddrs.put("C",2); }
}
import java.util.*;
public class Random01 { //不考虑权重 public static String getIpNoWeight(){ Set ipSet = new HashSet(); for(String ip:IpMap.ipAddrs.keySet()){ ipSet.add(ip); } List<String> ipList = new ArrayList<>(); ipList.addAll(ipSet); Integer random = new Random().nextInt(ipList.size()); return ipList.get(random); } //考虑权重 public static String getIpWithWeight01(){ List<String> ipList = new ArrayList<>(); for(String ip:IpMap.ipAddrs.keySet()){ Integer weight = IpMap.ipAddrs.get(ip); for(int i=0;i<weight;i++){ ipList.add(ip); } } Integer random = new Random().nextInt(ipList.size()); return ipList.get(random); }
public static String getIpWithWeight02(){
int totalweight = 0; boolean sameweight = true; Object[] weights = IpMap.ipAddrs.values().toArray(); for(int i=0;i<weights.length;i++){ totalweight +=(int) weights[i]; if(sameweight && i>0 && !weights[i].equals(weights[i-1])){ sameweight = false; } } Integer random = new Random().nextInt(totalweight); if(!sameweight){ for(String ip:IpMap.ipAddrs.keySet()){ Integer value = IpMap.ipAddrs.get(ip); if(random<value){ return ip; } random = random - value; } } //权重相同,相当于不考虑权重完全随机 return getIpNoWeight(); }
public static void main(String[] args) { for(int i=0;i<10;i++){ //System.out.println(getIpNoWeight()); System.out.println(getIpWithWeight02()); } }}

轮询算法:

有一种方法,调用编号,比如第1次调用为1,第2次调用为2,第100次调用为100,调用的编号是递增的,所以可以根据调用的编号推算出服务器。

Server=[]A,B,C]对应权重weights=[2,3,5]权重和为10;

如果调用10次,调用顺序为AABBBCCCCC

可以对权重和取余。

1号调用,1%10=1;2号调用,2%10=2......100号调用,100%10=0。可以发现编号在0-9之间。可以根据这10个数字找到对应的服务器。方法与上面类似,可以把权重想象为坐标轴“0-2-5-10”。


上面的方法,其实有一个弊端,如果一台服务器的权重特别大,他就会连续处理请求,此时可以使用平滑加权轮询。

每个服务器对应两个权重,分别为weight和currentWeight。weight固定,currentWeight动态变化,初始值为0。有新的请求进来时,遍历服务器列表,让它的currentWeight加上自身权重,遍历完后,找到最大的currentWeight,将其减去权重,然后返回对应服务器。

请求编号1中,初始值为[5, 1, 1],数组中最大的值5,那么选择结果为A,选择后最大的值5减去权重和7,变成了[-2, 1, 1];


请求编号2来的时候,[-2, 1, 1]加上[5, 1, 1],那么就变成编号2中的初始值为[3, 2, 2],数组中最大的值3,那么选择结果为A,最大的值3减去权重和7,变成了[-4, 2, 2];


请求编号3来的时候,[-4, 2, 2]加上[5, 1, 1],那么就变成编号2中的初始值为[1, 3, 3],数组中最大的值3,那么选择结果为B,最大的值3减去权重和7,变成了[1, -4, 3];

以此类推。。。。。。。。


package fuzaijunheng;
import java.util.*;
public class Round02 { private static Integer pos =0; //不考虑权重 public static String getIpNoWeight(){ String serverIp = null; synchronized (pos){ if(pos>=IpMap.ipAddrs.size()){ pos=0; } HashSet<String> ipSet = new HashSet<>(); for(String ip:IpMap.ipAddrs.keySet()){ ipSet.add(ip); } ArrayList<String> ipList = new ArrayList<>(); ipList.addAll(ipSet); serverIp = ipList.get(pos); pos++; } return serverIp; } //考虑权重(简单的就不演示了) static int num=0; public static String getIpWithWeight(){
int totalWeight=0; boolean sameWeight=true; Object[] weights = IpMap.ipAddrs.values().toArray(); for(int i=0;i<weights.length;i++){ Integer weight=(Integer)weights[i]; totalWeight +=weight; if(sameWeight&&i>0&& !weight.equals(weights[i-1])){ sameWeight=false; } }
Integer sequenceNum = ++num; Integer offset = sequenceNum % totalWeight; offset = offset==0?totalWeight: offset; if(!sameWeight){ for(String ip:IpMap.ipAddrs.keySet()){ Integer weight = IpMap.ipAddrs.get(ip); if(offset<=weight){ return ip; } offset = offset - weight; } } return null; }
//平滑加权 private static Map<String,Weight> weightMap = new HashMap<>(); public static String getIpwithCurrentWeight(){ int totalWeight = 0; for(int weigh: IpMap.ipAddrs.values()){ totalWeight+=weigh; } //初始化weightMap,初始化currentWeight复制为weight if(weightMap.isEmpty()){ IpMap.ipAddrs.forEach((key, value)->{ weightMap.put(key,new Weight(key,value,value)); }); } //找出currentWeight最大值 Weight maxCurrentWeight = null; for(Weight weight:weightMap.values()){ if(maxCurrentWeight==null || weight.getCurrentWeight()>maxCurrentWeight.getCurrentWeight()){ maxCurrentWeight = weight; } } //将maxcurrentWeight减去权重和 maxCurrentWeight.setCurrentWeight(maxCurrentWeight.getCurrentWeight() -totalWeight); //所有ip的currentWeight统一加上权重 for(Weight weight1:weightMap.values()){ weight1.setCurrentWeight(weight1.getCurrentWeight()+weight1.getWeight()); } return maxCurrentWeight.getIp(); }
public static void main(String[] args) { for(int i=0;i<10;i++){ System.out.println(getIpwithCurrentWeight()); } }}class Weight{ private String ip; private Integer weight; private Integer currentWeight;
public Weight(String ip, Integer weight, Integer currentWeight) { this.ip = ip; this.weight = weight; this.currentWeight = currentWeight; }
public String getIp() { return ip; }
public void setIp(String ip) { this.ip = ip; }
public Integer getWeight() { return weight; }
public void setWeight(Integer weight) { this.weight = weight; }
public Integer getCurrentWeight() { return currentWeight; }
public void setCurrentWeight(Integer currentWeight) { this.currentWeight = currentWeight; }}


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