-----------------看过之前一致性哈希和最少活跃书的可以跳过-----------------
链接在此:Dubbo的几个负载均衡类--一致性哈希
Dubbo的几个负载均衡类--最少活跃数
消费者发起调用过程中涉及如下几步
1:接口调用,比如DemoService.demoMethod
2:InvokerInvocationHandler.invoker:消费端启动时,通过JavassistProxyFactory.getProxy反射获取代理类,之后服务调用就直接调用这个Handler
3:MigrationInvoker.invoke:Dubbo 发起调用非常重要的一步,如果失败了,通过这个invoker做切换
4:其他
5:FailoverClusterInvoker.invoke(目前我们使用的,实际在AbstractClusterInvoker里面invoke逻辑是固定的)
6:其他
@Override
public Result invoke(final Invocation invocation) throws RpcException {
checkWhetherDestroyed();
// binding attachments into invocation.
Map contextAttachments = RpcContext.getContext().getObjectAttachments();
if (contextAttachments != null && contextAttachments.size() != 0) {
((RpcInvocation) invocation).addObjectAttachments(contextAttachments);
}
//如果设置了标签规则,则通过list方法过滤出来符合标签的几个invoker
List> invokers = list(invocation);
LoadBalance loadbalance = initLoadBalance(invokers, invocation);
RpcUtils.attachInvocationIdIfAsync(getUrl(), invocation);
//请求负载并且做好灾备降级
return doInvoke(invocation, invokers, loadbalance);
}
public Result doInvoke(Invocation invocation, final List> invokers, LoadBalance loadbalance) throws RpcException {
List> copyInvokers = invokers;
checkInvokers(copyInvokers, invocation);
String methodName = RpcUtils.getMethodName(invocation);
int len = calculateInvokeTimes(methodName);
// retry loop.
RpcException le = null; // last exception.
List> invoked = new ArrayList>(copyInvokers.size()); // invoked invokers.
Set providers = new HashSet(len);
for (int i = 0; i < len; i++) {
//Reselect before retry to avoid a change of candidate `invokers`.
//NOTE: if `invokers` changed, then `invoked` also lose accuracy.
if (i > 0) {
checkWhetherDestroyed();
copyInvokers = list(invocation);
// check again
checkInvokers(copyInvokers, invocation);
}
//这里通过loadBalance做负载
Invoker invoker = select(loadbalance, invocation, copyInvokers, invoked);
invoked.add(invoker);
RpcContext.getContext().setInvokers((List) invoked);
try {
Result result = invoker.invoke(invocation);
if (le != null && logger.isWarnEnabled()) {
logger.warn("Although retry the method " + methodName
+ " in the service " + getInterface().getName()
+ " was successful by the provider " + invoker.getUrl().getAddress()
+ ", but there have been failed providers " + providers
+ " (" + providers.size() + "/" + copyInvokers.size()
+ ") from the registry " + directory.getUrl().getAddress()
+ " on the consumer " + NetUtils.getLocalHost()
+ " using the dubbo version " + Version.getVersion() + ". Last error is: "
+ le.getMessage(), le);
}
return result;
} catch (RpcException e) {
if (e.isBiz()) { // biz exception.
throw e;
}
le = e;
} catch (Throwable e) {
le = new RpcException(e.getMessage(), e);
} finally {
providers.add(invoker.getUrl().getAddress());
}
}
throw new RpcException(le.getCode(), "Failed to invoke the method "
+ methodName + " in the service " + getInterface().getName()
+ ". Tried " + len + " times of the providers " + providers
+ " (" + providers.size() + "/" + copyInvokers.size()
+ ") from the registry " + directory.getUrl().getAddress()
+ " on the consumer " + NetUtils.getLocalHost() + " using the dubbo version "
+ Version.getVersion() + ". Last error is: "
+ le.getMessage(), le.getCause() != null ? le.getCause() : le);
}
-----------------看过之前一致性哈希的可以跳过-----------------
随机其实并不是我们想象的那么随机
@Override
protected Invoker doSelect(List> invokers, URL url, Invocation invocation) {
// Number of invokers
int length = invokers.size();
// Every invoker has the same weight?
boolean sameWeight = true;
// the maxWeight of every invokers, the minWeight = 0 or the maxWeight of the last invoker
int[] weights = new int[length];
// The sum of weights
int totalWeight = 0;
for (int i = 0; i < length; i++) {
int weight = getWeight(invokers.get(i), invocation);
// Sum
totalWeight += weight;
// save for later use
weights[i] = totalWeight;
if (sameWeight && totalWeight != weight * (i + 1)) {
sameWeight = false;
}
}
if (totalWeight > 0 && !sameWeight) {
// If (not every invoker has the same weight & at least one invoker's weight>0), select randomly based on totalWeight.
int offset = ThreadLocalRandom.current().nextInt(totalWeight);
// Return a invoker based on the random value.
for (int i = 0; i < length; i++) {
if (offset < weights[i]) {
return invokers.get(i);
}
}
}
// If all invokers have the same weight value or totalWeight=0, return evenly.
return invokers.get(ThreadLocalRandom.current().nextInt(length));
}
整体代码不多,还是要先获取权重值,这个我们在上一章的最少活跃数里面讲过
方法getWeight是处理那些启动在10分钟内的服务,做一定的服务负载降级。超过十分钟,那么返回的负载都是100,如果小于1分钟那么就是1,1分钟到10分钟之间分别的是分钟数的平方值。
基本针对的就是我们在版本发布的时候,需要启动某个服务的所有实例,这时候越早启动的权重值越大,这么做的原因其实也很合理,越早启动的越稳定,包括各种缓存热点的加载,连接数/链接池的初始化等等
什么时候totalWeight==weight*(i+1)呢?
就是所有的服务方服务都在1分钟内重启
然后和最少活跃数中的逻辑一样,如果权重值一样,那么就随机一个;如果不一样,就在总权重和中随机一个值,直到减完小于0
总结:随机并不是我们认为的随机,而是取决于线上服务的启动时间,如果短时间内所有的服务同时启动或者服务启动很长一段时间了,那么就是随机,如果短时间内,服务间断启动,那么还是会有一定的权重的