IRule

　　負載均衡器用來選擇服務器的規則。

public interface IRule{
    public Server choose(Object key);
    public void setLoadBalancer(ILoadBalancer lb);
    public ILoadBalancer getLoadBalancer();    
}

　　通過BaseLoadBalancer的setRule或構造函數來為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提供了部分路由規則。

RandomRule

　　生成一個隨機數，從負載均衡器中選取一個服務器。

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

　　輪詢從負載均衡器中選取一個服務器。

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

　　選擇並發量最小且沒有被熔斷的服務器，需要使用到LoadBalancerStats來獲取服務器的狀態。

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

　　按照響應時間的比例來選擇服務器。

　　首先內部會有一個定時器，定時從負載均衡器裏面讀取服務器的平均響應時間，然後根據平均響應時間轉換成權重。

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);
            }

        }
    }

　　然後根據權重來選擇服務器

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來選擇服務器，並且通過AvailabilityPredicate進行篩選。

ZoneAvoidanceRule

ribbon源碼之負載均衡算法