JAVA前線?

歡迎大家關(guān)注公眾號「JAVA前線」查看更多精彩分享，主要內(nèi)容包括源碼分析、實際應(yīng)用、架構(gòu)思維、職場分享、產(chǎn)品思考等等，同時也非常歡迎大家加我微信「java_front」一起交流學(xué)習(xí)

1 三組概念

負(fù)載均衡、集群容錯、服務(wù)降級這三個概念在DUBBO中非常重要，同理其它分布式框架也都有相同或者相近之概念。

從調(diào)用順序角度分析，調(diào)用順序依次是負(fù)載均衡、集群容錯、服務(wù)降級。從解決問題角度分析，負(fù)載均衡解決了「選哪一個」問題，集群容錯解決了「換哪一個」問題，服務(wù)降級解決了「全錯怎么辦」問題。

假設(shè)有1個服務(wù)消費者面對10個提供者，這時面臨第一個問題就是「選哪一個」進(jìn)行調(diào)用，所以負(fù)載均衡最先調(diào)用，假設(shè)選定了5號服務(wù)提供者進(jìn)行服務(wù)調(diào)用。

假設(shè)消費者調(diào)用5號提供者發(fā)生了超時異常，這時面臨第二個問題就是「換哪一個」進(jìn)行調(diào)用：5號超時要不要換1號試一試，或者直接返回不進(jìn)行重試，所以集群容錯第二個調(diào)用。

假設(shè)已經(jīng)重試了1號、3號、6號提供者全部超時，這時面臨「全錯怎么辦」這第三個問題，這時可以直接返回一個固定值或者提示文案，所以服務(wù)降級第三個調(diào)用。

負(fù)載均衡作為整個鏈路第一個節(jié)點非常重要，本文結(jié)合DUBBO源碼分析以下七種負(fù)載均衡策略：

簡單隨機
加權(quán)隨機
簡單輪詢
簡單加權(quán)輪詢
平滑加權(quán)輪詢
一致性哈希
最少活躍數(shù)

2 簡單隨機

簡單隨機含義是服務(wù)消費者每次會任意訪問一個服務(wù)提供者，并且從概率角度看每個提供者被訪問概率一致，可以通過指定范圍隨機數(shù)實現(xiàn)。第一步編寫服務(wù)器代碼

public?class?MyServer?{

????private?String?ip;

????public?MyServer(String?ip)?{
????????this.ip?=?ip;
????}

????public?String?getIp()?{
????????return?ip;
????}

????public?void?setIp(String?ip)?{
????????this.ip?=?ip;
????}
}

第二步編寫基礎(chǔ)負(fù)載均衡策略

public?abstract?class?AbstractLoadBalance?{

????public?MyServer?select(List?serverList)?{
????????return?doSelect(serverList);
????}

????public?abstract?MyServer?doSelect(List?serverList);
}

第三步編寫簡單隨機策略

public?class?RandomBalance?extends?AbstractLoadBalance?{

????@Override
????public?MyServer?doSelect(List?serverList)?{
????????//?隨機數(shù)范圍[0,serverListSize)
????????int?index?=?ThreadLocalRandom.current().nextInt(serverList.size());
????????return?serverList.get(index);
????}
}

第四步編寫測試代碼

public?class?LoadBalanceTest?{

????public?static?void?main(String[]?args)?{
????????List?serverList?=?buildData();
????????testRandomBalance(serverList);
????}

????public?static?void?testRandomBalance(List?serverList)?{
????????AbstractLoadBalance?randomBalance?=?new?RandomBalance();
????????for?(int?i?=?0;?i?10;?i++)?{
????????????MyServer?server?=?randomBalance.select(serverList);
????????????System.out.println("RandomBalance?route?server="?+?server);
????????}
????}

????public?static?List?buildData()?{
????????List?serverList?=?new?ArrayList();
????????MyServer?server1?=?new?MyServer("192.1.1.1");
????????MyServer?server2?=?new?MyServer("192.1.1.2");
????????MyServer?server3?=?new?MyServer("192.1.1.3");
????????serverList.add(server1);
????????serverList.add(server2);
????????serverList.add(server3);
????????return?serverList;
????}
}

第五步輸出結(jié)果，循環(huán)次數(shù)越多結(jié)果越準(zhǔn)確

RandomBalance route server=MyServer(ip=192.1.1.2)
RandomBalance route server=MyServer(ip=192.1.1.1)
RandomBalance route server=MyServer(ip=192.1.1.3)
RandomBalance route server=MyServer(ip=192.1.1.2)
RandomBalance route server=MyServer(ip=192.1.1.1)
RandomBalance route server=MyServer(ip=192.1.1.1)
RandomBalance route server=MyServer(ip=192.1.1.2)
RandomBalance route server=MyServer(ip=192.1.1.2)
RandomBalance route server=MyServer(ip=192.1.1.3)
RandomBalance route server=MyServer(ip=192.1.1.3)

3 加權(quán)隨機

3.1 設(shè)計思路

加權(quán)隨機新增了權(quán)重概念，假設(shè)服務(wù)器A權(quán)重等于1，服務(wù)器B權(quán)重等于5，從概率角度看B服務(wù)器被訪問概率5倍于A服務(wù)器。實現(xiàn)按照權(quán)重訪問有很多種方式，我們選擇使用概率區(qū)間這個思路。

假設(shè)現(xiàn)在有三臺服務(wù)器，服務(wù)器權(quán)重分別是3、5、2，那么三者構(gòu)成如下圖概率區(qū)間：

假設(shè)隨機數(shù)等于8，其位于[8,9]區(qū)間，所以選擇server3，下圖說明了概率區(qū)間計算步驟：

3.2 代碼實例

第一步編寫服務(wù)器代碼

public?class?MyServer?{

????private?String?ip;

????private?int?weight;

????public?MyServer(String?ip)?{
????????this.ip?=?ip;
????}

????public?String?getIp()?{
????????return?ip;
????}

????public?void?setIp(String?ip)?{
????????this.ip?=?ip;
????}

????public?int?getWeight()?{
????????return?weight;
????}

????public?void?setWeight(int?weight)?{
????????this.weight?=?weight;
????}
}

第二步編寫加權(quán)隨機策略

public?class?RandomWeightBalance?extends?AbstractLoadBalance?{

????@Override
????public?MyServer?doSelect(List?serverList)?{
????????//?所有服務(wù)器總權(quán)重
????????int?totalWeight?=?0;
????????//?第一個服務(wù)器權(quán)重
????????int?firstWeight?=?serverList.get(0).getWeight();
????????//?所有服務(wù)器權(quán)重相等
????????boolean?sameWeight?=?true;
????????//?遍歷所有服務(wù)器
????????for?(MyServer?server?:?serverList)?{
????????????//?計算總權(quán)重
????????????totalWeight?+=?server.getWeight();
????????????//?任意一個invoker權(quán)重不等于第一個權(quán)重則設(shè)置sameWeight=false
????????????if?(sameWeight?&&?server.getWeight()?!=?firstWeight)?{
????????????????sameWeight?=?false;
????????????}
????????}
????????//?權(quán)重不相等則根據(jù)權(quán)重選擇
????????if?(!sameWeight)?{
????????????//?在總區(qū)間范圍[0,totalWeight)生成隨機數(shù)A
????????????Integer?offset?=?ThreadLocalRandom.current().nextInt(totalWeight);
????????????//?遍歷所有服務(wù)器區(qū)間
????????????for?(MyServer?server?:?serverList)?{
????????????????//?如果A在server區(qū)間直接返回
????????????????if?(offset?????????????????????return?server;
????????????????}
????????????????//?如果A不在server區(qū)間則減去此區(qū)間范圍并繼續(xù)匹配其它區(qū)間
????????????????offset?-=?server.getWeight();
????????????}
????????}
????????//?所有服務(wù)器權(quán)重相等則隨機選擇
????????return?serverList.get(ThreadLocalRandom.current().nextInt(serverList.size()));
????}
}

第三步編寫測試代碼

public?class?LoadBalanceTest?{

????public?static?void?main(String[]?args)?{
????????List?serverList?=?buildData();
????????testRandomWeightBalance(serverList);
????}

????public?static?void?testRandomWeightBalance(List?serverList)?{
????????AbstractLoadBalance?randomBalance?=?new?RandomWeightBalance();
????????for?(int?i?=?0;?i?10;?i++)?{
????????????MyServer?server?=?randomBalance.select(serverList);
????????????System.out.println("RandomWeightBalance?route?server="?+?server);
????????}
????}

????public?static?List?buildData()?{
????????List?serverList?=?new?ArrayList();
????????MyServer?server1?=?new?MyServer("192.1.1.1",?3);
????????MyServer?server2?=?new?MyServer("192.1.1.2",?5);
????????MyServer?server3?=?new?MyServer("192.1.1.3",?2);
????????serverList.add(server1);
????????serverList.add(server2);
????????serverList.add(server3);
????????return?serverList;
????}
}

第四步輸出結(jié)果，循環(huán)次數(shù)越多結(jié)果越準(zhǔn)確

RandomWeightBalance route server=MyServer(ip=192.1.1.2, weight=2)
RandomWeightBalance route server=MyServer(ip=192.1.1.2, weight=3)
RandomWeightBalance route server=MyServer(ip=192.1.1.1, weight=3)
RandomWeightBalance route server=MyServer(ip=192.1.1.1, weight=3)
RandomWeightBalance route server=MyServer(ip=192.1.1.3, weight=2)
RandomWeightBalance route server=MyServer(ip=192.1.1.3, weight=2)
RandomWeightBalance route server=MyServer(ip=192.1.1.2, weight=5)
RandomWeightBalance route server=MyServer(ip=192.1.1.1, weight=3)
RandomWeightBalance route server=MyServer(ip=192.1.1.2, weight=5)
RandomWeightBalance route server=MyServer(ip=192.1.1.2, weight=5)

3.3 DUBBO源碼

public?class?RandomLoadBalance?extends?AbstractLoadBalance?{
????public?static?final?String?NAME?=?"random";

????@Override
????protected??Invoker?doSelect(List>?invokers,?URL?url,?Invocation?invocation)?{

????????//?invoker數(shù)量
????????int?length?=?invokers.size();

????????//?所有權(quán)重是否相等
????????boolean?sameWeight?=?true;

????????//?權(quán)重數(shù)組
????????int[]?weights?=?new?int[length];

????????//?第一個權(quán)重
????????int?firstWeight?=?getWeight(invokers.get(0),?invocation);
????????weights[0]?=?firstWeight;

????????//?權(quán)重之和
????????int?totalWeight?=?firstWeight;

????????//?遍歷所有invoker
????????for?(int?i?=?1;?i?
????????????//?獲取權(quán)重
????????????int?weight?=?getWeight(invokers.get(i),?invocation);
????????????weights[i]?=?weight;

????????????//?計算總權(quán)重
????????????totalWeight?+=?weight;

????????????//?任意一個invoker權(quán)重不等于第一個權(quán)重則設(shè)置sameWeight=false
????????????if?(sameWeight?&&?weight?!=?firstWeight)?{
????????????????sameWeight?=?false;
????????????}
????????}
????????//?權(quán)重不相等則根據(jù)權(quán)重選擇
????????if?(totalWeight?>?0?&&?!sameWeight)?{
????????????int?offset?=?ThreadLocalRandom.current().nextInt(totalWeight);
????????????for?(int?i?=?0;?i?????????????????offset?-=?weights[i];
????????????????if?(offset?0)?{
????????????????????return?invokers.get(i);
????????????????}
????????????}
????????}
????????//?所有服務(wù)權(quán)重相等則隨機選擇
????????return?invokers.get(ThreadLocalRandom.current().nextInt(length));
????}
}

4 簡單輪詢

簡單輪詢含義是服務(wù)消費者每次會依次訪問一個服務(wù)提供者，并且從概率角度看每個提供者被訪問概率一致，可以通過原子變量累加實現(xiàn)。第一步編寫簡單輪詢策略

public?class?RoundRobinBalance?extends?AbstractLoadBalance?{
????private?AtomicInteger?atomicIndex?=?new?AtomicInteger(0);

????@Override
????public?MyServer?doSelect(List?serverList)?{
????????//?atomicIndex自增大于服務(wù)器數(shù)量時取余
????????int?index?=?atomicIndex.getAndIncrement()?%?serverList.size();
????????return?serverList.get(index);
????}
}

第二步編寫測試代碼

public?class?LoadBalanceTest?{

????public?static?void?main(String[]?args)?{
????????List?serverList?=?buildData();
????????testRoundRobinBalance(serverList);
????}

????public?static?void?testRoundRobinBalance(List?serverList)?{
????????AbstractLoadBalance?roundRobinBalance?=?new?RoundRobinBalance();
????????for?(int?i?=?0;?i?10;?i++)?{
????????????MyServer?server?=?roundRobinBalance.select(serverList);
????????????System.out.println("RoundRobinBalance?route?server="?+?server);
????????}
????}

????public?static?List?buildData()?{
????????List?serverList?=?new?ArrayList();
????????MyServer?server1?=?new?MyServer("192.1.1.1");
????????MyServer?server2?=?new?MyServer("192.1.1.2");
????????MyServer?server3?=?new?MyServer("192.1.1.3");
????????serverList.add(server1);
????????serverList.add(server2);
????????serverList.add(server3);
????????return?serverList;
????}
}

第三步輸出結(jié)果

RoundRobinBalance route server=MyServer(ip=192.1.1.1)
RoundRobinBalance route server=MyServer(ip=192.1.1.2)
RoundRobinBalance route server=MyServer(ip=192.1.1.3)
RoundRobinBalance route server=MyServer(ip=192.1.1.1)
RoundRobinBalance route server=MyServer(ip=192.1.1.2)
RoundRobinBalance route server=MyServer(ip=192.1.1.3)
RoundRobinBalance route server=MyServer(ip=192.1.1.1)
RoundRobinBalance route server=MyServer(ip=192.1.1.2)
RoundRobinBalance route server=MyServer(ip=192.1.1.3)
RoundRobinBalance route server=MyServer(ip=192.1.1.1)

5 簡單加權(quán)輪詢

簡單加權(quán)輪詢新增了權(quán)重概念，假設(shè)服務(wù)器A權(quán)重等于1，服務(wù)器B權(quán)重等于5，從概率角度看B服務(wù)器被訪問概率5倍于A服務(wù)器，我們還是使用概率區(qū)間這個思路，相較于加權(quán)隨機會有一些變化。

第一步編寫簡單加權(quán)輪詢策略

public?class?RoundRobinWeightBalance1?extends?AbstractLoadBalance?{
????private?AtomicInteger?atomicIndex?=?new?AtomicInteger(0);

????@Override
????public?MyServer?doSelect(List?serverList)?{
????????int?totalWeight?=?0;
????????int?firstWeight?=?serverList.get(0).getWeight();
????????boolean?sameWeight?=?true;
????????for?(MyServer?server?:?serverList)?{
????????????totalWeight?+=?server.getWeight();
????????????if?(sameWeight?&&?server.getWeight()?!=?firstWeight)?{
????????????????sameWeight?=?false;
????????????}
????????}
????????if?(!sameWeight)?{
????????????//?自增方式計算offset
????????????int?offset?=?atomicIndex.getAndIncrement()?%?totalWeight;
????????????for?(MyServer?server?:?serverList)?{
????????????????if?(offset?????????????????????return?server;
????????????????}
????????????????offset?-=?server.getWeight();
????????????}
????????}
????????int?index?=?atomicIndex.getAndIncrement()?%?serverList.size();
????????return?serverList.get(index);
????}
}

第二步編寫測試代碼

public?class?LoadBalanceTest?{

????public?static?void?main(String[]?args)?{
????????List?serverList?=?buildData();
????????testRoundRobinWeightBalance1(serverList);
????}

????public?static?void?testRoundRobinWeightBalance1(List?serverList)?{
????????AbstractLoadBalance?roundRobinBalance?=?new?RoundRobinWeightBalance1();
????????for?(int?i?=?0;?i?10;?i++)?{
????????????MyServer?server?=?roundRobinBalance.select(serverList);
????????????System.out.println("RoundRobinWeightBalance1?route?server="?+?server);
????????}
????}

????public?static?List?buildData()?{
????????List?serverList?=?new?ArrayList();
????????MyServer?server1?=?new?MyServer("192.1.1.1",?3);
????????MyServer?server2?=?new?MyServer("192.1.1.2",?5);
????????MyServer?server3?=?new?MyServer("192.1.1.3",?2);
????????serverList.add(server1);
????????serverList.add(server2);
????????serverList.add(server3);
????????return?serverList;
????}
}

第三步輸出結(jié)果

RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.1, weight=3)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.1, weight=3)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.1, weight=3)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.2, weight=5)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.2, weight=5)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.2, weight=5)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.2, weight=5)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.2, weight=5)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.3, weight=2)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.3, weight=2)

6 平滑加權(quán)輪詢

6.1 設(shè)計思路

簡單加權(quán)輪詢有什么問題？我們分析其輸出結(jié)果發(fā)現(xiàn)，連續(xù)3次訪問服務(wù)器1，連續(xù)5次訪問服務(wù)器2，連續(xù)2次訪問服務(wù)器3，所以簡單加權(quán)輪詢策略會導(dǎo)致請求集中問題。

RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.1, weight=3)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.1, weight=3)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.1, weight=3)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.2, weight=5)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.2, weight=5)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.2, weight=5)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.2, weight=5)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.2, weight=5)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.3, weight=2)
RoundRobinWeightBalance1 route server=MyServer(ip=192.1.1.3, weight=2)

所以需要使用平滑加權(quán)輪詢策略，將請求比較均勻地分散至各個服務(wù)器，下圖說明了計算步驟：

6.2 代碼實例

第一步編寫服務(wù)器代碼

public?class?MyServer?{

????private?String?ip;

????private?int?weight;

????private?int?currentWeight?=?0;

????public?MyServer(String?ip)?{
????????this.ip?=?ip;
????}

????public?MyServer(String?ip,?int?weight)?{
????????this.ip?=?ip;
????????this.weight?=?weight;
????}

????public?int?getWeight()?{
????????return?weight;
????}

????public?void?setWeight(int?weight)?{
????????this.weight?=?weight;
????}

????public?int?getCurrentWeight()?{
????????return?currentWeight;
????}

????public?void?setCurrentWeight(int?currentWeight)?{
????????this.currentWeight?=?currentWeight;
????}

????public?String?getIp()?{
????????return?ip;
????}

????public?void?setIp(String?ip)?{
????????this.ip?=?ip;
????}
}

第二步編寫平滑加權(quán)輪詢策略

public?class?RoundRobinWeightBalance2?extends?AbstractLoadBalance?{
????private?AtomicInteger?atomicIndex?=?new?AtomicInteger(0);

????@Override
????public?MyServer?doSelect(List?serverList)?{
????????int?totalWeight?=?0;
????????int?firstWeight?=?serverList.get(0).getWeight();
????????boolean?sameWeight?=?true;
????????for?(MyServer?server?:?serverList)?{
????????????totalWeight?+=?server.getWeight();
????????????if?(sameWeight?&&?server.getWeight()?!=?firstWeight)?{
????????????????sameWeight?=?false;
????????????}
????????????//?設(shè)置動態(tài)權(quán)重?->?currentWeight?+=?weight
????????????server.setCurrentWeight(server.getCurrentWeight()?+?server.getWeight());
????????}
????????if?(!sameWeight)?{
????????????//?最大動態(tài)權(quán)重服務(wù)器?->?max(currentWeight)
????????????MyServer?maxCurrentWeightServer?=?serverList.stream().max((s1,?s2)?->?s1.getCurrentWeight()?-?s2.getCurrentWeight()).get();
????????????//?設(shè)置最大動態(tài)權(quán)重?->?max(currentWeight)?-?totalWeight
????????????maxCurrentWeightServer.setCurrentWeight(maxCurrentWeightServer.getCurrentWeight()?-?totalWeight);
????????????//?返回最大動態(tài)權(quán)重服務(wù)器
????????????return?maxCurrentWeightServer;
????????}
????????//?權(quán)重相同依次輪詢
????????int?index?=?atomicIndex.getAndIncrement()?%?serverList.size();
????????return?serverList.get(index);
????}
}

第三步編寫測試代碼

public?class?LoadBalanceTest?{

????public?static?void?main(String[]?args)?{
????????List?serverList?=?buildData();
????????testRoundRobinWeightBalance2(serverList);
????}

????public?static?void?testRoundRobinWeightBalance2(List?serverList)?{
????????AbstractLoadBalance?roundRobinBalance?=?new?RoundRobinWeightBalance2();
????????for?(int?i?=?0;?i?10;?i++)?{
????????????MyServer?server?=?roundRobinBalance.select(serverList);
????????????System.out.println("RoundRobinWeightBalance2?route?server="?+?server);
????????}
????}

????public?static?List?buildData()?{
????????List?serverList?=?new?ArrayList();
????????MyServer?server1?=?new?MyServer("192.1.1.1",?3);
????????MyServer?server2?=?new?MyServer("192.1.1.2",?5);
????????MyServer?server3?=?new?MyServer("192.1.1.3",?2);
????????serverList.add(server1);
????????serverList.add(server2);
????????serverList.add(server3);
????????return?serverList;
????}
}

第四步輸出結(jié)果

RoundRobinWeightBalance2 route server=MyServer(ip=192.1.1.2, weight=5, currentWeight=-5)
RoundRobinWeightBalance2 route server=MyServer(ip=192.1.1.1, weight=3, currentWeight=-4)
RoundRobinWeightBalance2 route server=MyServer(ip=192.1.1.3, weight=2, currentWeight=-4)
RoundRobinWeightBalance2 route server=MyServer(ip=192.1.1.2, weight=5, currentWeight=0)
RoundRobinWeightBalance2 route server=MyServer(ip=192.1.1.1, weight=3, currentWeight=-5)
RoundRobinWeightBalance2 route server=MyServer(ip=192.1.1.2, weight=5, currentWeight=0)
RoundRobinWeightBalance2 route server=MyServer(ip=192.1.1.2, weight=5, currentWeight=-5)
RoundRobinWeightBalance2 route server=MyServer(ip=192.1.1.3, weight=2, currentWeight=-4)
RoundRobinWeightBalance2 route server=MyServer(ip=192.1.1.1, weight=3, currentWeight=-3)
RoundRobinWeightBalance2 route server=MyServer(ip=192.1.1.2, weight=5, currentWeight=0)

6.3 DUBBO源碼

public?class?RoundRobinLoadBalance?extends?AbstractLoadBalance?{
????public?static?final?String?NAME?=?"roundrobin";

????private?static?int?RECYCLE_PERIOD?=?60000;

????protected?static?class?WeightedRoundRobin?{

????????//?權(quán)重
????????private?int?weight;

????????//?動態(tài)權(quán)重
????????private?AtomicLong?current?=?new?AtomicLong(0);

????????//?更新時間
????????private?long?lastUpdate;

????????public?int?getWeight()?{
????????????return?weight;
????????}

????????public?void?setWeight(int?weight)?{
????????????this.weight?=?weight;
????????????current.set(0);
????????}

????????public?long?increaseCurrent()?{
????????????return?current.addAndGet(weight);
????????}

????????public?void?sel(int?total)?{
????????????current.addAndGet(-1?*?total);
????????}

????????public?long?getLastUpdate()?{
????????????return?lastUpdate;
????????}

????????public?void?setLastUpdate(long?lastUpdate)?{
????????????this.lastUpdate?=?lastUpdate;
????????}
????}

????private?ConcurrentMap>?methodWeightMap?=?new?ConcurrentHashMap>();
????private?AtomicBoolean?updateLock?=?new?AtomicBoolean();

????protected??Collection?getInvokerAddrList(List>?invokers,?Invocation?invocation)?{
????????String?key?=?invokers.get(0).getUrl().getServiceKey()?+?"."?+?invocation.getMethodName();
????????Map?map?=?methodWeightMap.get(key);
????????if?(map?!=?null)?{
????????????return?map.keySet();
????????}
????????return?null;
????}

????@Override
????protected??Invoker?doSelect(List>?invokers,?URL?url,?Invocation?invocation)?{
????????String?key?=?invokers.get(0).getUrl().getServiceKey()?+?"."?+?invocation.getMethodName();
????????ConcurrentMap?map?=?methodWeightMap.get(key);
????????if?(map?==?null)?{
????????????methodWeightMap.putIfAbsent(key,?new?ConcurrentHashMap());
????????????map?=?methodWeightMap.get(key);
????????}
????????//?總權(quán)重
????????int?totalWeight?=?0;

????????//?最大當(dāng)前權(quán)重
????????long?maxCurrent?=?Long.MIN_VALUE;

????????//?當(dāng)前時間
????????long?now?=?System.currentTimeMillis();

????????//?選中提供者
????????Invoker?selectedInvoker?=?null;

????????//?選中提供者權(quán)重對象
????????WeightedRoundRobin?selectedWRR?=?null;

????????//?遍歷所有提供者
????????for?(Invoker?invoker?:?invokers)?{
????????????String?identifyString?=?invoker.getUrl().toIdentityString();
????????????WeightedRoundRobin?weightedRoundRobin?=?map.get(identifyString);

????????????//?獲取權(quán)重
????????????int?weight?=?getWeight(invoker,?invocation);
????????????if?(weightedRoundRobin?==?null)?{
????????????????weightedRoundRobin?=?new?WeightedRoundRobin();
????????????????weightedRoundRobin.setWeight(weight);
????????????????map.putIfAbsent(identifyString,?weightedRoundRobin);
????????????}
????????????if?(weight?!=?weightedRoundRobin.getWeight())?{
????????????????weightedRoundRobin.setWeight(weight);
????????????}
????????????//?選擇動態(tài)權(quán)重最大提供者
????????????long?cur?=?weightedRoundRobin.increaseCurrent();
????????????weightedRoundRobin.setLastUpdate(now);
????????????if?(cur?>?maxCurrent)?{
????????????????maxCurrent?=?cur;
????????????????selectedInvoker?=?invoker;
????????????????selectedWRR?=?weightedRoundRobin;
????????????}
????????????//?計算總權(quán)重
????????????totalWeight?+=?weight;
????????}
????????//?更新負(fù)載均衡容器
????????if?(!updateLock.get()?&&?invokers.size()?!=?map.size())?{
????????????if?(updateLock.compareAndSet(false,?true))?{
????????????????try?{
????????????????????ConcurrentMap?newMap?=?new?ConcurrentHashMap();
????????????????????newMap.putAll(map);
????????????????????Iterator>?it?=?newMap.entrySet().iterator();
????????????????????while?(it.hasNext())?{
????????????????????????Entry?item?=?it.next();
????????????????????????if?(now?-?item.getValue().getLastUpdate()?>?RECYCLE_PERIOD)?{
????????????????????????????it.remove();
????????????????????????}
????????????????????}
????????????????????methodWeightMap.put(key,?newMap);
????????????????}?finally?{
????????????????????updateLock.set(false);
????????????????}
????????????}
????????}
????????if?(selectedInvoker?!=?null)?{
????????????//?最大動態(tài)權(quán)重減去總權(quán)重
????????????selectedWRR.sel(totalWeight);
????????????return?selectedInvoker;
????????}
????????return?invokers.get(0);
????}
}

7 一致性哈希

一致性哈希策略具有三個顯著特性：第一是在不新增或者刪除提供者情況下，同一個客戶端總是可以訪問到同一個提供者。第二是一致性哈希可以有效分散新增或者刪除服務(wù)提供者帶來的波動性。第三是一致性哈希虛擬節(jié)點可以更加有效分散特性二之波動性。

7.1 特性分析

(1) 特性一

在不新增或者刪除提供者情況下，同一個客戶端總是可以訪問同一個提供者。第一步6個提供者分布在哈希環(huán)中，第二步client1發(fā)起訪問請求，此時計算客戶端哈希值位于哈希環(huán)位置，第三步沿著哈希環(huán)順時針旋轉(zhuǎn)，找到與客戶端哈希值最近的提供者server5。當(dāng)哈希環(huán)結(jié)構(gòu)不發(fā)生改變時，client1總是路由到server5。

哈希環(huán)應(yīng)該選擇什么數(shù)據(jù)結(jié)構(gòu)呢？我們可以選擇TreeMap構(gòu)建哈希環(huán)，其底層使用了紅黑樹。

public?class?TreeMapTest?{

????public?static?void?main(String[]?args)?{
????
????????//?構(gòu)建哈希環(huán)
????????TreeMap?treeMap?=?new?TreeMap();
????????treeMap.put(1,?new?MyServer("1"));
????????treeMap.put(2,?new?MyServer("2"));
????????treeMap.put(3,?new?MyServer("3"));
????????treeMap.put(4,?new?MyServer("4"));
????????treeMap.put(5,?new?MyServer("5"));
????????treeMap.put(6,?new?MyServer("6"));

????????//?找到第一個大于客戶端哈希值的服務(wù)器
????????Integer?clientHashCode?=?5;
????????SortedMap?tailMap?=?treeMap.tailMap(clientHashCode,?false);
????????MyServer?server?=?tailMap.get(tailMap.firstKey());

????????//?MyServer(ip=6)
????????System.out.println(server);
????}
}

(2) 特性二

一致性哈希可以有效分散新增或者刪除提供者帶來的波動性，例如新增服務(wù)器server7，但是并不影響client1路由結(jié)果：

服務(wù)器server5發(fā)生宕機只會影響client1路由結(jié)果，并不會影響其它客戶端路由結(jié)果：

(3) 特性三

一致性哈希虛擬節(jié)點可以更加有效分散特性二之波動性，例如我們可以為每個服務(wù)器節(jié)點新增一個虛擬節(jié)點，使得服務(wù)器分散得更加均勻：

7.2 代碼實例

第一步編寫基礎(chǔ)負(fù)載均衡策略

public?abstract?class?AbstractConsistentHashLoadBalance?{

????public?MyServer?select(String?clientIP,?List?serverList)?{
????????return?doSelect(clientIP,?serverList);
????}

????public?abstract?MyServer?doSelect(String?clientIP,?List?serverList);
}

第二步編寫一致性哈希策略

public?class?ConsistentHashBalance1?extends?AbstractConsistentHashLoadBalance?{
????private?ConsistentHashSelector?consistentHashSelector;

????@Override
????public?MyServer?doSelect(String?clientIP,?List?serverList)?{
????????initialConsistentHashSelector(serverList);
????????return?consistentHashSelector.select(clientIP);
????}

????private?class?ConsistentHashSelector?{
????????private?Integer?identityHashCode;
????????private?TreeMap/*?hashcode?*/,?MyServer>?serverNodes?=?new?TreeMap();

????????//?構(gòu)建哈希環(huán)
????????public?ConsistentHashSelector(Integer?identityHashCode,?List?serverList)?{
????????????this.identityHashCode?=?identityHashCode;
????????????TreeMap?newServerNodes?=?new?TreeMap();
????????????for?(MyServer?server?:?serverList)?{
????????????????newServerNodes.put(hashCode(server.getIp()),?server);
????????????}
????????????serverNodes?=?newServerNodes;
????????}

????????//?根據(jù)客戶端IP路由
????????public?MyServer?select(String?clientIP)?{

????????????//?計算客戶端哈希值
????????????int?clientHashCode?=?hashCode(clientIP);

????????????//?找到第一個大于客戶端哈希值的服務(wù)器
????????????SortedMap?tailMap?=?serverNodes.tailMap(clientHashCode,?false);
????????????if?(CollectionUtils.isEmpty(tailMap))?{
????????????????Integer?firstKey?=?serverNodes.firstKey();
????????????????return?serverNodes.get(firstKey);
????????????}

????????????//?找不到表示在最后一個節(jié)點和第一個節(jié)點之間?->選擇第一個節(jié)點
????????????Integer?firstKey?=?tailMap.firstKey();
????????????return?tailMap.get(firstKey);
????????}

????????//?計算哈希值
????????private?int?hashCode(String?key)?{
????????????return?Objects.hashCode(key);
????????}

????????//?提供者列表哈希值?->?如果新增或者刪除提供者會發(fā)生變化
????????public?Integer?getIdentityHashCode()?{
????????????return?identityHashCode;
????????}
????}

????private?void?initialConsistentHashSelector(List?serverList)?{

????????//?計算提供者列表哈希值
????????Integer?newIdentityHashCode?=?System.identityHashCode(serverList);

????????//?提供者列表哈希值沒有變化則無需重新構(gòu)建哈希環(huán)
????????if?(null?!=?consistentHashSelector?&&?(null?!=?consistentHashSelector.getIdentityHashCode()?&&?newIdentityHashCode?==?consistentHashSelector.getIdentityHashCode()))?{
????????????return;
????????}
????????//?提供者列表哈希值發(fā)生變化則重新構(gòu)建哈希環(huán)
????????consistentHashSelector?=?new?ConsistentHashSelector(newIdentityHashCode,?serverList);
????}
}

第三步編寫測試代碼

public?class?LoadBalanceTest?{

????public?static?void?main(String[]?args)?{
????????testConsistentHashBalance1();
????}

????public?static?void?testConsistentHashBalance1()?{
????????List?serverList?=?new?ArrayList();
????????MyServer?server1?=?new?MyServer("1");
????????MyServer?server2?=?new?MyServer("2");
????????MyServer?server3?=?new?MyServer("3");
????????MyServer?server4?=?new?MyServer("4");
????????MyServer?server5?=?new?MyServer("5");
????????MyServer?server6?=?new?MyServer("6");
????????serverList.add(server1);
????????serverList.add(server2);
????????serverList.add(server3);
????????serverList.add(server4);
????????serverList.add(server5);
????????serverList.add(server6);
????????AbstractConsistentHashLoadBalance?consistentHashBalance?=?new?ConsistentHashBalance1();
????????for?(int?i?=?0;?i?10;?i++)?{
????????????String?clientIP?=?"5";
????????????MyServer?server?=?consistentHashBalance.select(clientIP,?serverList);
????????????System.out.println("clientIP="?+?clientIP?+?",consistentHashBalance1?route?server="?+?server);
????????}
????}
}

第四步輸出結(jié)果

clientIP=5,consistentHashBalance1 route server=MyServer(ip=6)
clientIP=5,consistentHashBalance1 route server=MyServer(ip=6)
clientIP=5,consistentHashBalance1 route server=MyServer(ip=6)
clientIP=5,consistentHashBalance1 route server=MyServer(ip=6)
clientIP=5,consistentHashBalance1 route server=MyServer(ip=6)
clientIP=5,consistentHashBalance1 route server=MyServer(ip=6)
clientIP=5,consistentHashBalance1 route server=MyServer(ip=6)
clientIP=5,consistentHashBalance1 route server=MyServer(ip=6)
clientIP=5,consistentHashBalance1 route server=MyServer(ip=6)
clientIP=5,consistentHashBalance1 route server=MyServer(ip=6)

如果新增虛擬節(jié)點參看以下代碼

public?class?ConsistentHashBalance2?extends?AbstractConsistentHashLoadBalance?{
????private?ConsistentHashSelector?consistentHashSelector;

????@Override
????public?MyServer?doSelect(String?clientIP,?List?serverList)?{
????????initialSelector(serverList);
????????return?consistentHashSelector.select(clientIP);
????}

????private?class?ConsistentHashSelector?{
????????private?Integer?identityHashCode;
????????private?Integer?VIRTUAL_NODES_NUM?=?16;
????????private?TreeMap/*?hashcode?*/,?MyServer>?serverNodes?=?new?TreeMap();

????????public?ConsistentHashSelector(Integer?identityHashCode,?List?serverList)?{
????????????this.identityHashCode?=?identityHashCode;
????????????TreeMap?newServerNodes?=?new?TreeMap();
????????????for?(MyServer?server?:?serverList)?{
????????????????//?虛擬節(jié)點
????????????????for?(int?i?=?0;?i?????????????????????int?virtualKey?=?hashCode(server.getIp()?+?"_"?+?i);
????????????????????newServerNodes.put(virtualKey,?server);
????????????????}
????????????}
????????????serverNodes?=?newServerNodes;
????????}

????????public?MyServer?select(String?clientIP)?{
????????????int?clientHashCode?=?hashCode(clientIP);
????????????SortedMap?tailMap?=?serverNodes.tailMap(clientHashCode,?false);
????????????if?(CollectionUtils.isEmpty(tailMap))?{
????????????????Integer?firstKey?=?serverNodes.firstKey();
????????????????return?serverNodes.get(firstKey);
????????????}
????????????Integer?firstKey?=?tailMap.firstKey();
????????????return?tailMap.get(firstKey);
????????}

????????private?int?hashCode(String?key)?{
????????????return?Objects.hashCode(key);
????????}

????????public?Integer?getIdentityHashCode()?{
????????????return?identityHashCode;
????????}
????}

????private?void?initialSelector(List?serverList)?{
????????Integer?newIdentityHashCode?=?System.identityHashCode(serverList);
????????if?(null?!=?consistentHashSelector?&&?(null?!=?consistentHashSelector.getIdentityHashCode()?&&?newIdentityHashCode?==?consistentHashSelector.getIdentityHashCode()))?{
????????????return;
????????}
????????consistentHashSelector?=?new?ConsistentHashSelector(newIdentityHashCode,?serverList);
????}
}

7.3 DUBBO源碼

public?class?ConsistentHashLoadBalance?extends?AbstractLoadBalance?{
????public?static?final?String?NAME?=?"consistenthash";
????private?final?ConcurrentMap>?selectors?=?new?ConcurrentHashMap>();

????@Override
????protected??Invoker?doSelect(List>?invokers,?URL?url,?Invocation?invocation)?{
????????String?methodName?=?RpcUtils.getMethodName(invocation);
????????String?key?=?invokers.get(0).getUrl().getServiceKey()?+?"."?+?methodName;
????????int?identityHashCode?=?System.identityHashCode(invokers);
????????ConsistentHashSelector?selector?=?(ConsistentHashSelector)?selectors.get(key);

????????//?提供者列表哈希值發(fā)生變化則重新構(gòu)建哈希環(huán)
????????if?(selector?==?null?||?selector.identityHashCode?!=?identityHashCode)?{
????????????selectors.put(key,?new?ConsistentHashSelector(invokers,?methodName,?identityHashCode));
????????????selector?=?(ConsistentHashSelector)?selectors.get(key);
????????}
????????return?selector.select(invocation);
????}

????private?static?final?class?ConsistentHashSelector<T>?{

????????private?final?TreeMap>?virtualInvokers;

????????private?final?int?replicaNumber;

????????private?final?int?identityHashCode;

????????private?final?int[]?argumentIndex;

????????//?構(gòu)建哈希環(huán)
????????ConsistentHashSelector(List>?invokers,?String?methodName,?int?identityHashCode)?{
????????????this.virtualInvokers?=?new?TreeMap>();
????????????this.identityHashCode?=?identityHashCode;
????????????URL?url?=?invokers.get(0).getUrl();
????????????this.replicaNumber?=?url.getMethodParameter(methodName,?"hash.nodes",?160);
????????????String[]?index?=?Constants.COMMA_SPLIT_PATTERN.split(url.getMethodParameter(methodName,?"hash.arguments",?"0"));
????????????argumentIndex?=?new?int[index.length];
????????????for?(int?i?=?0;?i?????????????????argumentIndex[i]?=?Integer.parseInt(index[i]);
????????????}
????????????for?(Invoker?invoker?:?invokers)?{
????????????????String?address?=?invoker.getUrl().getAddress();
????????????????//?新增虛擬節(jié)點（默認(rèn)160個）
????????????????for?(int?i?=?0;?i?4;?i++)?{
????????????????????byte[]?digest?=?md5(address?+?i);
????????????????????for?(int?h?=?0;?h?4;?h++)?{
????????????????????????long?m?=?hash(digest,?h);
????????????????????????virtualInvokers.put(m,?invoker);
????????????????????}
????????????????}
????????????}
????????}

????????//?負(fù)載均衡
????????public?Invoker?select(Invocation?invocation)?{
????????????String?key?=?toKey(invocation.getArguments());
????????????byte[]?digest?=?md5(key);
????????????return?selectForKey(hash(digest,?0));
????????}

????????private?String?toKey(Object[]?args)?{
????????????StringBuilder?buf?=?new?StringBuilder();
????????????for?(int?i?:?argumentIndex)?{
????????????????if?(i?>=?0?&&?i?????????????????????buf.append(args[i]);
????????????????}
????????????}
????????????return?buf.toString();
????????}

????????private?Invoker?selectForKey(long?hash)?{
????????????Map.Entry>?entry?=?virtualInvokers.ceilingEntry(hash);
????????????if?(entry?==?null)?{
????????????????entry?=?virtualInvokers.firstEntry();
????????????}
????????????return?entry.getValue();
????????}

????????//?哈希運算
????????private?long?hash(byte[]?digest,?int?number)?{
????????????return?(((long)?(digest[3?+?number?*?4]?&?0xFF)?<24)
????????????????????|?((long)?(digest[2?+?number?*?4]?&?0xFF)?<16)
????????????????????|?((long)?(digest[1?+?number?*?4]?&?0xFF)?<8)
????????????????????|?(digest[number?*?4]?&?0xFF))
???????????????????&?0xFFFFFFFFL;
????????}

????????private?byte[]?md5(String?value)?{
????????????MessageDigest?md5;
????????????try?{
????????????????md5?=?MessageDigest.getInstance("MD5");
????????????}?catch?(NoSuchAlgorithmException?e)?{
????????????????throw?new?IllegalStateException(e.getMessage(),?e);
????????????}
????????????md5.reset();
????????????byte[]?bytes?=?value.getBytes(StandardCharsets.UTF_8);
????????????md5.update(bytes);
????????????return?md5.digest();
????????}
????}
}

8 最少活躍數(shù)

每個提供者維護并發(fā)處理的任務(wù)個數(shù)，任務(wù)個數(shù)越大活躍度越高。在服務(wù)消費者進(jìn)行負(fù)載均衡時，第一查詢提供者負(fù)載情況，第二選擇活躍度最低的提供者，我們直接分析DUBBO源碼：

public?class?LeastActiveLoadBalance?extends?AbstractLoadBalance?{
????public?static?final?String?NAME?=?"leastactive";

????@Override
????protected??Invoker?doSelect(List>?invokers,?URL?url,?Invocation?invocation)?{

????????//?invoker數(shù)量
????????int?length?=?invokers.size();

????????//?最小調(diào)用次數(shù)
????????int?leastActive?=?-1;

????????//?調(diào)用次數(shù)等于最小次數(shù)invoker數(shù)量
????????int?leastCount?=?0;

????????//?調(diào)用次數(shù)等于最小調(diào)用次數(shù)invoker下標(biāo)集合
????????int[]?leastIndexes?=?new?int[length];

????????//?每個服務(wù)提供者權(quán)重
????????int[]?weights?=?new?int[length];

????????//?總權(quán)重
????????int?totalWeight?=?0;

????????//?第一個調(diào)用者權(quán)重
????????int?firstWeight?=?0;

????????//?權(quán)重值是否相同
????????boolean?sameWeight?=?true;

????????//?遍歷invokers
????????for?(int?i?=?0;?i?????????????Invoker?invoker?=?invokers.get(i);

????????????//?調(diào)用次數(shù)
????????????int?active?=?RpcStatus.getStatus(invoker.getUrl(),?invocation.getMethodName()).getActive();

????????????//?獲取權(quán)重
????????????int?afterWarmup?=?getWeight(invoker,?invocation);

????????????//?設(shè)置權(quán)重
????????????weights[i]?=?afterWarmup;

????????????//?第一個invoker或者調(diào)用次數(shù)小于最小調(diào)用次數(shù)
????????????if?(leastActive?==?-1?||?active?????????????????leastActive?=?active;
????????????????leastCount?=?1;
????????????????leastIndexes[0]?=?i;
????????????????totalWeight?=?afterWarmup;
????????????????firstWeight?=?afterWarmup;
????????????????sameWeight?=?true;
????????????}
????????????//?當(dāng)前服務(wù)提供者調(diào)用次數(shù)等于最小調(diào)用次數(shù)
????????????else?if?(active?==?leastActive)?{
????????????????//?記錄下標(biāo)
????????????????leastIndexes[leastCount++]?=?i;
????????????????//?新增總權(quán)重值
????????????????totalWeight?+=?afterWarmup;
????????????????//?權(quán)重值是否相同
????????????????if?(sameWeight?&&?i?>?0?&&?afterWarmup?!=?firstWeight)?{
????????????????????sameWeight?=?false;
????????????????}
????????????}
????????}

????????//?只有一個invoker調(diào)用次數(shù)等于最小調(diào)用次數(shù)直接返回
????????if?(leastCount?==?1)?{
????????????return?invokers.get(leastIndexes[0]);
????????}

????????//?多個invoker調(diào)用次數(shù)等于最小調(diào)用次數(shù)并且權(quán)重值不相同->根據(jù)權(quán)重值選擇
????????if?(!sameWeight?&&?totalWeight?>?0)?{
????????????int?offsetWeight?=?ThreadLocalRandom.current().nextInt(totalWeight);
????????????for?(int?i?=?0;?i?????????????????int?leastIndex?=?leastIndexes[i];
????????????????offsetWeight?-=?weights[leastIndex];
????????????????if?(offsetWeight?0)?{
????????????????????return?invokers.get(leastIndex);
????????????????}
????????????}
????????}
????????//?多個invoker調(diào)用次數(shù)等于最小調(diào)用次數(shù)并且權(quán)重值相同->隨機選擇
????????return?invokers.get(leastIndexes[ThreadLocalRandom.current().nextInt(leastCount)]);
????}
}

9 文章總結(jié)

第一本文首先分析了負(fù)載均衡、集群容錯、服務(wù)降級這三組概念，第二結(jié)合代碼分析了簡單隨機，加權(quán)隨機，簡單輪詢，簡單加權(quán)輪詢，平滑加權(quán)輪詢，一致性哈希，最少活躍數(shù)七種負(fù)載均衡策略，其中權(quán)重計算、平滑加權(quán)輪詢，一致性哈希算法值得注意，希望本文對大家有所幫助。

JAVA前線?

長文圖解七種負(fù)載均衡策略

1 三組概念

2 簡單隨機

3 加權(quán)隨機

3.1 設(shè)計思路

3.2 代碼實例

3.3 DUBBO源碼

4 簡單輪詢

5 簡單加權(quán)輪詢

6 平滑加權(quán)輪詢

6.1 設(shè)計思路

6.2 代碼實例

6.3 DUBBO源碼

7 一致性哈希

7.1 特性分析

(1) 特性一

(2) 特性二

(3) 特性三

7.2 代碼實例

7.3 DUBBO源碼

8 最少活躍數(shù)

9 文章總結(jié)