# client-go 中的 informer 源码分析 本文将以图文并茂的方式对 client-go 中的 informer 的源码分析，其整体流程图如下所示。 ![client-go informer](../images/client-go-informer.png) ## 前言 Kubernetes作为新一代的基础设施系统，其重要性已经不言而喻了。基于控制器模型实现的声明式API支持着集群中各类型的工作负载稳定高效的按照期望状态运转，随着越来越多的用户选择kubernetes，无论是为了深入了解kubernetes这一云原生操作系统的工作逻辑，还是期待能够根据自己的特定业务需求对kubernetes进行二次开发，了解控制器模型的实现机制都是非常重要的。kubernetes提供了client-go以方便使用go语言进行二次快发，本文试图讲述client-go各模块如informer、reflector、cache等实现细节。 当我们需要利用client-go来实现自定义控制器时，通常会使用informerFactory来管理控制器需要的多个资源对象的informer实例 ```go // 创建一个informer factory kubeInformerFactory := kubeinformers.NewSharedInformerFactory(kubeClient, time.Second*30) // factory已经为所有k8s的内置资源对象提供了创建对应informer实例的方法，调用具体informer实例的Lister或Informer方法 // 就完成了将informer注册到factory的过程 deploymentLister := kubeInformerFactory.Apps().V1().Deployments().Lister() // 启动注册到factory的所有informer kubeInformerFactory.Start(stopCh) ``` ### SharedInformerFactory结构 使用sharedInformerFactory可以统一管理控制器中需要的各资源对象的informer实例，避免同一个资源创建多个实例，这里的informer实现是shareIndexInformer NewSharedInformerFactory调用了NewSharedInformerFactoryWithOptions，将返回一个sharedInformerFactory对象 > client: clientset，支持直接请求api中各内置资源对象的restful group客户端集合 > namespace: factory关注的namespace（默认All Namespace），informer中的reflector将只会listAndWatch指定namespace的资源 > defaultResync: 用于初始化持有的shareIndexInformer的resyncCheckPeriod和defaultEventHandlerResyncPeriod字段，用于定时的将local store同步到deltaFIFO > customResync：支持针对每一个informer来配置resync时间，通过WithCustomResyncConfig这个Option配置，否则就用指定的defaultResync > informers：factory管理的informer集合 > startedInformers：记录已经启动的informer集合 ```go type sharedInformerFactory struct { client kubernetes.Interface //clientset namespace string //关注的namepace，可以通过WithNamespace Option配置 tweakListOptions internalinterfaces.TweakListOptionsFunc lock sync.Mutex defaultResync time.Duration //前面传过来的时间，如30s customResync map[reflect.Type]time.Duration //自定义resync时间 informers map[reflect.Type]cache.SharedIndexInformer //针对每种类型资源存储一个informer，informer的类型是ShareIndexInformer startedInformers map[reflect.Type]bool //每个informer是否都启动了 } ``` sharedInformerFactory对象的关键方法： #### 创建一个sharedInformerFactory ```go func NewSharedInformerFactoryWithOptions(client kubernetes.Interface, defaultResync time.Duration, options ...SharedInformerOption) SharedInformerFactory { factory := &sharedInformerFactory{ client: client, //clientset，对原生资源来说，这里可以直接使用kube clientset namespace: v1.NamespaceAll, //可以看到默认是监听所有ns下的指定资源 defaultResync: defaultResync, //30s //以下初始化map结构 informers: make(map[reflect.Type]cache.SharedIndexInformer), startedInformers: make(map[reflect.Type]bool), customResync: make(map[reflect.Type]time.Duration), } return factory } ``` #### 启动factory下的所有informer ```go func (f *sharedInformerFactory) Start(stopCh <-chan struct{}) { f.lock.Lock() defer f.lock.Unlock() for informerType, informer := range f.informers { if !f.startedInformers[informerType] { //直接起gorouting调用informer的Run方法，并且标记对应的informer已经启动 go informer.Run(stopCh) f.startedInformers[informerType] = true } } } ``` #### 等待informer的cache被同步 等待每一个ShareIndexInformer的cache被同步，具体怎么算同步完成？ - sharedInformerFactory的WaitForCacheSync将会不断调用factory持有的所有informer的HasSynced方法，直到返回true - 而informer的HasSynced方法调用的自己持有的controller的HasSynced方法（informer结构持有controller对象，下文会分析informer的结构） - informer中的controller的HasSynced方法则调用的是controller持有的deltaFIFO对象的HasSynced方法 也就说sharedInformerFactory的WaitForCacheSync方法判断informer的cache是否同步，最终看的是informer中的deltaFIFO是否同步了，deltaFIFO的结构下文将会分析 ```go func (f *sharedInformerFactory) WaitForCacheSync(stopCh <-chan struct{}) map[reflect.Type]bool { //获取每一个已经启动的informer informers := func() map[reflect.Type]cache.SharedIndexInformer { f.lock.Lock() defer f.lock.Unlock() informers := map[reflect.Type]cache.SharedIndexInformer{} for informerType, informer := range f.informers { if f.startedInformers[informerType] { informers[informerType] = informer } } return informers }() res := map[reflect.Type]bool{} // 等待他们的cache被同步，调用的是informer的HasSynced方法 for informType, informer := range informers { res[informType] = cache.WaitForCacheSync(stopCh, informer.HasSynced) } return res } ``` #### factory为自己添加informer 只有向factory中添加informer，factory才有意义，添加完成之后，上面factory的start方法就可以启动了 > obj: informer关注的资源如deployment{} > newFunc: 一个知道如何创建指定informer的方法，k8s为每一个内置的对象都实现了这个方法，比如创建deployment的ShareIndexInformer的方法 ```go // 向factory中注册指定的informer func (f *sharedInformerFactory) InformerFor(obj runtime.Object, newFunc internalinterfaces.NewInformerFunc) cache.SharedIndexInformer { f.lock.Lock() defer f.lock.Unlock() //根据对象类型判断factory中是否已经有对应informer informerType := reflect.TypeOf(obj) informer, exists := f.informers[informerType] if exists { return informer } //如果factory中已经有这个对象类型的informer，就不创建了 resyncPeriod, exists := f.customResync[informerType] if !exists { resyncPeriod = f.defaultResync } //没有就根据newFunc创建一个，并存在map中 informer = newFunc(f.client, resyncPeriod) f.informers[informerType] = informer return informer } ``` ##### shareIndexInformer对应的newFunc的实现 client-go中已经为所有内置对象都提供了NewInformerFunc 以deployment为例，通过调用factory.Apps().V1().Deployments()即可为factory添加一个deployment对应的shareIndexInformer的实现，具体过程如下： - 调用factory.Apps().V1().Deployments()即会调用以下Deployments方法创建deploymentInformer对象 ```go func (v *version) Deployments() DeploymentInformer { return &deploymentInformer{factory: v.factory, namespace: v.namespace, tweakListOptions: v.tweakListOptions} } ``` - 只要调用了factory.Apps().V1().Deployments()返回的deploymentInformer的Informer或Lister方法，就完成了向factory中添加deployment informer ```go // deploymentInformer对象具有defaultInformer、Informer、Lister方法 // 可以看到创建deploymentInformer时传递了一个带索引的缓存，附带了一个namespace索引，后面可以了解带索引的缓存实现，比如可以支持查询：某个namespace下的所有pod // 用于创建对应的shareIndexInformer，该方法提供给factory的InformerFor方法 func (f *deploymentInformer) defaultInformer(client kubernetes.Interface, resyncPeriod time.Duration) cache.SharedIndexInformer { return NewFilteredDeploymentInformer(client, f.namespace, resyncPeriod, cache.Indexers{cache.NamespaceIndex: cache.MetaNamespaceIndexFunc}, f.tweakListOptions) } // 向factor中添加dpeloyment的shareIndexInformer并返回 func (f *deploymentInformer) Informer() cache.SharedIndexInformer { return f.factory.InformerFor(&appsv1.Deployment{}, f.defaultInformer) } // 返回dpeloyment的lister对象，该lister中持有上面创建出的shareIndexInformer的cache的引用，方便通过缓存获取对象 func (f *deploymentInformer) Lister() v1.DeploymentLister { return v1.NewDeploymentLister(f.Informer().GetIndexer()) } ``` - deploymentInformer的defaultInformer方法将会创建出一个shareIndexInformer ```go // 可先看看下面的shareIndexInformer结构 func NewFilteredDeploymentInformer(client kubernetes.Interface, namespace string, resyncPeriod time.Duration, indexers cache.Indexers, tweakListOptions internalinterfaces.TweakListOptionsFunc) cache.SharedIndexInformer { return cache.NewSharedIndexInformer( // 定义对象的ListWatch方法，这里直接用的是clientset中的方法 &cache.ListWatch{ ListFunc: func(options v1.ListOptions) (runtime.Object, error) { if tweakListOptions != nil { tweakListOptions(&options) } return client.AppsV1beta1().Deployments(namespace).List(options) }, WatchFunc: func(options v1.ListOptions) (watch.Interface, error) { if tweakListOptions != nil { tweakListOptions(&options) } return client.AppsV1beta1().Deployments(namespace).Watch(options) }, }, &appsv1beta1.Deployment{}, resyncPeriod, //创建factory是指定的时间，如30s indexers, ) } ``` ### shareIndexInformer结构 > indexer：底层缓存，其实就是一个map记录对象，再通过一些其他map在插入删除对象是根据索引函数维护索引key如ns与对象pod的关系 > controller：informer内部的一个controller，这个controller包含reflector：根据用户定义的ListWatch方法获取对象并更新增量队列DeltaFIFO > processor：知道如何处理DeltaFIFO队列中的对象，实现是sharedProcessor{} > listerWatcher：知道如何list对象和watch对象的方法 > objectType：deployment{} > resyncCheckPeriod: 给自己的controller的reflector每隔多少s<尝试>调用listener的shouldResync方法 > defaultEventHandlerResyncPeriod：通过AddEventHandler方法给informer配置回调时如果没有配置的默认值，这个值用在processor的listener中判断是否需要进行resync，最小1s 两个字段的默认值都是来自创建factory时指定的defaultResync，当resyncPeriod < s.resyncCheckPeriod时，如果informer已经启动了才添加的EventHandler，那么调整resyncPeriod为resyncCheckPeriod，否则调整resyncCheckPeriod为resyncPeriod ```go type sharedIndexInformer struct { indexer Indexer //informer中的底层缓存cache controller Controller //持有reflector和deltaFIFO对象，reflector对象将会listWatch对象添加到deltaFIFO，同时更新indexer cahce，更新成功则通过sharedProcessor触发用户配置的Eventhandler processor *sharedProcessor //持有一系列的listener，每个listener对应用户的EventHandler cacheMutationDetector MutationDetector //可以先忽略，这个对象可以用来监测local cache是否被外部直接修改 // This block is tracked to handle late initialization of the controller listerWatcher ListerWatcher //deployment的listWatch方法 objectType runtime.Object // resyncCheckPeriod is how often we want the reflector's resync timer to fire so it can call // shouldResync to check if any of our listeners need a resync. resyncCheckPeriod time.Duration // defaultEventHandlerResyncPeriod is the default resync period for any handlers added via // AddEventHandler (i.e. they don't specify one and just want to use the shared informer's default // value). defaultEventHandlerResyncPeriod time.Duration // clock allows for testability clock clock.Clock started, stopped bool startedLock sync.Mutex // blockDeltas gives a way to stop all event distribution so that a late event handler // can safely join the shared informer. blockDeltas sync.Mutex } ``` sharedIndexInformer对象的关键方法： #### sharedIndexInformer的Run方法 前面factory的start方法就是调用了这个Run方法 该方法初始化了controller对象并启动，同时调用processor.run启动所有的listener，用于回调用户配置的EventHandler > 具体sharedIndexInformer中的processor中的listener是怎么添加的，看下文shareProcessor的分析 ```go func (s *sharedIndexInformer) Run(stopCh <-chan struct{}) { defer utilruntime.HandleCrash() //创建一个DeltaFIFO，用于shareIndexInformer.controller.reflector //可以看到这里把indexer即本地缓存传入，用来初始化deltaFIFO的knownObject字段 fifo := NewDeltaFIFO(MetaNamespaceKeyFunc, s.indexer) //shareIndexInformer中的controller的配置 cfg := &Config{ Queue: fifo, ListerWatcher: s.listerWatcher, ObjectType: s.objectType, FullResyncPeriod: s.resyncCheckPeriod, RetryOnError: false, ShouldResync: s.processor.shouldResync, // 这个shouldResync方法将被用在reflector ListAndWatch方法中判断定时时间resyncCheckPeriod到了之后该不该进行resync动作 //一个知道如何处理从informer中的controller中的deltaFIFO pop出来的对象的方法 Process: s.HandleDeltas, } func() { s.startedLock.Lock() defer s.startedLock.Unlock() // 这里New一个具体的controller s.controller = New(cfg) s.controller.(*controller).clock = s.clock s.started = true }() // Separate stop channel because Processor should be stopped strictly after controller processorStopCh := make(chan struct{}) var wg wait.Group defer wg.Wait() // Wait for Processor to stop defer close(processorStopCh) // Tell Processor to stop // 调用processor.run启动所有的listener，回调用户配置的EventHandler wg.StartWithChannel(processorStopCh, s.processor.run) // 启动controller s.controller.Run(stopCh) } ``` #### 为shareIndexInformer创建controller 创建Controller的New方法会生成一个controller对象，只初始化controller的config成员，controller的reflector成员是在Run的时候初始化： - 通过执行reflector.Run方法启动reflector，开启对指定对象的listAndWatch过程，获取的对象将添加到reflector的deltaFIFO中 - 通过不断执行processLoop方法，从DeltaFIFO pop出对象，再调用reflector的Process（就是shareIndexInformer的HandleDeltas方法）处理 ```go func New(c *Config) Controller { ctlr := &controller{ config: *c, clock: &clock.RealClock{}, } return ctlr } //更多字段的配置是在Run的时候 func (c *controller) Run(stopCh <-chan struct{}) { // 使用config创建一个Reflector r := NewReflector( c.config.ListerWatcher, // deployment的listWatch方法 c.config.ObjectType, // deployment{} c.config.Queue, //DeltaFIFO c.config.FullResyncPeriod, //30s ) r.ShouldResync = c.config.ShouldResync //来自sharedProcessor的方法 r.clock = c.clock c.reflectorMutex.Lock() c.reflector = r c.reflectorMutex.Unlock() var wg wait.Group defer wg.Wait() // 启动reflector，执行ListWatch方法 wg.StartWithChannel(stopCh, r.Run) // 不断执行processLoop，这个方法其实就是从DeltaFIFO pop出对象，再调用reflector的Process（其实是shareIndexInformer的HandleDeltas方法）处理 wait.Until(c.processLoop, time.Second, stopCh) } ``` #### controller的processLoop方法 不断执行processLoop，这个方法其实就是从DeltaFIFO pop出对象，再调用reflector的Process（其实是shareIndexInformer的HandleDeltas方法）处理 ``` func (c *controller) processLoop() { for { obj, err := c.config.Queue.Pop(PopProcessFunc(c.config.Process)) if err != nil { if err == ErrFIFOClosed { return } if c.config.RetryOnError { // This is the safe way to re-enqueue. c.config.Queue.AddIfNotPresent(obj) } } } } ``` #### deltaFIFO pop出来的对象处理逻辑 先看看controller怎么处理DeltaFIFO中的对象，需要注意DeltaFIFO中的Deltas的结构，是一个slice，保存同一个对象的所有增量事件 ![image](https://github.com/jianlongzhou/client-go-source-analysis/blob/main/deltaFIFO.png?raw=true) sharedIndexInformer的HandleDeltas处理从deltaFIFO pod出来的增量时，先尝试更新到本地缓存cache，更新成功的话会调用processor.distribute方法向processor中的listener添加notification，listener启动之后会不断获取notification回调用户的EventHandler方法 - Sync: reflector list到对象时Replace到deltaFIFO时daltaType为Sync或者resync把localstrore中的对象加回到deltaFIFO - Added、Updated: reflector watch到对象时根据watch event type是Add还是Modify对应deltaType为Added或者Updated - Deleted: reflector watch到对象的watch event type是Delete或者re-list Replace到deltaFIFO时local store多出的对象以Delete的方式加入deltaFIFO ```go func (s *sharedIndexInformer) HandleDeltas(obj interface{}) error { s.blockDeltas.Lock() defer s.blockDeltas.Unlock() // from oldest to newest for _, d := range obj.(Deltas) { switch d.Type { case Sync, Added, Updated: isSync := d.Type == Sync // 对象先通过shareIndexInformer中的indexer更新到缓存 if old, exists, err := s.indexer.Get(d.Object); err == nil && exists { if err := s.indexer.Update(d.Object); err != nil { return err } // 如果informer的本地缓存更新成功，那么就调用shareProcess分发对象给用户自定义controller处理 // 可以看到，对EventHandler来说，本地缓存已经存在该对象就认为是update s.processor.distribute(updateNotification{oldObj: old, newObj: d.Object}, isSync) } else { if err := s.indexer.Add(d.Object); err != nil { return err } s.processor.distribute(addNotification{newObj: d.Object}, isSync) } case Deleted: if err := s.indexer.Delete(d.Object); err != nil { return err } s.processor.distribute(deleteNotification{oldObj: d.Object}, false) } } return nil } ``` 前面描述了shareIndexInformer内部如何从deltaFIFO取出对象更新缓存并通过processor回调用户的EventHandler，那deltaFIFO中的增量事件是怎么加进入的呢？先看看shareIndexInformer中controller中的reflector实现 #### reflector.run发起ListWatch reflector.run将会调用指定资源的ListAndWatch方法，注意这里什么时候可能发生re-list或者re-watch：因为是通过wait.Util不断调用ListAndWatch方法，所以只要该方法return了，那么就会发生re-list，watch过程则被嵌套在for循环中 - 以ResourceVersion=0开始首次的List操作获取指定资源的全量对象，并通过reflector的syncWith方法将所有对象批量插入deltaFIFO - List完成之后将会更新ResourceVersion用户Watch操作，通过reflector的watchHandler方法把watch到的增量对象加入到deltaFIFO ```go func (r *Reflector) ListAndWatch(stopCh <-chan struct{}) error { // 以版本号ResourceVersion=0开始首次list options := metav1.ListOptions{ResourceVersion: "0"} if err := func() error { initTrace := trace.New("Reflector ListAndWatch", trace.Field{"name", r.name}) var list runtime.Object go func() { // 获取list的结果 list, err = pager.List(context.Background(), options) close(listCh) }() listMetaInterface, err := meta.ListAccessor(list) // 根据结果更新版本号，用于接下来的watch resourceVersion = listMetaInterface.GetResourceVersion() items, err := meta.ExtractList(list) // 这里的syncWith是把首次list到的结果通过DeltaFIFO的Replce方法批量添加到队列 // 队列提供了Resync方法用于判断Replace批量插入的对象是否都pop出去了，factory/informer的WaitForCacheSync就是调用了DeltaFIFO的的Resync方法 if err := r.syncWith(items, resourceVersion); err != nil { return fmt.Errorf("%s: Unable to sync list result: %v", r.name, err) } r.setLastSyncResourceVersion(resourceVersion) }(); err != nil { return err } // 以list对象中获取的ResourceVersion不断watch for { start := r.clock.Now() w, err := r.listerWatcher.Watch(options) // watchhandler处理watch到的数据，即把对象根据watch.type增加到DeltaFIFO中 if err := r.watchHandler(start, w, &resourceVersion, resyncerrc, stopCh); err != nil { if err != errorStopRequested { switch { case apierrs.IsResourceExpired(err): klog.V(4).Infof("%s: watch of %v ended with: %v", r.name, r.expectedType, err) default: klog.Warningf("%s: watch of %v ended with: %v", r.name, r.expectedType, err) } } return nil } } } ``` ##### list出的对象批量插入deltaFIFO > 可以看到是syncWith方法是通过调用deltaFIFO的Replace实现批量插入，具体实现见下文中deltaFIFO的实现描述 ```go func (r *Reflector) syncWith(items []runtime.Object, resourceVersion string) error { found := make([]interface{}, 0, len(items)) for _, item := range items { found = append(found, item) } return r.store.Replace(found, resourceVersion) } ``` ##### watch出的增量对象插入到deltaFIFO > watch到的对象直接根据watch到的事件类型eventType更新store（即deltaFIFO），注意这个event是api直接返回的，watch event type可能是Added、Modifyed、Deleted ```go // watchHandler watches w and keeps *resourceVersion up to date. func (r *Reflector) watchHandler(start time.Time, w watch.Interface, resourceVersion *string, errc chan error, stopCh <-chan struct{}) error { for { select { case <-stopCh: return errorStopRequested case err := <-errc: return err case event, ok := <-w.ResultChan(): switch event.Type { case watch.Added: err := r.store.Add(event.Object) case watch.Modified: err := r.store.Update(event.Object) case watch.Deleted: err := r.store.Delete(event.Object) case watch.Bookmark: // A `Bookmark` means watch has synced here, just update the resourceVersion default: utilruntime.HandleError(fmt.Errorf("%s: unable to understand watch event %#v", r.name, event)) } *resourceVersion = newResourceVersion r.setLastSyncResourceVersion(newResourceVersion) } } } ``` ##### 定时触发resync 在ListAndWatch中还起了一个gorouting定时的进行resync动作 ```go resyncerrc := make(chan error, 1) cancelCh := make(chan struct{}) defer close(cancelCh) go func() { //获取一个定时channel，定时的时间是创建informer factory时传入的resyncPeriod resyncCh, cleanup := r.resyncChan() defer func() { cleanup() // Call the last one written into cleanup }() for { select { case <-resyncCh: case <-stopCh: return case <-cancelCh: return } if r.ShouldResync == nil || r.ShouldResync() { klog.V(4).Infof("%s: forcing resync", r.name) if err := r.store.Resync(); err != nil { resyncerrc <- err return } } cleanup() resyncCh, cleanup = r.resyncChan() } }() ``` 调用deltaFIFO的Resync方法，把底层缓存的对象全部重新添加到deltaFIFO中 ```go func (f *DeltaFIFO) Resync() error { f.lock.Lock() defer f.lock.Unlock() if f.knownObjects == nil { return nil } keys := f.knownObjects.ListKeys() for _, k := range keys { if err := f.syncKeyLocked(k); err != nil { return err } } return nil } ``` 需要注意的是，在添加对象到deltaFIFO时会检查该队列中有没有增量没有处理完的，如果有则忽略这个对象的此次resync ```go func (f *DeltaFIFO) syncKeyLocked(key string) error { obj, exists, err := f.knownObjects.GetByKey(key) if err != nil { klog.Errorf("Unexpected error %v during lookup of key %v, unable to queue object for sync", err, key) return nil } else if !exists { klog.Infof("Key %v does not exist in known objects store, unable to queue object for sync", key) return nil } // If we are doing Resync() and there is already an event queued for that object, // we ignore the Resync for it. This is to avoid the race, in which the resync // comes with the previous value of object (since queueing an event for the object // doesn't trigger changing the underlying store . id, err := f.KeyOf(obj) if err != nil { return KeyError{obj, err} } // 如果deltaFIFO中该对象还有增量没有处理，则忽略以避免冲突，原因如上面注释：在同一个对象的增量列表中，排在后面的增量的object相比前面的增量应该更新才是合理的 if len(f.items[id]) > 0 { return nil } // 跟deltaFIFO的Replace方法一样，都是添加一个Sync类型的增量 if err := f.queueActionLocked(Sync, obj); err != nil { return fmt.Errorf("couldn't queue object: %v", err) } return nil } ``` ### 底层缓存的实现 shareIndexInformer中带有一个缓存indexer，是一个支持索引的map，优点是支持快速查询： - Indexer、Queue接口和cache结构体都实现了顶层的Store接口 - cache结构体持有threadSafeStore对象，threadSafeStore是线程安全的，并且具备自定义索引查找的能力 threadSafeMap的结构如下： > items:存储具体的对象，比如key为ns/podName，value为pod{} > Indexers:一个map[string]IndexFunc结构，其中key为索引的名称，如’namespace’字符串，value则是一个具体的索引函数 > Indices:一个map[string]Index结构，其中key也是索引的名称，value是一个map[string]sets.String结构，其中key是具体的namespace，如default这个ns，vlaue则是这个ns下的按照索引函数求出来的值的集合，比如default这个ns下的所有pod对象名称 ```go type threadSafeMap struct { lock sync.RWMutex items map[string]interface{} // indexers maps a name to an IndexFunc indexers Indexers // indices maps a name to an Index indices Indices } // Indexers maps a name to a IndexFunc type Indexers map[string]IndexFunc // Indices maps a name to an Index type Indices map[string]Index type Index map[string]sets.String ``` #### 索引的维护 通过在向items插入对象的过程中，遍历所有的Indexers中的索引函数，根据索引函数存储索引key到value的集合关系，以下图式结构可以很好的说明： ![图片来源于网络](https://user-images.githubusercontent.com/41672087/116666278-5981ca00-a9cd-11eb-9570-8ee6eb447d05.png) #### 缓存中增加对象 在向threadSafeMap的items map中增加完对象后，再通过updateIndices更新索引结构 ```go func (c *threadSafeMap) Add(key string, obj interface{}) { c.lock.Lock() defer c.lock.Unlock() oldObject := c.items[key] //存储对象 c.items[key] = obj //更新索引 c.updateIndices(oldObject, obj, key) } // updateIndices modifies the objects location in the managed indexes, if this is an update, you must provide an oldObj // updateIndices must be called from a function that already has a lock on the cache func (c *threadSafeMap) updateIndices(oldObj interface{}, newObj interface{}, key string) { // if we got an old object, we need to remove it before we add it again if oldObj != nil { // 这是一个更新操作，先删除原对象的索引记录 c.deleteFromIndices(oldObj, key) } // 枚举所有添加的索引函数 for name, indexFunc := range c.indexers { //根据索引函数计算obj对应的 indexValues, err := indexFunc(newObj) if err != nil { panic(fmt.Errorf("unable to calculate an index entry for key %q on index %q: %v", key, name, err)) } index := c.indices[name] if index == nil { index = Index{} c.indices[name] = index } //索引函数计算出多个value，也可能是一个，比如pod的ns就只有一个值，pod的label可能就有多个值 for _, indexValue := range indexValues { //比如namespace索引，根据indexValue=default，获取default对应的ji he再把当前对象插入 set := index[indexValue] if set == nil { set = sets.String{} index[indexValue] = set } set.Insert(key) } } } ``` #### IndexFunc索引函数 一个典型的索引函数MetaNamespaceIndexFunc，方便查询时可以根据namespace获取该namespace下的所有对象 ```go // MetaNamespaceIndexFunc is a default index function that indexes based on an object's namespace func MetaNamespaceIndexFunc(obj interface{}) ([]string, error) { meta, err := meta.Accessor(obj) if err != nil { return []string{""}, fmt.Errorf("object has no meta: %v", err) } return []string{meta.GetNamespace()}, nil } ``` #### Index方法利用索引查找对象 提供利用索引来查询的能力，Index方法可以根据索引名称和对象，查询所有的关联对象 > 例如通过 `Index(“namespace”, &metav1.ObjectMeta{Namespace: namespace})`获取指定ns下的所有对象，具体可以参考tools/cache/listers.go#ListAllByNamespace > ```go func (c *threadSafeMap) Index(indexName string, obj interface{}) ([]interface{}, error) { c.lock.RLock() defer c.lock.RUnlock() indexFunc := c.indexers[indexName] if indexFunc == nil { return nil, fmt.Errorf("Index with name %s does not exist", indexName) } indexKeys, err := indexFunc(obj) if err != nil { return nil, err } index := c.indices[indexName] var returnKeySet sets.String //例如namespace索引 if len(indexKeys) == 1 { // In majority of cases, there is exactly one value matching. // Optimize the most common path - deduping is not needed here. returnKeySet = index[indexKeys[0]] //例如label索引 } else { // Need to de-dupe the return list. // Since multiple keys are allowed, this can happen. returnKeySet = sets.String{} for _, indexKey := range indexKeys { for key := range index[indexKey] { returnKeySet.Insert(key) } } } list := make([]interface{}, 0, returnKeySet.Len()) for absoluteKey := range returnKeySet { list = append(list, c.items[absoluteKey]) } return list, nil } ``` ### deltaFIFO实现 shareIndexInformer.controller.reflector中的deltaFIFO实现 > items：记录deltaFIFO中的对象，注意map的value是一个delta slice > queue：记录上面items中的key，维护对象的fifo顺序 > populated：队列中是否填充过数据，LIST时调用Replace或调用Delete/Add/Update都会置为true > initialPopulationCount：首次List的时候获取到的数据就会调用Replace批量增加到队列，同时设置initialPopulationCount为List到的对象数量，每次Pop出来会减一，用于判断是否把首次批量插入的数据都POP出去了 > keyFunc：知道怎么从对象中解析出对应key的函数，如MetaNamespaceKeyFunc可以解析出namespace/name的形式 > knownObjects：这个其实就是shareIndexInformer中的indexer底层缓存的引用，可以认为和etcd中的数据一致 ```go // NewDeltaFIFO方法在前面分析的sharedIndexInformer的Run方法中调用 // fifo := NewDeltaFIFO(MetaNamespaceKeyFunc, s.indexer) func NewDeltaFIFO(keyFunc KeyFunc, knownObjects KeyListerGetter) *DeltaFIFO { f := &DeltaFIFO{ items: map[string]Deltas{}, queue: []string{}, keyFunc: keyFunc, knownObjects: knownObjects, } f.cond.L = &f.lock return f } type DeltaFIFO struct { // lock/cond protects access to 'items' and 'queue'. lock sync.RWMutex cond sync.Cond // We depend on the property that items in the set are in // the queue and vice versa, and that all Deltas in this // map have at least one Delta. // 这里的Deltas是[]Delta类型 items map[string]Deltas queue []string // populated is true if the first batch of items inserted by Replace() has been populated // or Delete/Add/Update was called first. populated bool // initialPopulationCount is the number of items inserted by the first call of Replace() initialPopulationCount int // keyFunc is used to make the key used for queued item // insertion and retrieval, and should be deterministic. keyFunc KeyFunc // knownObjects list keys that are "known", for the // purpose of figuring out which items have been deleted // when Replace() or Delete() is called. // 这个其实就是shareIndexInformer中的indexer底层缓存的引用 knownObjects KeyListerGetter // Indication the queue is closed. // Used to indicate a queue is closed so a control loop can exit when a queue is empty. // Currently, not used to gate any of CRED operations. closed bool closedLock sync.Mutex } type Delta struct { Type DeltaType Object interface{} } // Deltas is a list of one or more 'Delta's to an individual object. // The oldest delta is at index 0, the newest delta is the last one. type Deltas []Delta ``` DeltaFIFO关键的方法： #### 向deltaFIFO批量插入对象 批量向队列插入数据的方法，注意knownObjects是informer中本地缓存indexer的引用 这里会更新deltaFIFO的initialPopulationCount为Replace list的对象总数加上list中相比knownObjects多出的对象数量。 > 因为Replace方法可能是reflector发生re-list的时候再次调用，这个时候就会出现knownObjects中存在的对象不在Replace list的情况（比如watch的delete事件丢失了），这个时候是把这些对象筛选出来，封装成DeletedFinalStateUnknown对象以Delete type类型再次加入到deltaFIFO中，这样最终从detaFIFO处理这个DeletedFinalStateUnknown 增量时就可以更新本地缓存并且触发reconcile。 > 因为这个对象最终的结构确实找不到了，所以只能用knownObjects里面的记录来封装delta，所以叫做FinalStateUnknown。 ```go func (f *DeltaFIFO) Replace(list []interface{}, resourceVersion string) error { f.lock.Lock() defer f.lock.Unlock() keys := make(sets.String, len(list)) for _, item := range list { key, err := f.KeyOf(item) if err != nil { return KeyError{item, err} } keys.Insert(key) // 调用deltaFIFO的queueActionLocked向deltaFIFO增加一个增量 // 可以看到Replace添加的Delta type都是Sync if err := f.queueActionLocked(Sync, item); err != nil { return fmt.Errorf("couldn't enqueue object: %v", err) } } // 底层的缓存不应该会是nil，可以忽略这种情况 if f.knownObjects == nil { // Do deletion detection against our own list. queuedDeletions := 0 for k, oldItem := range f.items { if keys.Has(k) { continue } // 当knownObjects为空时，如果item中存在对象不在新来的list中，那么该对象被认为要被删除 var deletedObj interface{} if n := oldItem.Newest(); n != nil { deletedObj = n.Object } queuedDeletions++ if err := f.queueActionLocked(Deleted, DeletedFinalStateUnknown{k, deletedObj}); err != nil { return err } } if !f.populated { f.populated = true // While there shouldn't be any queued deletions in the initial // population of the queue, it's better to be on the safe side. f.initialPopulationCount = len(list) + queuedDeletions } return nil } // Detect deletions not already in the queue. // 当reflector发生re-list时，可能会出现knownObjects中存在的对象不在Replace list的情况 knownKeys := f.knownObjects.ListKeys() // 记录这次替换相当于在缓存中删除多少对象 queuedDeletions := 0 // 枚举local store中的所有对象 for _, k := range knownKeys { // 对象也在Replace list中，所以跳过 if keys.Has(k) { continue } // 对象在缓存，但不在list中，说明替换操作完成后，这个对象相当于被删除了 // 注意这里的所谓替换，对deltaFIFO来说，是给队列中的对应对象增加一个 // delete增量queueActionLocked(Deleted, DeletedFinalStateUnknown{k, deletedObj}) // 真正删除缓存需要等到DeletedFinalStateUnknown增量被POP出来操作local store时 deletedObj, exists, err := f.knownObjects.GetByKey(k) queuedDeletions++ if err := f.queueActionLocked(Deleted, DeletedFinalStateUnknown{k, deletedObj}); err != nil { return err } } // 设置f.initialPopulationCount，该值大于0表示首次插入的对象还没有全部pop出去 // informer WaitForCacheSync就是在等待该值为0 if !f.populated { f.populated = true f.initialPopulationCount = len(list) + queuedDeletions } return nil } ``` #### 从deltaFIFO pop出对象 从队列中Pop出一个方法，并由函数process来处理，其实就是shareIndexInformer的HandleDeltas > 每次从DeltaFIFO Pop出一个对象，f.initialPopulationCount会减一，初始值为List时的对象数量 > 前面的Informer的WaitForCacheSync最终就是调用了这个HasSynced方法 ```go func (f *DeltaFIFO) Pop(process PopProcessFunc) (interface{}, error) { f.lock.Lock() defer f.lock.Unlock() for { for len(f.queue) == 0 { // When the queue is empty, invocation of Pop() is blocked until new item is enqueued. // When Close() is called, the f.closed is set and the condition is broadcasted. // Which causes this loop to continue and return from the Pop(). if f.IsClosed() { return nil, ErrFIFOClosed } f.cond.Wait() } //取出队首元素 id := f.queue[0] //去掉队首元素 f.queue = f.queue[1:] //首次填充的对象数减一 if f.initialPopulationCount > 0 { f.initialPopulationCount-- } item, ok := f.items[id] if !ok { // Item may have been deleted subsequently. continue } delete(f.items, id) //处理增量对象 err := process(item) // 如果没有处理成功，那么就会重新加到deltaFIFO队列中 if e, ok := err.(ErrRequeue); ok { f.addIfNotPresent(id, item) err = e.Err } // Don't need to copyDeltas here, because we're transferring // ownership to the caller. return item, err } } ``` #### deltaFIFO是否同步完成 串连前面的问题：factory的WaitForCacheSync是如何等待缓存同步完成 > factory的WaitForCacheSync方法调用informer的HasSync方法，继而调用deltaFIFO的HasSync方法，也就是判断从reflector list到的数据是否pop完 ```go func (f *DeltaFIFO) HasSynced() bool { f.lock.Lock() defer f.lock.Unlock() return f.populated && f.initialPopulationCount == 0 } ``` #### 同步local store到deltaFIFO > 所谓的resync，其实就是把knownObjects即缓存中的对象全部再通过queueActionLocked(Sync, obj)加到队列 ```go func (f *DeltaFIFO) Resync() error { f.lock.Lock() defer f.lock.Unlock() if f.knownObjects == nil { return nil } keys := f.knownObjects.ListKeys() // 把local store中的对象都以Sync类型增量的形式重新放回到deltaFIFO for _, k := range keys { if err := f.syncKeyLocked(k); err != nil { return err } } return nil } func (f *DeltaFIFO) syncKeyLocked(key string) error { obj, exists, err := f.knownObjects.GetByKey(key) // If we are doing Resync() and there is already an event queued for that object, // we ignore the Resync for it. This is to avoid the race, in which the resync // comes with the previous value of object (since queueing an event for the object // doesn't trigger changing the underlying store . id, err := f.KeyOf(obj) if err != nil { return KeyError{obj, err} } // 如上述注释，在resync时，如果deltaFIFO中该对象还存在其他delta没处理，那么忽略这次的resync // 因为调用queueActionLocked是增加delta是通过append的，且处理对象的增量delta时，是从oldest到newdest的 // 所以如果某个对象还存在增量没处理，再append就可能导致后处理的delta是旧的对象 if len(f.items[id]) > 0 { return nil } // 可以看到这里跟list一样，增加到deltaFIFO的是一个Sync类型的增量 if err := f.queueActionLocked(Sync, obj); err != nil { return fmt.Errorf("couldn't queue object: %v", err) } return nil } ``` #### 在deltaFIFO增加一个对象 注意这里在append增量时的去重逻辑：如果连续的两个增量类型都是Deleted，那么就去掉一个（正常情况确实不会出现这样，且没必要），优先去掉前面所说的因为re-list可能导致的api与local store不一致而增加的DeletedFinalStateUnknown类型的增量 ```go //在队列中给指定的对象append一个Delta func (f *DeltaFIFO) queueActionLocked(actionType DeltaType, obj interface{}) error { id, err := f.KeyOf(obj) if err != nil { return KeyError{obj, err} } // 把增量append到slice的后面 newDeltas := append(f.items[id], Delta{actionType, obj}) // 连续的两个Deleted delta将会去掉一个 newDeltas = dedupDeltas(newDeltas) if len(newDeltas) > 0 { // 维护queue队列 if _, exists := f.items[id]; !exists { f.queue = append(f.queue, id) } f.items[id] = newDeltas f.cond.Broadcast() } else { // We need to remove this from our map (extra items in the queue are // ignored if they are not in the map). delete(f.items, id) } return nil } ``` 当前认为只有连续的两个Delete delta才有必要去重 ```go func dedupDeltas(deltas Deltas) Deltas { n := len(deltas) if n < 2 { return deltas } // 每次取最后两个delta来判断 a := &deltas[n-1] b := &deltas[n-2] if out := isDup(a, b); out != nil { d := append(Deltas{}, deltas[:n-2]...) return append(d, *out) } return deltas } func isDup(a, b *Delta) *Delta { // 当前认为只有连续的两个Delete delta才有必要去重 if out := isDeletionDup(a, b); out != nil { return out } // TODO: Detect other duplicate situations? Are there any? return nil } // keep the one with the most information if both are deletions. func isDeletionDup(a, b *Delta) *Delta { if b.Type != Deleted || a.Type != Deleted { return nil } // Do more sophisticated checks, or is this sufficient? // 优先去重DeletedFinalStateUnknown类型的Deleted delta if _, ok := b.Object.(DeletedFinalStateUnknown); ok { return a } return b } ``` ### sharedProcessor的实现 shareIndexInformer中的sharedProcess结构，用于分发deltaFIFO的对象，回调用户配置的EventHandler方法 可以看到shareIndexInformer中的process直接通过&sharedProcessor{clock: realClock}初始化 ```go // NewSharedIndexInformer creates a new instance for the listwatcher. func NewSharedIndexInformer(lw ListerWatcher, objType runtime.Object, defaultEventHandlerResyncPeriod time.Duration, indexers Indexers) SharedIndexInformer { realClock := &clock.RealClock{} sharedIndexInformer := &sharedIndexInformer{ // 初始化一个默认的processor processor: &sharedProcessor{clock: realClock}, indexer: NewIndexer(DeletionHandlingMetaNamespaceKeyFunc, indexers), listerWatcher: lw, objectType: objType, resyncCheckPeriod: defaultEventHandlerResyncPeriod, defaultEventHandlerResyncPeriod: defaultEventHandlerResyncPeriod, // cacheMutationDetector：可以记录local store是否被外部修改 cacheMutationDetector: NewCacheMutationDetector(fmt.Sprintf("%T", objType)), clock: realClock, } return sharedIndexInformer } ``` 如下为sharedProcessor结构： > listenersStarted：listeners中包含的listener是否都已经启动了 > listeners：已添加的listener列表，用来处理watch到的数据 > syncingListeners：已添加的listener列表，用来处理list或者resync的数据 ```go type sharedProcessor struct { listenersStarted bool listenersLock sync.RWMutex listeners []*processorListener syncingListeners []*processorListener clock clock.Clock wg wait.Group } ``` #### 理解listeners和syncingListeners的区别 processor可以支持listener的维度配置是否需要resync：一个informer可以配置多个EventHandler，而一个EventHandler对应processor中的一个listener，每个listener可以配置需不需要resync，如果某个listener需要resync，那么添加到deltaFIFO的Sync增量最终也只会回到对应的listener reflector中会定时判断每一个listener是否需要进行resync，判断的依据是看配置EventHandler的时候指定的resyncPeriod，0代表该listener不需要resync，否则就每隔resyncPeriod看看是否到时间了 - listeners：记录了informer添加的所有listener - syncingListeners：记录了informer中哪些listener处于sync状态 syncingListeners是listeners的子集，syncingListeners记录那些开启了resync且时间已经到达了的listener，把它们放在一个独立的slice是避免下面分析的distribute方法中把obj增加到了还不需要resync的listener中 #### 为sharedProcessor添加listener 在sharedProcessor中添加一个listener ```go func (p *sharedProcessor) addListenerLocked(listener *processorListener) { // 同时添加到listeners和syncingListeners列表，但其实添加的是同一个对象的引用 // 所以下面run启动的时候只需要启动listeners中listener就可以了 p.listeners = append(p.listeners, listener) p.syncingListeners = append(p.syncingListeners, listener) } ``` #### 启动sharedProcessor中的listener sharedProcessor启动所有的listener 是通过调用listener.run和listener.pop来启动一个listener，两个方法具体作用看下文processorListener说明 ```go func (p *sharedProcessor) run(stopCh <-chan struct{}) { func() { p.listenersLock.RLock() defer p.listenersLock.RUnlock() for _, listener := range p.listeners { // listener的run方法不断的从listener自身的缓冲区取出对象回调handler p.wg.Start(listener.run) // listener的pod方法不断的接收对象并暂存在自身的缓冲区中 p.wg.Start(listener.pop) } p.listenersStarted = true }() <-stopCh p.listenersLock.RLock() defer p.listenersLock.RUnlock() for _, listener := range p.listeners { close(listener.addCh) // Tell .pop() to stop. .pop() will tell .run() to stop } p.wg.Wait() // Wait for all .pop() and .run() to stop } ``` #### sharedProcessor分发对象 distribute方法是在前面介绍`[deltaFIFO pop出来的对象处理逻辑]`时提到的，把notification事件添加到listener中，listener如何pop出notification回调EventHandler见下文listener部分分析 当通过distribute分发从deltaFIFO获取的对象时，如果delta type是Sync，那么就会把对象交给sync listener来处理，而Sync类型的delta只能来源于下面两种情况： - reflector list Replace到deltaFIFO的对象：因为首次在sharedProcessor增加一个listener的时候是同时加在listeners和syncingListeners中的 - reflector定时触发resync local store到deltaFIFO的对象：因为每次reflector调用processor的shouldResync时，都会把达到resync条件的listener筛选出来重新放到p.syncingListeners 上面两种情况都可以在p.syncingListeners中准备好listener ```go func (p *sharedProcessor) distribute(obj interface{}, sync bool) { p.listenersLock.RLock() defer p.listenersLock.RUnlock() // 如果是通过reflector list Replace到deltaFIFO的对象或者reflector定时触发resync到deltaFIFO的对象，那么distribute到syncingListeners if sync { // 保证deltaFIFO Resync方法过来的delta obj只给开启了resync能力的listener for _, listener := range p.syncingListeners { listener.add(obj) } } else { for _, listener := range p.listeners { listener.add(obj) } } } ``` ### processorListener结构 sharedProcessor中的listener具体的类型：运转逻辑就是把用户通过addCh增加的事件发送到nextCh供run方法取出回调Eventhandler，因为addCh和nectCh都是无缓冲channel，所以中间引入ringBuffer做缓存 processorListener是sharedIndexInformer调用AddEventHandler时创建并添加到sharedProcessor，对于一个Informer，可以多次调用AddEventHandler来添加多个listener > addCh：无缓冲的chan，listener的pod方法不断从addCh取出对象丢给nextCh。addCh中的对象来源于listener的add方法，如果nextCh不能及时消费，则放入缓冲区pendingNotifications > nextCh：无缓冲的chan，listener的run方法不断从nextCh取出对象回调用户handler。nextCh的对象来源于addCh或者缓冲区 > pendingNotifications：一个无容量限制的环形缓冲区，可以理解为可以无限存储的队列，用来存储deltaFIFO分发过来的消息 > nextResync：由resyncPeriod和requestedResyncPeriod计算得出，与当前时间now比较判断listener是否该进行resync了 > resyncPeriod：listener自身期待多长时间进行resync > requestedResyncPeriod：informer希望listener多长时间进行resync ```go type processorListener struct { nextCh chan interface{} addCh chan interface{} handler ResourceEventHandler // pendingNotifications is an unbounded ring buffer that holds all notifications not yet distributed. // There is one per listener, but a failing/stalled listener will have infinite pendingNotifications // added until we OOM. // TODO: This is no worse than before, since reflectors were backed by unbounded DeltaFIFOs, but // we should try to do something better. pendingNotifications buffer.RingGrowing // requestedResyncPeriod is how frequently the listener wants a full resync from the shared informer requestedResyncPeriod time.Duration // resyncPeriod is how frequently the listener wants a full resync from the shared informer. This // value may differ from requestedResyncPeriod if the shared informer adjusts it to align with the // informer's overall resync check period. resyncPeriod time.Duration // nextResync is the earliest time the listener should get a full resync nextResync time.Time // resyncLock guards access to resyncPeriod and nextResync resyncLock sync.Mutex } ``` #### 在listener中添加事件 shareProcessor中的distribute方法调用的是listener的add来向addCh增加消息，注意addCh是无缓冲的chan，依赖pop不断从addCh取出数据 ```go func (p *processorListener) add(notification interface{}) { // 虽然p.addCh是一个无缓冲的channel，但是因为listener中存在ring buffer，所以这里并不会一直阻塞 p.addCh <- notification } ``` #### 判断是否需要resync 如果resyncPeriod为0表示不需要resync，否则判断当前时间now是否已经超过了nextResync，是的话则返回true表示需要resync。其中nextResync在每次调用listener的shouldResync方法成功时更新 ```go // shouldResync queries every listener to determine if any of them need a resync, based on each // listener's resyncPeriod. func (p *sharedProcessor) shouldResync() bool { p.listenersLock.Lock() defer p.listenersLock.Unlock() // 这里每次都会先置空列表，保证里面记录了当前需要resync的listener p.syncingListeners = []*processorListener{} resyncNeeded := false now := p.clock.Now() for _, listener := range p.listeners { // need to loop through all the listeners to see if they need to resync so we can prepare any // listeners that are going to be resyncing. if listener.shouldResync(now) { resyncNeeded = true // 达到resync条件的listener被加入syncingListeners p.syncingListeners = append(p.syncingListeners, listener) listener.determineNextResync(now) } } return resyncNeeded } ``` #### listener的run方法回调EventHandler listener的run方法不断的从nextCh中获取notification，并根据notification的类型来调用用户自定的EventHandler ```go func (p *processorListener) run() { // this call blocks until the channel is closed. When a panic happens during the notification // we will catch it, **the offending item will be skipped!**, and after a short delay (one second) // the next notification will be attempted. This is usually better than the alternative of never // delivering again. stopCh := make(chan struct{}) wait.Until(func() { // this gives us a few quick retries before a long pause and then a few more quick retries err := wait.ExponentialBackoff(retry.DefaultRetry, func() (bool, error) { for next := range p.nextCh { switch notification := next.(type) { case updateNotification: // 回调用户配置的handler p.handler.OnUpdate(notification.oldObj, notification.newObj) case addNotification: p.handler.OnAdd(notification.newObj) case deleteNotification: p.handler.OnDelete(notification.oldObj) default: utilruntime.HandleError(fmt.Errorf("unrecognized notification: %T", next)) } } // the only way to get here is if the p.nextCh is empty and closed return true, nil }) // the only way to get here is if the p.nextCh is empty and closed if err == nil { close(stopCh) } }, 1*time.Minute, stopCh) } ``` #### addCh到nextCh的对象传递 listener中pop方法的逻辑相对比较绕，最终目的就是把分发到addCh的数据从nextCh或者pendingNotifications取出来 > notification变量记录下一次要被放到p.nextCh供pop方法取出的对象 > 开始seletct时必然只有case2可能ready > Case2做的事可以描述为：从p.addCh获取对象，如果临时变量notification还是nil，说明需要往notification赋值，供case1推送到p.nextCh > 如果notification已经有值了，那个当前从p.addCh取出的值要先放到环形缓冲区中 > Case1做的事可以描述为：看看能不能把临时变量notification推送到nextCh（nil chan会阻塞在读写操作上），可以写的话，说明这个nextCh是p.nextCh，写成功之后，需要从缓存中取出一个对象放到notification为下次执行这个case做准备，如果缓存是空的，通过把nextCh chan设置为nil来禁用case1，以便case2位notification赋值 ```go func (p *processorListener) pop() { defer utilruntime.HandleCrash() defer close(p.nextCh) // Tell .run() to stop //nextCh没有利用make初始化，将阻塞在读和写上 var nextCh chan<- interface{} //notification初始值为nil var notification interface{} for { select { // 执行这个case，相当于给p.nextCh添加来自p.addCh的内容 case nextCh <- notification: // Notification dispatched var ok bool //前面的notification已经加到p.nextCh了， 为下一次这个case再次ready做准备 notification, ok = p.pendingNotifications.ReadOne() if !ok { // Nothing to pop nextCh = nil // Disable this select case } //第一次select只有这个case ready case notificationToAdd, ok := <-p.addCh: if !ok { return } if notification == nil { // No notification to pop (and pendingNotifications is empty) // Optimize the case - skip adding to pendingNotifications //为notification赋值 notification = notificationToAdd //唤醒第一个case nextCh = p.nextCh } else { // There is already a notification waiting to be dispatched //select没有命中第一个case，那么notification就没有被消耗，那么把从p.addCh获取的对象加到缓存中 p.pendingNotifications.WriteOne(notificationToAdd) } } } } ```