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  • Ribbonn负载均衡

    1.Ribbon简介

      Ribbon是Netflix Ribbon实现的一套客户端负载均衡的工具。主要提供客户端的软件负载均衡和服务调用。

      Ribbon客户端提供一系列完善的配置项如连接超时,重试等。简单的说,就是在配置文件中列出LoadBalancer(简称LB)后面所有的机器,Ribbon会基于某种规则(轮询、随机连接)等去连接这些机器。也可以实现自定义的负载均衡算法。

      Ribbon属于进程内的LB,集成于消费方进程,消费方通过它来获取到服务提供方的地址。在Java中对应的就是负载均衡+RestTemplate调用。

      git地址:https://github.com/Netflix/ribbon

    2.Ribbon负载均衡和RestTemplate调用

    Ribbon的LB的IRule核心类如下:

     主要实现有:

    RandomRule:随机

    RoundRobinRule:轮询

    RetryRule:先按照轮询策略获取,如果获取失败会在指定时间内进行重试

    WeightedResponseTimeRule:对RoundRobinRule轮询的扩展,响应速度越快的权重越大,越容易被选中

    BestAvailableRule:会过滤掉多次访问故障而处于断路器跳闸状态的服务,然后选择一个并发量最小的服务

    AvailabilityFilteringRule:过滤掉故障实例然后选择并发较小的实例

    ZoneAvoidanceRule:默认规则,复合判断server所在区域的性能和server的可用性选择服务器

    1.默认的负载均衡:

    package cn.qz.cloud.config;
    
    import org.springframework.cloud.client.loadbalancer.LoadBalanced;
    import org.springframework.context.annotation.Bean;
    import org.springframework.context.annotation.Configuration;
    import org.springframework.web.client.RestTemplate;
    
    /**
     * 注入一个bean
     */
    @Configuration
    public class ApplicationContextConfig {
        @Bean
        @LoadBalanced
        public RestTemplate getRestTemplate() {
            return new RestTemplate();
        }
    }

      在getRestTemplate增加@LoadBalanced注解即可实现负载均衡。默认的是轮询算法。验证的话可以通过订单(消费者模块)调用支付模块(服务提供者)根据服务的端口等信息来测试。

    2.负载规则替换

     1. 修改全局默认的负载均衡算法

    package cn.qz.cloud.config;
    
    import com.netflix.loadbalancer.IRule;
    import com.netflix.loadbalancer.RandomRule;
    import org.springframework.cloud.client.loadbalancer.LoadBalanced;
    import org.springframework.context.annotation.Bean;
    import org.springframework.context.annotation.Configuration;
    import org.springframework.web.client.RestTemplate;
    
    /**
     * 注入一个bean
     */
    @Configuration
    public class ApplicationContextConfig {
        @Bean
        @LoadBalanced
        public RestTemplate getRestTemplate() {
            return new RestTemplate();
        }
    
        @Bean
        public IRule myRule() {
            // 修改全局默认的负载均衡算法(轮询)义为随机
            return new RandomRule();
        }
    
    }

       注入一个新的IRule对象即可修改全局的负载均衡策略。

    2.针对单个服务修改负载均衡策略

    这里需要注意:配置类所在的包不能在SpringBoot主启动类所在的包以及子包。SpringBoot启动的时候默认的时候扫描的是启动类所在的包以及其子包,所以如果放在当前包或者子包会替换全局的负载均衡策略。

      对单个服务设置的负载均衡策略>全局的负载均衡策略

    package cn.ribbon.rules;
    
    import com.netflix.loadbalancer.IRule;
    import com.netflix.loadbalancer.RoundRobinRule;
    import org.springframework.context.annotation.Bean;
    import org.springframework.context.annotation.Configuration;
    
    @Configuration
    public class MyLoadBalanceRule {
    
        @Bean
        public IRule myRule() {
            // 定义为轮询
            return new RoundRobinRule();
        }
    
    }

    SpringBoot主启动类增加注解:(可以用单个注解,也可以用多个注解声明多个服务采用不同的负载规则)

    package cn.qz.cloud;
    
    import cn.ribbon.rules.MyLoadBalanceRule;
    import org.springframework.boot.SpringApplication;
    import org.springframework.boot.autoconfigure.SpringBootApplication;
    import org.springframework.cloud.netflix.eureka.EnableEurekaClient;
    import org.springframework.cloud.netflix.ribbon.RibbonClient;
    import org.springframework.cloud.netflix.ribbon.RibbonClients;
    
    /**
     * 启动类
     */
    @SpringBootApplication
    @EnableEurekaClient
    // 可以使用注解数组定义多个,也可以使用单个注解定义单个规则
    @RibbonClients(@RibbonClient(name = "CLOUD-PAYMENT-SERVICE", configuration = MyLoadBalanceRule.class))
    //@RibbonClient(name = "CLOUD-PAYMENT-SERVICE",configuration = MyLoadBalanceRule.class)
    public class OrderConsumerMain80 {
        public static void main(String[] args) {
            SpringApplication.run(OrderConsumerMain80.class, args);
        }
    }

     3. 定义自己的负载均衡规则

      根据RandomRule随机负载均衡算法模仿着写一个即可。

    (1) 查看RandomRule类的源码如下:

    //
    // Source code recreated from a .class file by IntelliJ IDEA
    // (powered by Fernflower decompiler)
    //
    
    package com.netflix.loadbalancer;
    
    import com.netflix.client.config.IClientConfig;
    import edu.umd.cs.findbugs.annotations.SuppressWarnings;
    import java.util.List;
    import java.util.concurrent.ThreadLocalRandom;
    
    public class RandomRule extends AbstractLoadBalancerRule {
        public RandomRule() {
        }
    
        @SuppressWarnings({"RCN_REDUNDANT_NULLCHECK_OF_NULL_VALUE"})
        public Server choose(ILoadBalancer lb, Object key) {
            if (lb == null) {
                return null;
            } else {
                Server server = null;
    
                while(server == null) {
                    if (Thread.interrupted()) {
                        return null;
                    }
    
                    List<Server> upList = lb.getReachableServers();
                    List<Server> allList = lb.getAllServers();
                    int serverCount = allList.size();
                    if (serverCount == 0) {
                        return null;
                    }
    
                    int index = this.chooseRandomInt(serverCount);
                    server = (Server)upList.get(index);
                    if (server == null) {
                        Thread.yield();
                    } else {
                        if (server.isAlive()) {
                            return server;
                        }
    
                        server = null;
                        Thread.yield();
                    }
                }
    
                return server;
            }
        }
    
        protected int chooseRandomInt(int serverCount) {
            return ThreadLocalRandom.current().nextInt(serverCount);
        }
    
        public Server choose(Object key) {
            return this.choose(this.getLoadBalancer(), key);
        }
    
        public void initWithNiwsConfig(IClientConfig clientConfig) {
        }
    }

    (2) 编写自己的规则:实现每个服务调用3次的轮询算法

    轮询规则:

    package cn.ribbon.rules;
    
    import com.netflix.client.config.IClientConfig;
    import com.netflix.loadbalancer.AbstractLoadBalancerRule;
    import com.netflix.loadbalancer.ILoadBalancer;
    import com.netflix.loadbalancer.Server;
    
    import java.util.List;
    import java.util.concurrent.atomic.AtomicInteger;
    
    public class CustomRandomRule extends AbstractLoadBalancerRule {
    
    
        /**
         * 每个服务调用的次数
         */
        private int serverCallTimes = 3;
    
        /**
         * 总共调用的次数
         */
        private AtomicInteger total = new AtomicInteger(-1);
    
        /**
         * 当前的下标
         */
        private AtomicInteger currentIndex = new AtomicInteger(0);
    
        public Server choose(ILoadBalancer lb, Object key) {
            if (lb == null) {
                return null;
            }
            Server server = null;
            while (server == null) {
                if (Thread.interrupted()) {
                    return null;
                }
    
                // 可用列表
                List<Server> upList = lb.getReachableServers();
                // 所有服务列表
                List<Server> allList = lb.getAllServers();
                int serverCount = allList.size();
                if (serverCount == 0) {
                    return null;
                }
    
                // 修改总次数以及下次需要取的下标:total++;根据 total % serverCallTimes == 0 ,下标移动
                int totalNum = total.intValue();
                if (totalNum == Integer.MAX_VALUE) {
                    total.set(-1);
                    totalNum = 0;
                }
                total.addAndGet(1);
                if (totalNum % serverCallTimes == 0) {
                    // 判断当前的下标
                    if (currentIndex.intValue() == allList.size() - 1) {
                        currentIndex.set(0);
                    } else {
                        currentIndex.addAndGet(1);
                    }
                }
                server = upList.get(currentIndex.intValue());
                System.out.println("key: " + key + "	currentIndex: " + currentIndex.intValue() + "	total" + total.intValue()) ;
    
                if (server == null) {
                    Thread.yield();
                    continue;
                }
                if (server.isAlive()) {
                    return (server);
                }
                server = null;
                Thread.yield();
            }
            return server;
        }
    
        @Override
        public Server choose(Object key) {
            return choose(getLoadBalancer(), key);
        }
    
        @Override
        public void initWithNiwsConfig(IClientConfig clientConfig) {
        }
    }

    使用自己定义的规则:

    package cn.ribbon.rules;
    
    import com.netflix.loadbalancer.IRule;
    import org.springframework.context.annotation.Bean;
    import org.springframework.context.annotation.Configuration;
    
    @Configuration
    public class MyLoadBalanceRule {
    
        @Bean
        public IRule myRule() {//         定义为自定义的负载均衡算法
            return new CustomRandomRule();
        }
    
    }

     主启动类设置:

    package cn.qz.cloud;
    
    import cn.ribbon.rules.MyLoadBalanceRule;
    import org.springframework.boot.SpringApplication;
    import org.springframework.boot.autoconfigure.SpringBootApplication;
    import org.springframework.cloud.netflix.eureka.EnableEurekaClient;
    import org.springframework.cloud.netflix.ribbon.RibbonClient;
    import org.springframework.cloud.netflix.ribbon.RibbonClients;
    
    /**
     * 启动类
     */
    @SpringBootApplication
    @EnableEurekaClient
    // 可以使用注解数组定义多个,也可以使用单个注解定义单个规则
    @RibbonClients(@RibbonClient(name = "CLOUD-PAYMENT-SERVICE", configuration = MyLoadBalanceRule.class))
    //@RibbonClient(name = "CLOUD-PAYMENT-SERVICE",configuration = MyLoadBalanceRule.class)
    public class OrderConsumerMain80 {
        public static void main(String[] args) {
            SpringApplication.run(OrderConsumerMain80.class, args);
        }
    } 

    3.Ribbon负载均衡算法

     1.分析RoundRobinRule源码

    源码如下:

    //
    // Source code recreated from a .class file by IntelliJ IDEA
    // (powered by Fernflower decompiler)
    //
    
    package com.netflix.loadbalancer;
    
    import com.netflix.client.config.IClientConfig;
    import java.util.List;
    import java.util.concurrent.atomic.AtomicInteger;
    import org.slf4j.Logger;
    import org.slf4j.LoggerFactory;
    
    public class RoundRobinRule extends AbstractLoadBalancerRule {
        private AtomicInteger nextServerCyclicCounter;
        private static final boolean AVAILABLE_ONLY_SERVERS = true;
        private static final boolean ALL_SERVERS = false;
        private static Logger log = LoggerFactory.getLogger(RoundRobinRule.class);
    
        public RoundRobinRule() {
            this.nextServerCyclicCounter = new AtomicInteger(0);
        }
    
        public RoundRobinRule(ILoadBalancer lb) {
            this();
            this.setLoadBalancer(lb);
        }
    
        public Server choose(ILoadBalancer lb, Object key) {
            if (lb == null) {
                log.warn("no load balancer");
                return null;
            } else {
                Server server = null;
                int count = 0;
    
                while(true) {
                    if (server == null && count++ < 10) {
                        List<Server> reachableServers = lb.getReachableServers();
                        List<Server> allServers = lb.getAllServers();
                        int upCount = reachableServers.size();
                        int serverCount = allServers.size();
                        if (upCount != 0 && serverCount != 0) {
                            int nextServerIndex = this.incrementAndGetModulo(serverCount);
                            server = (Server)allServers.get(nextServerIndex);
                            if (server == null) {
                                Thread.yield();
                            } else {
                                if (server.isAlive() && server.isReadyToServe()) {
                                    return server;
                                }
    
                                server = null;
                            }
                            continue;
                        }
    
                        log.warn("No up servers available from load balancer: " + lb);
                        return null;
                    }
    
                    if (count >= 10) {
                        log.warn("No available alive servers after 10 tries from load balancer: " + lb);
                    }
    
                    return server;
                }
            }
        }
    
        private int incrementAndGetModulo(int modulo) {
            int current;
            int next;
            do {
                current = this.nextServerCyclicCounter.get();
                next = (current + 1) % modulo;
            } while(!this.nextServerCyclicCounter.compareAndSet(current, next));
    
            return next;
        }
    
        public Server choose(Object key) {
            return this.choose(this.getLoadBalancer(), key);
        }
    
        public void initWithNiwsConfig(IClientConfig clientConfig) {
        }
    }

       核心的是choose方法。方法里面进行一堆验证之后调用incrementAndGetModulo方法获得了本次提供服务的server的索引。

      incrementAndGetModulo放啊里面是使用类似于自旋锁的概念。用 (当前调用次数+1)%server数量 得到下标。

    2.重写轮询算法结合discoveryClient实现负载均衡

     定义一个接口:

    package cn.qz.cloud.loadbalance;
    
    import org.springframework.cloud.client.ServiceInstance;
    
    import java.util.List;
    
    public interface LoadBalancer {
    
        ServiceInstance instances(List<ServiceInstance> serviceInstances);
    }

    实现类如下:

    package cn.qz.cloud.loadbalance;
    
    import org.springframework.cloud.client.ServiceInstance;
    import org.springframework.stereotype.Component;
    
    import java.util.List;
    import java.util.concurrent.atomic.AtomicInteger;
    
    @Component
    public class MyLoadBalancerImpl implements LoadBalancer {
    
        private AtomicInteger atomicInteger = new AtomicInteger(0);
    
        public final int getAndIncrement() {
            int current;
            int next;
            do {
                current = this.atomicInteger.get();
                next = current >= 2147483647 ? 0 : current + 1;
            } while (!this.atomicInteger.compareAndSet(current, next));
            System.out.println("****第几次访问,次数next: " + next);
            return next;
        }
    
        // 负载均衡轮询算法,rest接口第几次请求数 % 服务器集群总数 = 实际调用服务器位置下标
        @Override
        public ServiceInstance instances(List<ServiceInstance> serviceInstances) {
            int index = getAndIncrement() % serviceInstances.size();
            return serviceInstances.get(index);
        }
    }

     修改restTemplate取消负载均衡:

    package cn.qz.cloud.config;
    
    import com.netflix.loadbalancer.IRule;
    import com.netflix.loadbalancer.RandomRule;
    import org.springframework.cloud.client.loadbalancer.LoadBalanced;
    import org.springframework.context.annotation.Bean;
    import org.springframework.context.annotation.Configuration;
    import org.springframework.web.client.RestTemplate;
    
    /**
     * 注入一个bean
     */
    @Configuration
    public class ApplicationContextConfig {
        @Bean
        public RestTemplate getRestTemplate() {
            return new RestTemplate();
        }
    }

    修改Controller增加lb测试接口:

    package cn.qz.cloud.controller;
    
    import cn.qz.cloud.bean.Payment;
    import cn.qz.cloud.loadbalance.LoadBalancer;
    import cn.qz.cloud.utils.JSONResultUtil;
    import org.springframework.cloud.client.ServiceInstance;
    import org.springframework.cloud.client.discovery.DiscoveryClient;
    import org.springframework.web.bind.annotation.*;
    import org.springframework.web.client.RestTemplate;
    
    import javax.annotation.Resource;
    import java.net.URI;
    import java.util.List;
    import java.util.Map;
    
    /**
     * @Author: qlq
     * @Description
     * @Date: 22:09 2020/9/25
     */
    @RestController
    @RequestMapping("/consumer")
    public class OrderController {
    
        private static final String PAYMENT_URL = "http://CLOUD-PAYMENT-SERVICE";
    
        @Resource
        private RestTemplate restTemplate;
    
        @Resource
        private LoadBalancer loadBalancer;
    
        @Resource
        private DiscoveryClient discoveryClient;
    
        @GetMapping("/pay/lb")
        public JSONResultUtil<String> lb() {
            // 通过容器中的 discoveryClient和服务名来获取服务集群
            List<ServiceInstance> instances = discoveryClient.getInstances("CLOUD-PAYMENT-SERVICE");
            if (instances == null || instances.size() <= 0) {
                return null;
            }
    
            // 传入服务集群来计算出获取具体的服务实例
            ServiceInstance serviceInstance = loadBalancer.instances(instances);
            URI uri = serviceInstance.getUri();
            return restTemplate.getForObject(uri + "/pay/getServerPort", JSONResultUtil.class);
        }
    }

    主启动类取消负载均衡设置:

    package cn.qz.cloud;
    
    import org.springframework.boot.SpringApplication;
    import org.springframework.boot.autoconfigure.SpringBootApplication;
    import org.springframework.cloud.netflix.eureka.EnableEurekaClient;
    
    /**
     * 启动类
     */
    @SpringBootApplication
    @EnableEurekaClient
    // 可以使用注解数组定义多个,也可以使用单个注解定义单个规则
    //@RibbonClients(@RibbonClient(name = "CLOUD-PAYMENT-SERVICE", configuration = MyLoadBalanceRule.class))
    //@RibbonClient(name = "CLOUD-PAYMENT-SERVICE",configuration = MyLoadBalanceRule.class)
    public class OrderConsumerMain80 {
        public static void main(String[] args) {
            SpringApplication.run(OrderConsumerMain80.class, args);
        }
    }

      启动测试即可。注意需要注释掉restTemplate的loadBalance,而且不能和原来的接口一起使用,因为原来的接口基于loadBalance的负载均衡来替换URL中的服务名称。

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  • 原文地址:https://www.cnblogs.com/qlqwjy/p/13823705.html
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