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
client: clientset，支持直接请求api中各内置资源对象的restful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
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：
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到的数据
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)
}
}
}
}