I.负载均衡策略:
II.随机 Random loadBalance实现
protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
int length = invokers.size(); // 总个数
int totalWeight = 0; // 总权重
boolean sameWeight = true; // 权重是否都一样
for (int i = 0; i < length; i++) {
int weight = getWeight(invokers.get(i), invocation);
totalWeight += weight; // 累计总权重
if (sameWeight && i > 0
&& weight != getWeight(invokers.get(i - 1), invocation)) {
sameWeight = false; // 计算所有权重是否一样
}
}
if (totalWeight > 0 && ! sameWeight) {
// 如果权重不相同且权重大于0则按总权重数随机
int offset = random.nextInt(totalWeight);
// 并确定随机值落在哪个片断上
for (int i = 0; i < length; i++) {
offset -= getWeight(invokers.get(i), invocation);
if (offset < 0) {
return invokers.get(i);
}
}
}
// 如果权重相同或权重为0则均等随机
return invokers.get(random.nextInt(length));
}
II.轮训RoundRobin LoadBalance
//可能会卡在某台反应慢的机器
protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
String key = invokers.get(0).getUrl().getServiceKey() + "." + invocation.getMethodName();
int length = invokers.size(); // 总个数
int maxWeight = 0; // 最大权重
int minWeight = Integer.MAX_VALUE; // 最小权重
for (int i = 0; i < length; i++) {
int weight = getWeight(invokers.get(i), invocation);
maxWeight = Math.max(maxWeight, weight); // 累计最大权重
minWeight = Math.min(minWeight, weight); // 累计最小权重
}
if (maxWeight > 0 && minWeight < maxWeight) { // 权重不一样
AtomicPositiveInteger weightSequence = weightSequences.get(key);
if (weightSequence == null) {
weightSequences.putIfAbsent(key, new AtomicPositiveInteger());
weightSequence = weightSequences.get(key);
}
int currentWeight = weightSequence.getAndIncrement() % maxWeight;
List<Invoker<T>> weightInvokers = new ArrayList<Invoker<T>>();
for (Invoker<T> invoker : invokers) { // 筛选权重大于当前权重基数的Invoker
if (getWeight(invoker, invocation) > currentWeight) {
weightInvokers.add(invoker);
}
}
int weightLength = weightInvokers.size();
if (weightLength == 1) {
return weightInvokers.get(0);
} else if (weightLength > 1) {
invokers = weightInvokers;
length = invokers.size();
}
}
AtomicPositiveInteger sequence = sequences.get(key);
if (sequence == null) {
sequences.putIfAbsent(key, new AtomicPositiveInteger());
sequence = sequences.get(key);
}
// 取模轮循
return invokers.get(sequence.getAndIncrement() % length);
}
II.最小活跃LeastActiveLoadBanlance
protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
int length = invokers.size(); // 总个数
int leastActive = -1; // 最小的活跃数
int leastCount = 0; // 相同最小活跃数的个数
int[] leastIndexs = new int[length]; // 相同最小活跃数的下标
int totalWeight = 0; // 总权重
int firstWeight = 0; // 第一个权重,用于于计算是否相同
boolean sameWeight = true; // 是否所有权重相同
for (int i = 0; i < length; i++) {
Invoker<T> invoker = invokers.get(i);
int active = RpcStatus.getStatus(invoker.getUrl(), invocation.getMethodName()).getActive(); // 活跃数
int weight = invoker.getUrl().getMethodParameter(invocation.getMethodName(), Constants.WEIGHT_KEY, Constants.DEFAULT_WEIGHT); // 权重
if (leastActive == -1 || active < leastActive) { // 发现更小的活跃数,重新开始
leastActive = active; // 记录最小活跃数
leastCount = 1; // 重新统计相同最小活跃数的个数
leastIndexs[0] = i; // 重新记录最小活跃数下标
totalWeight = weight; // 重新累计总权重
firstWeight = weight; // 记录第一个权重
sameWeight = true; // 还原权重相同标识
} else if (active == leastActive) { // 累计相同最小的活跃数
leastIndexs[leastCount ++] = i; // 累计相同最小活跃数下标
totalWeight += weight; // 累计总权重
// 判断所有权重是否一样
if (sameWeight && i > 0
&& weight != firstWeight) {
sameWeight = false;
}
}
}
// assert(leastCount > 0)
if (leastCount == 1) {
// 如果只有一个最小则直接返回
return invokers.get(leastIndexs[0]);
}
if (! sameWeight && totalWeight > 0) {
// 如果权重不相同且权重大于0则按总权重数随机
int offsetWeight = random.nextInt(totalWeight);
// 并确定随机值落在哪个片断上
for (int i = 0; i < leastCount; i++) {
int leastIndex = leastIndexs[i];
offsetWeight -= getWeight(invokers.get(leastIndex), invocation);
if (offsetWeight <= 0)
return invokers.get(leastIndex);
}
}
// 如果权重相同或权重为0则均等随机
return invokers.get(leastIndexs[random.nextInt(leastCount)]);
}
II.一致性hash consistenHash
protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
String key = invokers.get(0).getUrl().getServiceKey() + "." + invocation.getMethodName();
//根据现有集合生产hash值
int identityHashCode = System.identityHashCode(invokers);
ConsistentHashSelector<T> selector = (ConsistentHashSelector<T>) selectors.get(key);
if (selector == null || selector.getIdentityHashCode() != identityHashCode) {
//根据集合和接口名字和hash值新建集合
selectors.put(key, new ConsistentHashSelector<T>(invokers, invocation.getMethodName(), identityHashCode));
selector = (ConsistentHashSelector<T>) selectors.get(key);
}
//根据访问的接口进行MD5
return selector.select(invocation);
}