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IRule是选择服务的一种策略。
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IRule
public interface IRule{ /* * choose one alive server from lb.allServers or * lb.upServers according to key * * @return choosen Server object. NULL is returned if none * server is available */ public Server choose(Object key); public void setLoadBalancer(ILoadBalancer lb); public ILoadBalancer getLoadBalancer(); }
choose选择可用的服务。
RandomRule
随机选择一个UP的服务。
Random rand; // 随机计数器 public RandomRule() { rand = new Random(); } public Server choose(ILoadBalancer lb, Object key) { ... ListupList = lb.getReachableServers(); List allList = lb.getAllServers(); int index = rand.nextInt(serverCount); // 随机选择一个 server = upList.get(index); ... }
RoundRobinRule
轮询获取服务。
public RoundRobinRule() { nextServerCyclicCounter = new AtomicInteger(0);// int线程安全计数器 } public Server choose(ILoadBalancer lb, Object key) { ... int nextServerIndex = incrementAndGetModulo(serverCount); // nextServerCyclicCounter依次向后获取服务。 server = allServers.get(nextServerIndex); ... } // 轮询方法 private int incrementAndGetModulo(int modulo) { for (;;) { int current = nextServerCyclicCounter.get(); int next = (current + 1) % modulo; if (nextServerCyclicCounter.compareAndSet(current, next)) return next; } }
BestAvailableRule
跳过熔断的服务,获取请求数最少的服务.通常与ServerListSubsetFilter一起使用.
public Server choose(Object key) { if (loadBalancerStats == null) { return super.choose(key); // 如果没有loadBalancerStats,则采用RoundRibonRule. } ListserverList = getLoadBalancer().getAllServers(); int minimalConcurrentConnections = Integer.MAX_VALUE; long currentTime = System.currentTimeMillis(); Server chosen = null; for (Server server: serverList) { ServerStats serverStats = loadBalancerStats.getSingleServerStat(server); if (!serverStats.isCircuitBreakerTripped(currentTime)) { int concurrentConnections = serverStats.getActiveRequestsCount(currentTime); if (concurrentConnections < minimalConcurrentConnections) { minimalConcurrentConnections = concurrentConnections; chosen = server; } } } if (chosen == null) { return super.choose(key); } else { return chosen; } }
WeightedResponseTimeRule
权重的方式挑选服务.服务实例响应时间越小的服务,则更容易被选中.如果服务实例响应的时间相差不大的,排在前面的服务实例更容易被选中.
// 继承了RoundRobinRule,也就是当WeightedResponseTimeRule不满足条件的时候,则采用RoundRobinRule的方式. public class WeightedResponseTimeRule extends RoundRobinRule { // 这个方式很重要,就是定时的计算每个服务实例的响应时间,并以此作为每个服务实例的权重. void initialize(ILoadBalancer lb) { if (serverWeightTimer != null) { serverWeightTimer.cancel(); } serverWeightTimer = new Timer("NFLoadBalancer-serverWeightTimer-" + name, true); serverWeightTimer.schedule(new DynamicServerWeightTask(), 0,serverWeightTaskTimerInterval); // do a initial run ServerWeight sw = new ServerWeight(); sw.maintainWeights(); Runtime.getRuntime().addShutdownHook(new Thread(new Runnable() { public void run() { logger.info("Stopping NFLoadBalancer-serverWeightTimer-"+ name); serverWeightTimer.cancel(); } })); } // 定时任务内部类 class DynamicServerWeightTask extends TimerTask { public void run() { ServerWeight serverWeight = new ServerWeight(); try { serverWeight.maintainWeights(); } catch (Exception e) { logger.error("Error running DynamicServerWeightTask for {}", name, e); } } } // 计算服务实例权重的核心方法. class ServerWeight { public void maintainWeights() { ILoadBalancer lb = getLoadBalancer(); if (lb == null) { return; } if (!serverWeightAssignmentInProgress.compareAndSet(false, true)) { return; } try { logger.info("Weight adjusting job started"); AbstractLoadBalancer nlb = (AbstractLoadBalancer) lb; LoadBalancerStats stats = nlb.getLoadBalancerStats(); if (stats == null) { // no statistics, nothing to do return; } double totalResponseTime = 0; // find maximal 95% response time for (Server server : nlb.getAllServers()) { // this will automatically load the stats if not in cache ServerStats ss = stats.getSingleServerStat(server); totalResponseTime += ss.getResponseTimeAvg(); } // weight for each server is (sum of responseTime of all servers - responseTime) // so that the longer the response time, the less the weight and the less likely to be chosen Double weightSoFar = 0.0; // create new list and hot swap the reference ListfinalWeights = new ArrayList (); for (Server server : nlb.getAllServers()) { ServerStats ss = stats.getSingleServerStat(server); double weight = totalResponseTime - ss.getResponseTimeAvg(); // 平均响应时间越短,则权重越大,就越容易被选中. weightSoFar += weight; finalWeights.add(weightSoFar); } setWeights(finalWeights); } catch (Exception e) { logger.error("Error calculating server weights", e); } finally { serverWeightAssignmentInProgress.set(false); } } } public Server choose(ILoadBalancer lb, Object key) { ... // 根据权重选择服务的核心代码 double randomWeight = random.nextDouble() * maxTotalWeight; // pick the server index based on the randomIndex int n = 0; for (Double d : currentWeights) { if (d >= randomWeight) { serverIndex = n; break; } else { n++; } } server = allList.get(serverIndex); ... } }
RetryRule
在RoundRobinRule的基础上,增加了重试的机制.