常用策略

1.RoundRobinRule 轮转调度策略

//该策略实现安装线性轮询的方式依次选择每个服务实例
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() {nextServerCyclicCounter = new AtomicInteger(0);}public RoundRobinRule(ILoadBalancer lb) {this();setLoadBalancer(lb);}public Server choose(ILoadBalancer lb, Object key) {if (lb == null) {log.warn("no load balancer");return null;}Server server = null;int count = 0;//最多选择十次，就会结束尝试while (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)) {log.warn("No up servers available from load balancer: " + lb);return null;}int nextServerIndex = incrementAndGetModulo(serverCount);server = allServers.get(nextServerIndex);if (server == null) {/* Transient. */Thread.yield();continue;}if (server.isAlive() && (server.isReadyToServe())) {return (server);}// Next.server = null;}if (count >= 10) {log.warn("No available alive servers after 10 tries from load balancer: "+ lb);}return server;}//通过递增实现轮询private int incrementAndGetModulo(int modulo) {for (;;) {int current = nextServerCyclicCounter.get();int next = (current + 1) % modulo;if (nextServerCyclicCounter.compareAndSet(current, next))return next;}}@Overridepublic Server choose(Object key) {return choose(getLoadBalancer(), key);}@Overridepublic void initWithNiwsConfig(IClientConfig clientConfig) {}
}

2.RetryRule重试规律策略

//具备重试机制的实例选择功能
public class RetryRule extends AbstractLoadBalancerRule {//默认使用RoundRobinRule实例IRule subRule = new RoundRobinRule();//阈值为500mslong maxRetryMillis = 500;public RetryRule() {}public RetryRule(IRule subRule) {this.subRule = (subRule != null) ? subRule : new RoundRobinRule();}public RetryRule(IRule subRule, long maxRetryMillis) {this.subRule = (subRule != null) ? subRule : new RoundRobinRule();this.maxRetryMillis = (maxRetryMillis > 0) ? maxRetryMillis : 500;}public void setRule(IRule subRule) {this.subRule = (subRule != null) ? subRule : new RoundRobinRule();}public IRule getRule() {return subRule;}public void setMaxRetryMillis(long maxRetryMillis) {if (maxRetryMillis > 0) {this.maxRetryMillis = maxRetryMillis;} else {this.maxRetryMillis = 500;}}public long getMaxRetryMillis() {return maxRetryMillis;}@Overridepublic void setLoadBalancer(ILoadBalancer lb) {        super.setLoadBalancer(lb);subRule.setLoadBalancer(lb);}public Server choose(ILoadBalancer lb, Object key) {long requestTime = System.currentTimeMillis();long deadline = requestTime + maxRetryMillis;Server answer = null;answer = subRule.choose(key);if (((answer == null) || (!answer.isAlive()))&& (System.currentTimeMillis() < deadline)) {InterruptTask task = new InterruptTask(deadline- System.currentTimeMillis());//反复重试while (!Thread.interrupted()) {//选择实例answer = subRule.choose(key);//500ms内没选择到就返回nullif (((answer == null) || (!answer.isAlive()))&& (System.currentTimeMillis() < deadline)) {/* pause and retry hoping it's transient */Thread.yield();} else //若能选择到实例，就返回{break;}}task.cancel();}if ((answer == null) || (!answer.isAlive())) {return null;} else {return answer;}}@Overridepublic Server choose(Object key) {return choose(getLoadBalancer(), key);}@Overridepublic void initWithNiwsConfig(IClientConfig clientConfig) {}
}

3.RandomRule随机策略

/*** Copyright 2013 Netflix, Inc.** Licensed under the Apache License, Version 2.0 (the "License");* you may not use this file except in compliance with the License.* You may obtain a copy of the License at** http://www.apache.org/licenses/LICENSE-2.0** Unless required by applicable law or agreed to in writing, software* distributed under the License is distributed on an "AS IS" BASIS,* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.* See the License for the specific language governing permissions and* limitations under the License.**/
package com.netflix.loadbalancer;import java.util.List;
import java.util.Random;import com.netflix.client.config.IClientConfig;/*** A loadbalacing strategy that randomly distributes traffic amongst existing* servers.* * @author stonse* */
public class RandomRule extends AbstractLoadBalancerRule {Random rand;public RandomRule() {rand = new Random();          //new  一个   Random类对象}/*** Randomly choose from all living servers*/@edu.umd.cs.findbugs.annotations.SuppressWarnings(value = "RCN_REDUNDANT_NULLCHECK_OF_NULL_VALUE")public Server choose(ILoadBalancer lb, Object key) {if (lb == null) {return null;}Server server = null;                      //刚开始不知道服务哪个为nullwhile (server == null) {                  //循环判断服务if (Thread.interrupted()) {           //判断线程是不是中断return null;}List<Server> upList = lb.getReachableServers();    //获取活着的微服务List<Server> allList = lb.getAllServers();         //获取所有的微服务int serverCount = allList.size();                  //统计微服务的数量if (serverCount == 0) {                            ///** No servers. End regardless of pass, because subsequent passes* only get more restrictive.*/return null;}int index = rand.nextInt(serverCount);               //假如有三台微服务serverCount=3   随机获取一个数字(nextInt(3)左闭右开)server = upList.get(index);                          //根据随机数获取集合的一个微服务if (server == null) {                             //如果微服务微null/** The only time this should happen is if the server list were* somehow trimmed. This is a transient condition. Retry after* yielding.*/Thread.yield();                      //线程礼让，continue;                           //继续循环判断}if (server.isAlive()) {                 //假如这个微server是活的return (server);                    //返回这个微服务}// Shouldn't actually happen.. but must be transient or a bug.server = null;Thread.yield();}return server;                               //最终返回这个微服务}@Overridepublic Server choose(Object key) {return choose(getLoadBalancer(), key);}@Overridepublic void initWithNiwsConfig(IClientConfig clientConfig) {// TODO Auto-generated method stub}
}

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Ribbon负载均衡策略-3

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常用策略

1.RoundRobinRule 轮转调度策略

2.RetryRule重试规律策略

3.RandomRule随机策略

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