RoundRobinLoadBalance是dubbo里面提供的按照權(quán)重進(jìn)行輪詢的負(fù)載均衡算法，整個(gè)算法設(shè)計(jì)的非常巧妙，如下
1 初始化本地權(quán)重表，根據(jù)情況動(dòng)態(tài)調(diào)整
2 每次動(dòng)態(tài)的更新本地權(quán)重表，更新算法為當(dāng)前invoker的權(quán)重+本地權(quán)重表的old值
3 選取本地權(quán)重最大的invoker，并將其本地權(quán)重表的權(quán)重 減去 本輪所有invoker的權(quán)重和，并返回當(dāng)前的invoker
重復(fù)3
tip 本地權(quán)重表中如果一分鐘內(nèi)某個(gè)權(quán)重信息沒(méi)有更新（即對(duì)應(yīng)的invoker沒(méi)有被調(diào)用，那么回收，重新的初始化）
，舉個(gè)例子，引用于
https://blog.csdn.net/lizz861109/article/details/109517749（侵權(quán)請(qǐng)聯(lián)系我刪除）
圖如下
image.png
源碼分析如下
public class RoundRobinLoadBalance extends AbstractLoadBalance {
//負(fù)載均衡器的名稱
public static final String NAME = "roundrobin";
//更新時(shí)間（就是某個(gè)invoker一直沒(méi)有被調(diào)用，將其刪除，并重新的初始化）
private static int RECYCLE_PERIOD = 60000;
//內(nèi)置的權(quán)重輪詢器，主要對(duì)當(dāng)前invoker的默認(rèn)權(quán)重weight（一般不會(huì)變，如果是啟動(dòng)
//十分鐘內(nèi)會(huì)變化）和當(dāng)前權(quán)重current（如果被選中，會(huì)減少total的權(quán)重，保證下次被 //選中的概率減?。? protected static class WeightedRoundRobin {
//配置權(quán)重
private int weight;
//當(dāng)前權(quán)重
private AtomicLong current = new AtomicLong(0);
//最后更新時(shí)間
private long lastUpdate;
public int getWeight() {
return weight;
}
public void setWeight(int weight) {
this.weight = weight;
current.set(0);
}
//每次輪詢的時(shí)候，都會(huì)將當(dāng)前權(quán)重 + 默認(rèn)權(quán)重再次設(shè)置為當(dāng)前權(quán)重
public long increaseCurrent() {
return current.addAndGet(weight);
}
//如果被選中，則當(dāng)前權(quán)重減去 total
public void sel(int total) {
current.addAndGet(-1 * total);
}
public long getLastUpdate() {
return lastUpdate;
}
public void setLastUpdate(long lastUpdate) {
this.lastUpdate = lastUpdate;
}
}
//緩存
private ConcurrentMap<String, ConcurrentMap<String, WeightedRoundRobin>> methodWeightMap = new ConcurrentHashMap<String, ConcurrentMap<String, WeightedRoundRobin>>();
//cas鎖
private AtomicBoolean updateLock = new AtomicBoolean();
/**
* get invoker addr list cached for specified invocation
* <p>
* <b>for unit test only</b>
*
* @param invokers
* @param invocation
* @return
*/
protected <T> Collection<String> getInvokerAddrList(List<Invoker<T>> invokers, Invocation invocation) {
String key = invokers.get(0).getUrl().getServiceKey() + "." + invocation.getMethodName();
Map<String, WeightedRoundRobin> map = methodWeightMap.get(key);
if (map != null) {
return map.keySet();
}
return null;
}
@Override
protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
//獲取key service + method
String key = invokers.get(0).getUrl().getServiceKey() + "." + invocation.getMethodName();
ConcurrentMap<String, WeightedRoundRobin> map = methodWeightMap.get(key);
//如果為空，那么初始化一個(gè)
if (map == null) {
methodWeightMap.putIfAbsent(key, new ConcurrentHashMap<String, WeightedRoundRobin>());
map = methodWeightMap.get(key);
}
int totalWeight = 0;
long maxCurrent = Long.MIN_VALUE;
long now = System.currentTimeMillis();
Invoker<T> selectedInvoker = null;
WeightedRoundRobin selectedWRR = null;
for (Invoker<T> invoker : invokers) {
String identifyString = invoker.getUrl().toIdentityString();
WeightedRoundRobin weightedRoundRobin = map.get(identifyString);
//獲取當(dāng)前invoker的權(quán)重
int weight = getWeight(invoker, invocation);
if (weight < 0) {
weight = 0;
}
//如果當(dāng)前invoker對(duì)應(yīng)的weightedRoundRobin為空，那么new一個(gè)，順便使用
//當(dāng)前invoker的信息來(lái)初始化這個(gè)weightedRoundRobin
if (weightedRoundRobin == null) {
weightedRoundRobin = new WeightedRoundRobin();
weightedRoundRobin.setWeight(weight);
map.putIfAbsent(identifyString, weightedRoundRobin);
weightedRoundRobin = map.get(identifyString);
}
//如果默認(rèn)的weight與實(shí)際的不一致，那么更新（有可能在warmup階段）
if (weight != weightedRoundRobin.getWeight()) {
//weight changed
weightedRoundRobin.setWeight(weight);
}
//將invoker的當(dāng)前權(quán)重 + 默認(rèn)權(quán)重
long cur = weightedRoundRobin.increaseCurrent();
//更新時(shí)間
weightedRoundRobin.setLastUpdate(now);
if (cur > maxCurrent) {
maxCurrent = cur;
selectedInvoker = invoker;
selectedWRR = weightedRoundRobin;
}
totalWeight += weight;
}
//如果invokers的個(gè)數(shù)與緩存的個(gè)數(shù)對(duì)不上，進(jìn)行更新
if (!updateLock.get() && invokers.size() != map.size()) {
if (updateLock.compareAndSet(false, true)) {
try {
// copy -> modify -> update reference
ConcurrentMap<String, WeightedRoundRobin> newMap = new ConcurrentHashMap<String, WeightedRoundRobin>();
newMap.putAll(map);
Iterator<Entry<String, WeightedRoundRobin>> it = newMap.entrySet().iterator();
while (it.hasNext()) {
//如果某個(gè)invoker一分鐘都沒(méi)有更新了（也就是根本沒(méi)有請(qǐng)求過(guò)來(lái)）
//將其回收，下次請(qǐng)求進(jìn)來(lái)會(huì)重建
Entry<String, WeightedRoundRobin> item = it.next();
if (now - item.getValue().getLastUpdate() > RECYCLE_PERIOD) {
it.remove();
}
}
methodWeightMap.put(key, newMap);
} finally {
updateLock.set(false);
}
}
}
//經(jīng)過(guò)上面的操作之后，當(dāng)前權(quán)重最大的invoker被選出來(lái)了
if (selectedInvoker != null) {
//更新當(dāng)前權(quán)重（也就是減去totalWeight ）
selectedWRR.sel(totalWeight);
return selectedInvoker;
}
// should not happen here
return invokers.get(0);
}
}
大家結(jié)合圖和代碼就能很好的理解這個(gè)加權(quán)輪詢算法了
