guohao commented on code in PR #10642: URL: https://github.com/apache/dubbo/pull/10642#discussion_r977516862
########## dubbo-cluster/src/main/java/org/apache/dubbo/rpc/cluster/loadbalance/AdaptivePowerOfTwoChoice.java: ########## @@ -0,0 +1,166 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.dubbo.rpc.cluster.loadbalance; + +import org.apache.dubbo.common.URL; +import org.apache.dubbo.common.threadpool.manager.FrameworkExecutorRepository; +import org.apache.dubbo.rpc.Invocation; +import org.apache.dubbo.rpc.Invoker; +import org.apache.dubbo.rpc.RpcStatus; +import org.apache.dubbo.rpc.cluster.Constants; +import org.apache.dubbo.rpc.model.ApplicationModel; +import org.apache.dubbo.rpc.model.ScopeModelAware; + +import java.util.List; +import java.util.concurrent.ConcurrentHashMap; +import java.util.concurrent.ExecutorService; +import java.util.concurrent.ThreadLocalRandom; +import java.util.concurrent.atomic.AtomicBoolean; + +public class AdaptivePowerOfTwoChoice extends AbstractLoadBalance implements ScopeModelAware { + public static final String NAME = "adaptiveP2C"; + + private int slidePeriod = 30_000; + + private ExecutorService executorService; + + private volatile long lastUpdateTime = System.currentTimeMillis(); + + private AtomicBoolean onResetSlideWindow = new AtomicBoolean(false); + + private ConcurrentHashMap<RpcStatus,SlideWindowData> methodMap = new ConcurrentHashMap<>(); + + @Override + public void setApplicationModel(ApplicationModel applicationModel) { + slidePeriod = applicationModel.getModelEnvironment().getConfiguration().getInt(Constants.ADAPTIVE_POWER_OF_TWO_CHOICE_SLIDE_PERIOD,30_000); + executorService = applicationModel.getFrameworkModel().getBeanFactory().getBean(FrameworkExecutorRepository.class).getSharedExecutor(); + } + + protected static class SlideWindowData{ + + private RpcStatus rpcStatus; + + private long totalOffset; + + private long succeedOffset; + + private long totalElapsedOffset; + + private long succeedElapsedOffset; + + public SlideWindowData(RpcStatus rpcStatus){ + this.rpcStatus = rpcStatus; + this.totalOffset = 0; + this.totalElapsedOffset = 0; + this.succeedElapsedOffset = 0; + this.succeedOffset = 0; + } + + public void reset(){ + this.totalOffset = rpcStatus.getTotal(); + this.succeedOffset = rpcStatus.getSucceeded(); + this.totalElapsedOffset = rpcStatus.getTotalElapsed(); + this.succeedElapsedOffset = rpcStatus.getSucceededElapsed(); + } + + public double getLatency(){ + if((this.rpcStatus.getSucceeded() - this.succeedOffset) == 0){ + return 0; + } + return (double) (this.rpcStatus.getSucceededElapsed() - this.succeedElapsedOffset)/(this.rpcStatus.getSucceeded() - this.succeedOffset); + } + + public long getAccept(){ + return (this.rpcStatus.getSucceeded() - this.succeedOffset); + } + + private long getRequest(){ + return (this.rpcStatus.getTotal() - this.totalOffset); + } + + } + + private double getNormlize(double x){ + return x/(1 + x); + } + + public <T> double getWeight(Invoker<T> invoker,Invocation invocation,double averageLatency){ + RpcStatus rpcStatus = RpcStatus.getStatus(invoker.getUrl(),invocation.getMethodName()); + SlideWindowData slideWindowData = methodMap.get(rpcStatus); + double latency = (1 + averageLatency)/(1 + slideWindowData.getLatency()); + + return (1 + slideWindowData.getAccept())/(1 + slideWindowData.getRequest()) * getNormlize(latency); + } + + private <T> Invoker<T> leastWeight(Invoker<T> invoker1,Invoker<T> invoker2,Invocation invocation,double averageLatency){ + double weight1 = getWeight(invoker1,invocation,averageLatency); + double weight2 = getWeight(invoker2,invocation,averageLatency); + if(weight1 >= weight2) + return invoker1; + return invoker2; + } + + public <T> double getAverageLatency(List<Invoker<T>> invokers,Invocation invocation){ + double averageLatency = 0; + double totalLatency = 0; + int length = invokers.size(); + for(int i = 0; i < length; i++){ + RpcStatus rpcStatus = RpcStatus.getStatus(invokers.get(i).getUrl(),invocation.getMethodName()); + SlideWindowData slideWindowData = methodMap.computeIfAbsent(rpcStatus,SlideWindowData::new); + totalLatency += slideWindowData.getLatency(); + } + averageLatency = totalLatency/length; + return averageLatency; + } + + @Override + protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) { + int length = invokers.size(); + if(length == 1) + return invokers.get(0); + + double averageLatency = 0; + double totalLatency = 0; + for(int i = 0; i < length; i++){ + RpcStatus rpcStatus = RpcStatus.getStatus(invokers.get(i).getUrl(),invocation.getMethodName()); + SlideWindowData slideWindowData = methodMap.computeIfAbsent(rpcStatus,SlideWindowData::new); + totalLatency += slideWindowData.getLatency(); + } + averageLatency = totalLatency/length; + + if(length == 2) + return leastWeight(invokers.get(0),invokers.get(1),invocation,averageLatency); + + int pos1 = ThreadLocalRandom.current().nextInt(length); + int pos2 = ThreadLocalRandom.current().nextInt(length); 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