IRule
负载均衡器用来选择服务器的规则。
public interface IRule{ public Server choose(Object key); public void setLoadBalancer(ILoadBalancer lb); public ILoadBalancer getLoadBalancer(); }
通过BaseLoadBalancer的setRule或构造函数来为BaseLoadBalancer添加IRule
public void setRule(IRule rule) { if (rule != null) { this.rule = rule; } else { /* default rule */ this.rule = new RoundRobinRule(); } if (this.rule.getLoadBalancer() != this) { this.rule.setLoadBalancer(this); } }
ribbon提供了部分路由规则。
RandomRule
生成一个随机数,从负载均衡器中选取一个服务器。
public Server choose(ILoadBalancer lb, Object key) { if (lb == null) { return null; } 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 = rand.nextInt(serverCount); server = upList.get(index); if (server == null) { Thread.yield(); continue; } if (server.isAlive()) { return (server); } server = null; Thread.yield(); } return server; }
RoundRobinRule
轮询从负载均衡器中选取一个服务器。
public Server choose(ILoadBalancer lb, Object key) { if (lb == null) { log.warn("no load balancer"); return null; } Server server = null; int count = 0; 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); } server = null; } if (count >= 10) { log.warn("No available alive servers after 10 tries from load balancer: " + lb); } return server; }
BestAvailableRule
选择并发量最小且没有被熔断的服务器,需要使用到LoadBalancerStats来获取服务器的状态。
public Server choose(Object key) { if (loadBalancerStats == null) { return super.choose(key); } List<Server> serverList = 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
按照响应时间的比例来选择服务器。
首先内部会有一个定时器,定时从负载均衡器里面读取服务器的平均响应时间,然后根据平均响应时间转换成权重。
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); } } } 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) { 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 List<Double> finalWeights = new ArrayList<Double>(); for (Server server : nlb.getAllServers()) { ServerStats ss = stats.getSingleServerStat(server); double weight = totalResponseTime - ss.getResponseTimeAvg(); weightSoFar += weight; finalWeights.add(weightSoFar); } setWeights(finalWeights); } catch (Exception e) { logger.error("Error calculating server weights", e); } finally { serverWeightAssignmentInProgress.set(false); } } }
然后根据权重来选择服务器
public Server choose(ILoadBalancer lb, Object key) { if (lb == null) { return null; } Server server = null; while (server == null) { // get hold of the current reference in case it is changed from the other thread List<Double> currentWeights = accumulatedWeights; if (Thread.interrupted()) { return null; } List<Server> allList = lb.getAllServers(); int serverCount = allList.size(); if (serverCount == 0) { return null; } int serverIndex = 0; // last one in the list is the sum of all weights double maxTotalWeight = currentWeights.size() == 0 ? 0 : currentWeights.get(currentWeights.size() - 1); // No server has been hit yet and total weight is not initialized // fallback to use round robin if (maxTotalWeight < 0.001d) { server = super.choose(getLoadBalancer(), key); if(server == null) { return server; } } else { // generate a random weight between 0 (inclusive) to maxTotalWeight (exclusive) 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); } if (server == null) { /* Transient. */ Thread.yield(); continue; } if (server.isAlive()) { return (server); } // Next. server = null; } return server; }
AvailabilityFilteringRule
使用RoundRobinRule来选择服务器,并且通过AvailabilityPredicate进行筛选。
ZoneAvoidanceRule