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DefaultControllerOverridepublicbooleancanPass(Nodenode,intacquireCount,booleanprioritized){intcurCount=avgUsedTokens(node);if(curCount+acquireCount>count){if(prioritized&&grade==RuleConstant.FLOW_GRADE_QPS){longcurrentTime;longwaitInMs;currentTime=TimeUtil.currentTimeMillis();waitInMs=node.tryOccupyNext(currentTime,acquireCount,count);if(waitInMs0,statDurationMsshouldbepositive);AssertUtil.assertTrue(maxCountPerStat>=0,maxCountPerStatshouldbe>=0);AssertUtil.assertTrue(queueingTimeoutMs>=0,queueingTimeoutMsshouldbe>=0);this.maxQueueingTimeMs=queueingTimeoutMs;this.count=maxCountPerStat;this.statDurationMs=statDurationMs;//UsenanoSecondswhendurationMs%count!=0orcount/durationMs>1(tobeaccurate)//可见装备限流值count大于1000时useNanoSeconds会是true不然是falseif(maxCountPerStat>0){this.useNanoSeconds=statDurationMs%Math.round(maxCountPerStat)!=0||maxCountPerStat/statDurationMs>1;}else{this.useNanoSeconds=false;}}OverridepublicbooleancanPass(Nodenode,intacquireCount){returncanPass(node,acquireCount,false);}privatebooleancheckPassUsingNanoSeconds(intacquireCount,doublemaxCountPerStat){finallongmaxQueueingTimeNs=maxQueueingTimeMs*MS_TO_NS_OFFSET;longcurrentTime=System.nanoTime();//Calculatetheintervalbetweeneverytworequests.finallongcostTimeNs=Math.round(1.0d*MS_TO_NS_OFFSET*statDurationMs*acquireCount/maxCountPerStat);//Expectedpasstimeofthisrequest.longexpectedTime=costTimeNs+latestPassedTime.get();if(expectedTimethreshold){transformToOpen(curCount);}}staticclassSimpleErrorCounter{privateLongAddererrorCount;privateLongAddertotalCount;publicSimpleErrorCounter(){this.errorCount=newLongAdder();this.totalCount=newLongAdder();}publicLongAddergetErrorCount(){returnerrorCount;}publicLongAddergetTotalCount(){returntotalCount;}publicSimpleErrorCounterreset(){errorCount.reset();totalCount.reset();returnthis;}OverridepublicStringtoString(){returnSimpleErrorCounter{+errorCount=+errorCount+,totalCount=+totalCount+};}}staticclassSimpleErrorCounterLeapArrayextendsLeapArray{publicSimpleErrorCounterLeapArray(intsampleCount,intintervalInMs){super(sampleCount,intervalInMs);}OverridepublicSimpleErrorCounternewEmptyBucket(longtimeMillis){returnnewSimpleErrorCounter();}OverrideprotectedWindowWrapresetWindowTo(WindowWrapw,longstartTime){//Updatethestarttimeandresetvalue.w.resetTo(startTime);w.value().reset();returnw;}}}2.6SystemSlot校验逻辑首要会集在com.alibaba.csp.sentinel.slots.system.SystemRuleManager#checkSystem，瑞幸以下是片段，瑞幸能够看到，作为负载维护规矩校验，完结了集群的QPS、线程、RT（呼应时刻）、体系负载的操控，除体系负载以外，其他核算都是依靠StatisticSlot完结，体系负载是经过SystemRuleManager守时调度SystemStatusListener，经过OperatingSystemMXBean去获取/***Apply{linkSystemRule}totheresource.Onlyinboundtrafficwillbechecked.**paramresourceWrappertheresource.*throwsBlockExceptionwhenanysystemrulesthresholdisexceeded.*/publicstaticvoidcheckSystem(ResourceWrapperresourceWrapper,intcount)throwsBlockException{if(resourceWrapper==null){return;}//Ensurethecheckingswitchison.if(!checkSystemStatus.get()){return;}//forinboundtrafficonlyif(resourceWrapper.getEntryType()!=EntryType.IN){return;}//totalqps此处是拿到某个资源在集群中的QPS总和，相关概念能够会看初始化关于Node的介绍doublecurrentQps=Constants.ENTRY_NODE.passQps();if(currentQps+count>qps){thrownewSystemBlockException(resourceWrapper.getName(),qps);}//totalthreadintcurrentThread=Constants.ENTRY_NODE.curThreadNum();if(currentThread>maxThread){thrownewSystemBlockException(resourceWrapper.getName(),thread);}doublert=Constants.ENTRY_NODE.avgRt();if(rt>maxRt){thrownewSystemBlockException(resourceWrapper.getName(),rt);}//load.BBRalgorithm.if(highestSystemLoadIsSet&&getCurrentSystemAvgLoad()>highestSystemLoad){if(!checkBbr(currentThread)){thrownewSystemBlockException(resourceWrapper.getName(),load);}}//cpuusageif(highestCpuUsageIsSet&&getCurrentCpuUsage()>highestCpuUsage){thrownewSystemBlockException(resourceWrapper.getName(),cpu);}}privatestaticbooleancheckBbr(intcurrentThread){if(currentThread>1&¤tThread>Constants.ENTRY_NODE.maxSuccessQps()*Constants.ENTRY_NODE.minRt()/1000){returnfalse;}returntrue;}publicstaticdoublegetCurrentSystemAvgLoad(){returnstatusListener.getSystemAverageLoad();}publicstaticdoublegetCurrentCpuUsage(){returnstatusListener.getCpuUsage();}publicclassSystemStatusListenerimplementsRunnable{volatiledoublecurrentLoad=-1;volatiledoublecurrentCpuUsage=-1;volatileStringreason=StringUtil.EMPTY;volatilelongprocessCpuTime=0;volatilelongprocessUpTime=0;publicdoublegetSystemAverageLoad(){returncurrentLoad;}publicdoublegetCpuUsage(){returncurrentCpuUsage;}Overridepublicvoidrun(){try{OperatingSystemMXBeanosBean=ManagementFactory.getPlatformMXBean(OperatingSystemMXBean.class);currentLoad=osBean.getSystemLoadAverage();/**JavaDoccopiedfrom{linkOperatingSystemMXBean#getSystemCpuLoad()}:*Returnstherecentcpuusageforthewholesystem.Thisvalueisadoubleinthe[0.0,1.0]interval.*Avalueof0.0meansthatallCPUswereidleduringtherecentperiodoftimeobserved,whileavalue*of1.0meansthatallCPUswereactivelyrunning100%ofthetimeduringtherecentperiodbeing*observed.Allvaluesbetween0.0and1.0arepossibledependingoftheactivitiesgoingoninthe*system.Ifthesystemrecentcpuusageisnotavailable,themethodreturnsanegativevalue.*/doublesystemCpuUsage=osBean.getSystemCpuLoad();//calculateprocesscpuusagetosupportapplicationrunningincontainerenvironmentRuntimeMXBeanruntimeBean=ManagementFactory.getPlatformMXBean(RuntimeMXBean.class);longnewProcessCpuTime=osBean.getProcessCpuTime();longnewProcessUpTime=runtimeBean.getUptime();intcpuCores=osBean.getAvailableProcessors();longprocessCpuTimeDiffInMs=TimeUnit.NANOSECONDS.toMillis(newProcessCpuTime-processCpuTime);longprocessUpTimeDiffInMs=newProcessUpTime-processUpTime;doubleprocessCpuUsage=(double)processCpuTimeDiffInMs/processUpTimeDiffInMs/cpuCores;processCpuTime=newProcessCpuTime;processUpTime=newProcessUpTime;currentCpuUsage=Math.max(processCpuUsage,systemCpuUsage);if(currentLoad>SystemRuleManager.getSystemLoadThreshold()){writeSystemStatusLog();}}catch(Throwablee){RecordLog.warn([SystemStatusListener]FailedtogetsystemmetricsfromJMX,e);}}privatevoidwriteSystemStatusLog(){StringBuildersb=newStringBuilder();sb.append(Loadexceedsthethreshold:);sb.append(load:).append(String.format(%.4f,currentLoad)).append(;);sb.append(cpuUsage:).append(String.format(%.4f,currentCpuUsage)).append(;);sb.append(qps:).append(String.format(%.4f,Constants.ENTRY_NODE.passQps())).append(;);sb.append(rt:).append(String.format(%.4f,Constants.ENTRY_NODE.avgRt())).append(;);sb.append(thread:).append(Constants.ENTRY_NODE.curThreadNum()).append(;);sb.append(success:).append(String.format(%.4f,Constants.ENTRY_NODE.successQps())).append(;);sb.append(minRt:).append(String.format(%.2f,Constants.ENTRY_NODE.minRt())).append(;);sb.append(maxSuccess:).append(String.format(%.2f,Constants.ENTRY_NODE.maxSuccessQps())).append(;);RecordLog.info(sb.toString());}}三、京东版最佳实践3.1运用办法Sentinel运用办法自身十分简略，便是一个注解，可是要考虑规矩加载和规矩耐久化的办法，现有的办法有：•运用Sentinel-dashboard功用：运用面板接入需求维护一个装备规矩的办理端，考虑到偏后端的体系需求额定维护一个面板本钱较大，假如是像RPC结构这种自身有办理端的接入能够考虑次计划。FlowSlot的首要逻辑都在FlowRuleChecker里，咖啡狂营介绍之前，咖啡狂营咱们先看一下Sentinel关于规矩的模型描绘，下图分别是限流、拜访操控规矩、体系维护规矩（Linux负载）、降级规矩/***流量操控两种形式*0:threadcount（当调用该api的线程数抵达阈值的时分，进行限流）*1:QPS（当调用该api的QPS抵达阈值的时分，进行限流）*/privateintgrade=RuleConstant.FLOW_GRADE_QPS;/***流量操控阈值，值意义与grade有关*/privatedoublecount;/***调用联系限流战略（能够支撑相关资源或指定链路的多样性限流需求）*直接（api抵达限流条件时，直接限流）*相关（当相关的资源抵达限流阈值时，就限流自己）*链路（只记载指定链路上的流量）*{linkRuleConstant#STRATEGY_DIRECT}fordirectflowcontrol(byorigin);*{linkRuleConstant#STRATEGY_RELATE}forrelevantflowcontrol(withrelevantresource);*{linkRuleConstant#STRATEGY_CHAIN}forchainflowcontrol(byentranceresource).*/privateintstrategy=RuleConstant.STRATEGY_DIRECT;/***Referenceresourceinflowcontrolwithrelevantresourceorcontext.*/privateStringrefResource;/***流控作用：*0.default(rejectdirectly),直接回绝，抛反常FlowException*1.warmup,慢发动形式（依据coldFactor（冷加载因子，默许3）的值，从阈值/coldFactor，经过预热时长，才抵达设置的QPS阈值）*2.ratelimiter排队等候*3.warmup+ratelimiter*/privateintcontrolBehavior=RuleConstant.CONTROL_BEHAVIOR_DEFAULT;privateintwarmUpPeriodSec=10;/***Maxqueueingtimeinratelimiterbehavior.*/privateintmaxQueueingTimeMs=500;/***是否集群限流，默许为否*/privatebooleanclusterMode;/***Flowruleconfigforclustermode.*/privateClusterFlowConfigclusterConfig;/***Thetrafficshaping(throttling)controller.*/privateTrafficShapingControllercontroller;接着咱们持续剖析FlowRuleCheckercanPassCheck第一步会美观limitApp，这个是结合拜访授权约束规矩运用的，默许是一切。

关于数据核算，首席首要会牵扯到ArrayMetric、BucketLeapArray、MetricBucket、WindowWrap等类。接下来咱们就要看看Metric//StatisticNode持有两个Metric，营销一个秒级一个分钟级，营销由入参可知，秒级核算划分了两个时刻窗口，窗口程度是500msprivatetransientvolatileMetricrollingCounterInSecond=newArrayMetric(SampleCountProperty.SAMPLE_COUNT,IntervalProperty.INTERVAL);//分钟级核算划分了60个时刻窗口，窗口长度是1000msprivatetransientMetricrollingCounterInMinute=newArrayMetric(60,60*1000,false);/***Thecounterforthreadcount.*/privateLongAddercurThreadNum=newLongAdder();/***Thelasttimestampwhenmetricswerefetched.*/privatelonglastFetchTime=-1;ArrayMetric只要一个特点LeapArray，其他都是用于核算的办法，LeapArray是sentinel中核算最根本的数据结构，这里有必要具体看一下，整体便是依据timeMillis去获取一个bucket，分为：没有创立、有直接回来、被抛弃后的reset三种场景。在细看Node完结时，官杨不难发现LongAddr的运用，官杨关于LongAddr和DoubleAddr都是java8java.util.concurrent.atomic里的内容，感兴趣的小伙伴能够再深化研究一下，这两个是高并发下计数功用十分优异的数据结构，实践运用场景里需求计数时能够考虑运用。

2.4.2单机限流形式接下来咱们看一下Sentinel中的限流完结，飞操比较上述根本限流算法，飞操Sentinel限流的第一个特性便是引进资源的概念，能够细粒度多样性的支撑特定资源、相关资源、指定链路的限流。Sentinel具有以下特征:•丰厚的运用场景：盘疯Sentinel承接了阿里巴巴近10年的双十一大促流量的中心场景，盘疯例如秒杀（即突发流量操控在体系容量能够接受的规模）、音讯削峰填谷、集群流量操控、实时熔断下流不可用运用等。

2.4FlowSlot2.4.1常见限流算法介绍sentinel限流完结前，揭蛊先介绍一下常见限流算法，根本分为三种：计数器、漏斗、令牌桶。

•ClusterBuilderSlot则用于存储资源的核算信息以及调用者信息，瑞幸例如该资源的RT,QPS,threadcount等等，这些信息将用作为多维度限流，降级的依据。LLM在生成进程中在这些人物之间无缝切换，咖啡狂营使用其自回归才能依据上下文猜测下一个token。

这种无环的特性保证推理进程不受循环依靠的影响，首席能更实在反映合理的逻辑推导。团队更是为这种推理进程供给了数学根底，营销通过拓扑斯理论(ToposTheory)正式化(formalize)DoT，保证其逻辑一致性和合理性。

官杨2012年结业于北京大学核算机系;2018年获美国康奈尔大学核算机博士学位;2018-2019年前往麻省理工学院大数据科学学院做博士后。张伊凡张伊凡2021年本科结业于于北京大学元培学院，飞操现为清华大学穿插信息学院博士研讨生，师从袁洋助理教授。