一、负载均衡策略
负载均衡策略在分布式系统中至关重要,通过将流量分配到多个服务器上,确保服务的高可用性和稳定性,常见的负载均衡策略包括简单随机、加权随机、轮询、加权轮询、平滑加权轮询、一致性哈希和最少活跃数。
二、负载均衡策略代码实现

1. 服务器类定义
public class MyServer {
private String ip;
private int weight; // 用于加权策略
public MyServer(String ip, int weight) {
this.ip = ip;
this.weight = weight;
}
public String getIp() {
return ip;
}
public void setIp(String ip) {
this.ip = ip;
}
public int getWeight() {
return weight;
}
public void setWeight(int weight) {
this.weight = weight;
}
}
2. 抽象负载均衡策略类
public abstract class AbstractLoadBalance {
public MyServer select(List<MyServer> serverList) {
return doSelect(serverList);
}
protected abstract MyServer doSelect(List<MyServer> serverList);
}
3. 简单随机策略
import java.util.concurrent.ThreadLocalRandom;
public class RandomBalance extends AbstractLoadBalance {
@Override
protected MyServer doSelect(List<MyServer> serverList) {
int index = ThreadLocalRandom.current().nextInt(serverList.size());
return serverList.get(index);
}
}
4. 加权随机策略
import java.util.concurrent.ThreadLocalRandom;
import java.util.List;
import java.util.ArrayList;
import java.util.Collections;
public class WeightedRandomBalance extends AbstractLoadBalance {
@Override
protected MyServer doSelect(List<MyServer> serverList) {
int totalWeight = serverList.stream().mapToInt(MyServer::getWeight).sum();
int randomWeight = ThreadLocalRandom.current().nextInt(totalWeight);
int sum = 0;
for (MyServer server : serverList) {
sum += server.getWeight();
if (randomWeight < sum) {
return server;
}
}
return null; // 理论上不会到达这里
}
}
5. 简单轮询策略
import java.util.List;
import java.util.concurrent.atomic.AtomicInteger;
public class RoundRobinBalance extends AbstractLoadBalance {
private AtomicInteger currentIndex = new AtomicInteger(0);
@Override
protected MyServer doSelect(List<MyServer> serverList) {
int index = currentIndex.getAndIncrement() % serverList.size();
return serverList.get(index);
}
}
6. 简单加权轮询策略
import java.util.List;
import java.util.concurrent.atomic.AtomicInteger;
public class WeightedRoundRobinBalance extends AbstractLoadBalance {
private AtomicInteger currentIndex = new AtomicInteger(0);
private List<Integer> cumulativeWeights;
private int maxWeight;
private int gcdWeight;
public WeightedRoundRobinBalance(List<MyServer> servers) {
this.maxWeight = servers.stream().mapToInt(MyServer::getWeight).max().orElse(1);
this.gcdWeight = calculateGCD(servers);
this.cumulativeWeights = new ArrayList<>();
int sum = 0;
for (MyServer server : servers) {
sum += gcdWeight * server.getWeight();
cumulativeWeights.add(sum);
}
}
private int calculateGCD(List<MyServer> servers) {
int gcd = servers.get(0).getWeight();
for (int i = 1; i < servers.size(); i++) {
gcd = gcd(gcd, servers.get(i).getWeight());
}
return gcd;
}
private int gcd(int a, int b) {
while (b != 0) {
int t = b;
b = a % b;
a = t;
}
return a;
}
@Override
protected MyServer doSelect(List<MyServer> serverList) {
int index = (currentIndex.getAndAdd(gcdWeight) 1) / gcdWeight;
int sum = 0;
for (int i = 0; i <= index; i++) {
sum += gcdWeight * serverList.get(i).getWeight();
}
return serverList.get(index);
}
}
7. 平滑加权轮询策略(略)

平滑加权轮询策略的实现较为复杂,通常需要维护一个权重队列,根据权重动态调整队列中的元素顺序,具体实现可以参考相关算法书籍或开源项目。
8. 一致性哈希策略(略)
一致性哈希策略需要构建一个哈希环,并根据请求的哈希值找到最近的节点,具体实现也较为复杂,建议参考专业资料。
9. 最少活跃数策略(略)
最少活跃数策略需要实时监控每个服务器的连接数,并选择连接数最少的服务器,这通常需要额外的监控组件来收集服务器状态信息。
三、相关问题与解答栏目
问题1:什么是负载均衡?
答:负载均衡是一种计算机网络技术,通过将流量分配到多个服务器上,以确保服务的高可用性和稳定性,它解决了单个服务器可能过载的问题,提高了系统的整体性能和可靠性。

问题2:如何选择适合的负载均衡策略?
答:选择适合的负载均衡策略取决于具体的业务场景和需求,如果服务器处理能力差异较大,可以选择加权随机或加权轮询策略;如果请求具有地域性特征,可以考虑一致性哈希策略;对于长连接请求较多的场景,最少活跃数策略可能更合适,在选择负载均衡策略时,需要综合考虑多种因素,并进行实际测试和评估。
各位小伙伴们,我刚刚为大家分享了有关“负载均衡策略代码”的知识,希望对你们有所帮助。如果您还有其他相关问题需要解决,欢迎随时提出哦!














