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
图 9.5.1.1:client-go informer

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

// 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。下面是对该结构的描述:

  • 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
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

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

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

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

// 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
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
// 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
// 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

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

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

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
图 9.5.1.2:image

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

    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
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

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

// 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

    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

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

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 <knownObjects>.
   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

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
图 9.5.1.3:图片来源于网络

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

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

// 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

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

// 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。

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

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

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

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 <knownObjects>.
   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

//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

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

// 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

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

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

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

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

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

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

// 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

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

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)
         }
      }
   }
}
Copyright © 2017-2022 | Distributed under CC BY 4.0 | jimmysong.io all right reserved. Updated at 2022-06-01 07:51:14

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