之前了解了client-go中的架构设计，也就是 tools/cache 下面的一些概念，那么下面将对informer进行分析

Controller

在client-go informer架构中存在一个 controller ，这个不是 Kubernetes 中的Controller组件；而是在 tools/cache 中的一个概念，controller 位于 informer 之下，Reflector 之上。code

Config

从严格意义上来讲，controller 是作为一个 sharedInformer 使用，通过接受一个 Config ，而 Reflector 则作为 controller 的 slot。Config 则包含了这个 controller 里所有的设置。

type Config struct {
	Queue // DeltaFIFO
	ListerWatcher // 用于list watch的
	Process ProcessFunc // 定义如何从DeltaFIFO中弹出数据后处理的操作
	ObjectType runtime.Object // Controller处理的对象数据，实际上就是kubernetes中的资源
	FullResyncPeriod time.Duration // 全量同步的周期
	ShouldResync ShouldResyncFunc // Reflector通过该标记来确定是否应该重新同步
	RetryOnError bool
}

controller

然后 controller 又为 reflertor 的上层

type controller struct {
	config         Config
	reflector      *Reflector 
	reflectorMutex sync.RWMutex
	clock          clock.Clock
}

type Controller interface {
	// controller 主要做两件事，
    // 1. 构建并运行 Reflector,将listerwacther中的泵压到queue（Delta fifo）中
    // 2. Queue用Pop()弹出数据，具体的操作是Process
    // 直到 stopCh 不阻塞，这两个协程将退出
	Run(stopCh <-chan struct{})
	HasSynced() bool // 这个实际上是从store中继承的，标记这个controller已经
	LastSyncResourceVersion() string
}

controller 中的方法，仅有一个 Run() 和 New()；这意味着，controller 只是一个抽象的概念，作为 Reflector, Delta FIFO 整合的工作流

而 controller 则是 SharedInformer 了。

Queue

这里的 queue 可以理解为是一个具有 Pop() 功能的 Indexer ;而 Pop() 的功能则是 controller 中的一部分；也就是说 queue 是一个扩展的 Store ， Store 是不具备弹出功能的。

type Queue interface {
	Store
	// Pop会阻塞等待，直到有内容弹出，删除对应的值并处理计数器
	Pop(PopProcessFunc) (interface{}, error)

	// AddIfNotPresent puts the given accumulator into the Queue (in
	// association with the accumulator's key) if and only if that key
	// is not already associated with a non-empty accumulator.
	AddIfNotPresent(interface{}) error

	// HasSynced returns true if the first batch of keys have all been
	// popped.  The first batch of keys are those of the first Replace
	// operation if that happened before any Add, Update, or Delete;
	// otherwise the first batch is empty.
	HasSynced() bool
	Close() // 关闭queue
}

而弹出的操作是通过 controller 中的 processLoop() 进行的，最终走到Delta FIFO中进行处理。

通过忙等待去读取要弹出的数据，然后在弹出前 通过PopProcessFunc 进行处理

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()

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()
		}
		id := f.queue[0]
		f.queue = f.queue[1:]
		if f.initialPopulationCount > 0 {
			f.initialPopulationCount--
		}
		item, ok := f.items[id]
		if !ok {
			// Item may have been deleted subsequently.
			continue
		}
		delete(f.items, id)
		err := process(item) // 进行处理
		if e, ok := err.(ErrRequeue); ok {
			f.addIfNotPresent(id, item) // 如果失败，再重新加入到队列中
			err = e.Err 
		}
		// Don't need to copyDeltas here, because we're transferring
		// ownership to the caller.
		return item, err
	}
}

Informer

通过对 Reflector, Store, Queue, ListerWatcher、ProcessFunc, 等的概念，发现由 controller 所包装的起的功能并不能完成通过对API的动作监听，并通过动作来处理本地缓存的一个能力；这个情况下诞生了 informer 严格意义上来讲是 sharedInformer

func newInformer(
	lw ListerWatcher,
	objType runtime.Object,
	resyncPeriod time.Duration,
	h ResourceEventHandler,
	clientState Store,
) Controller {
	// This will hold incoming changes. Note how we pass clientState in as a
	// KeyLister, that way resync operations will result in the correct set
	// of update/delete deltas.
	fifo := NewDeltaFIFOWithOptions(DeltaFIFOOptions{
		KnownObjects:          clientState,
		EmitDeltaTypeReplaced: true,
	})

	cfg := &Config{
		Queue:            fifo,
		ListerWatcher:    lw,
		ObjectType:       objType,
		FullResyncPeriod: resyncPeriod,
		RetryOnError:     false,

		Process: func(obj interface{}) error {
			// from oldest to newest
			for _, d := range obj.(Deltas) {
				switch d.Type {
				case Sync, Replaced, Added, Updated:
					if old, exists, err := clientState.Get(d.Object); err == nil && exists {
						if err := clientState.Update(d.Object); err != nil {
							return err
						}
						h.OnUpdate(old, d.Object)
					} else {
						if err := clientState.Add(d.Object); err != nil {
							return err
						}
						h.OnAdd(d.Object)
					}
				case Deleted:
					if err := clientState.Delete(d.Object); err != nil {
						return err
					}
					h.OnDelete(d.Object)
				}
			}
			return nil
		},
	}
	return New(cfg)
}

newInformer是位于 tools/cache/controller.go 下，可以看出，这里面并没有informer的概念，这里通过注释可以看到，newInformer实际上是一个提供了存储和事件通知的informer。他关联的 queue 则是 Delta FIFO，并包含了 ProcessFunc, Store 等 controller的概念。最终对外的方法为 NewInformer()

func NewInformer(
	lw ListerWatcher,
	objType runtime.Object,
	resyncPeriod time.Duration,
	h ResourceEventHandler,
) (Store, Controller) {
	// This will hold the client state, as we know it.
	clientState := NewStore(DeletionHandlingMetaNamespaceKeyFunc)

	return clientState, newInformer(lw, objType, resyncPeriod, h, clientState)
}

type ResourceEventHandler interface {
	OnAdd(obj interface{})
	OnUpdate(oldObj, newObj interface{})
	OnDelete(obj interface{})
}

可以看到 NewInformer() 就是一个带有 Store功能的controller，通过这些可以假定出，Informer 就是controller ，将queue中相关操作分发给不同事件处理的功能

SharedIndexInformer

shareInformer 为客户端提供了与apiserver一致的数据对象本地缓存，并支持多事件处理程序的informer，而 shareIndexInformer 则是对shareInformer 的扩展

type SharedInformer interface {
	// AddEventHandler adds an event handler to the shared informer using the shared informer's resync
	// period.  Events to a single handler are delivered sequentially, but there is no coordination
	// between different handlers.
	AddEventHandler(handler ResourceEventHandler)
	// AddEventHandlerWithResyncPeriod adds an event handler to the
	// shared informer with the requested resync period; zero means
	// this handler does not care about resyncs.  The resync operation
	// consists of delivering to the handler an update notification
	// for every object in the informer's local cache; it does not add
	// any interactions with the authoritative storage.  Some
	// informers do no resyncs at all, not even for handlers added
	// with a non-zero resyncPeriod.  For an informer that does
	// resyncs, and for each handler that requests resyncs, that
	// informer develops a nominal resync period that is no shorter
	// than the requested period but may be longer.  The actual time
	// between any two resyncs may be longer than the nominal period
	// because the implementation takes time to do work and there may
	// be competing load and scheduling noise.
	AddEventHandlerWithResyncPeriod(handler ResourceEventHandler, resyncPeriod time.Duration)
	// GetStore returns the informer's local cache as a Store.
	GetStore() Store
	// GetController is deprecated, it does nothing useful
	GetController() Controller
	// Run starts and runs the shared informer, returning after it stops.
	// The informer will be stopped when stopCh is closed.
	Run(stopCh <-chan struct{})
	// HasSynced returns true if the shared informer's store has been
	// informed by at least one full LIST of the authoritative state
	// of the informer's object collection.  This is unrelated to "resync".
	HasSynced() bool
	// LastSyncResourceVersion is the resource version observed when last synced with the underlying
	// store. The value returned is not synchronized with access to the underlying store and is not
	// thread-safe.
	LastSyncResourceVersion() string
}

SharedIndexInformer 是对SharedInformer的实现，可以从结构中看出，SharedIndexInformer 大致具有如下功能：

• 索引本地缓存
• controller，通过list watch拉取API并推入 Deltal FIFO
• 事件的处理

type sharedIndexInformer struct {
	indexer    Indexer // 具有索引的本地缓存
	controller Controller // controller

	processor             *sharedProcessor // 事件处理函数集合
	cacheMutationDetector MutationDetector

	listerWatcher ListerWatcher
	objectType runtime.Object
	resyncCheckPeriod time.Duration
	defaultEventHandlerResyncPeriod time.Duration
	clock clock.Clock
	started, stopped bool
	startedLock      sync.Mutex
	blockDeltas sync.Mutex
}

而在 tools/cache/share_informer.go 可以看到 shareIndexInformer 的运行过程

func (s *sharedIndexInformer) Run(stopCh <-chan struct{}) {
	defer utilruntime.HandleCrash()

	fifo := NewDeltaFIFOWithOptions(DeltaFIFOOptions{
		KnownObjects:          s.indexer,
		EmitDeltaTypeReplaced: true,
	})

	cfg := &Config{
		Queue:            fifo,
		ListerWatcher:    s.listerWatcher,
		ObjectType:       s.objectType,
		FullResyncPeriod: s.resyncCheckPeriod,
		RetryOnError:     false,
		ShouldResync:     s.processor.shouldResync,

		Process: s.HandleDeltas, // process 弹出时操作的流程
	}

	func() {
		s.startedLock.Lock()
		defer s.startedLock.Unlock()

		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
	wg.StartWithChannel(processorStopCh, s.cacheMutationDetector.Run)
	wg.StartWithChannel(processorStopCh, s.processor.run) // 启动事件处理函数

	defer func() {
		s.startedLock.Lock()
		defer s.startedLock.Unlock()
		s.stopped = true // Don't want any new listeners
	}()
    s.controller.Run(stopCh) // 启动controller，controller会启动Reflector和fifo的Pop()
}

而在操作Delta FIFO中可以看到，做具体操作时，会将动作分发至对应的事件处理函数中，这个是informer初始化时对事件操作的函数

func (s *sharedIndexInformer) HandleDeltas(obj interface{}) error {
	s.blockDeltas.Lock()
	defer s.blockDeltas.Unlock()


	for _, d := range obj.(Deltas) {
		switch d.Type {
		case Sync, Replaced, Added, Updated:
			s.cacheMutationDetector.AddObject(d.Object)
			if old, exists, err := s.indexer.Get(d.Object); err == nil && exists {
				if err := s.indexer.Update(d.Object); err != nil {
					return err
				}

				isSync := false
				switch {
				case d.Type == Sync:
					isSync = true
				case d.Type == Replaced:
					if accessor, err := meta.Accessor(d.Object); err == nil {
						if oldAccessor, err := meta.Accessor(old); err == nil {
							isSync = accessor.GetResourceVersion() == oldAccessor.GetResourceVersion()
						}
					}
				}
                // 事件的分发
				s.processor.distribute(updateNotification{oldObj: old, newObj: d.Object}, isSync)
			} else {
				if err := s.indexer.Add(d.Object); err != nil {
					return err
				}
                // 事件的分发
				s.processor.distribute(addNotification{newObj: d.Object}, false)
			}
		case Deleted:
			if err := s.indexer.Delete(d.Object); err != nil {
				return err
			}
			s.processor.distribute(deleteNotification{oldObj: d.Object}, false)
		}
	}
	return nil
}

事件处理函数 processor

启动informer时也会启动注册进来的事件处理函数；processor 就是这个事件处理函数。

run() 函数会启动两个 listener，j监听事件处理业务函数 listener.run 和 事件的处理

wg.StartWithChannel(processorStopCh, s.processor.run)

func (p *sharedProcessor) run(stopCh <-chan struct{}) {
	func() {
		p.listenersLock.RLock()
		defer p.listenersLock.RUnlock()
		for _, listener := range p.listeners {
			p.wg.Start(listener.run) 
			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
}

可以看出，就是拿到的事件，根据注册的到informer的事件函数进行处理

func (p *processorListener) run() {
	stopCh := make(chan struct{})
	wait.Until(func() {
		for next := range p.nextCh { // 消费事件
			switch notification := next.(type) {
			case updateNotification:
				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
		close(stopCh)
	}, 1*time.Second, stopCh)
}

informer中的事件的设计

了解了informer如何处理事件，就需要学习下，informer的事件系统设计 prossorListener

事件的添加

当在handleDelta时，会分发具体的事件

// 事件的分发
s.processor.distribute(updateNotification{oldObj: old, newObj: d.Object}, isSync)

此时，事件泵 Pop() 会根据接收到的事件进行处理

// run() 时会启动一个事件泵
p.wg.Start(listener.pop)

func (p *processorListener) pop() {
	defer utilruntime.HandleCrash()
	defer close(p.nextCh) 

	var nextCh chan<- interface{}
	var notification interface{}
	for {
		select {
        case nextCh <- notification: // 这里实际上是一个阻塞的等待
            // 单向channel 可能不会走到这步骤
			var ok bool
            // deltahandle 中 distribute 会将事件添加到addCh待处理事件中
            // 处理完事件会再次拿到一个事件
			notification, ok = p.pendingNotifications.ReadOne()
			if !ok { // Nothing to pop
				nextCh = nil // Disable this select case
			}
        // 处理 分发过来的事件 addCh
		case notificationToAdd, ok := <-p.addCh: // distribute分发的事件
			if !ok {
				return
			}
            // 这里代表第一次，没有任何事件时，或者上面步骤完成读取
			if notification == nil { // 就会走这里
				notification = notificationToAdd 
				nextCh = p.nextCh 
			} else { 
                // notification否则代表没有处理完，将数据再次添加到待处理中
				p.pendingNotifications.WriteOne(notificationToAdd)
			}
		}
	}
}

该消息事件的流程图为

通过一个简单实例来学习client-go中的消息通知机制

package main

import (
	"fmt"
	"time"

	"k8s.io/utils/buffer"
)

var nextCh1 = make(chan interface{})
var addCh = make(chan interface{})
var stopper = make(chan struct{})
var notification interface{}
var pendding = *buffer.NewRingGrowing(2)

func main() {
	// pop
	go func() {
		var nextCh chan<- interface{}
		var notification interface{}
		//var n int
		for {
			fmt.Println("busy wait")
			fmt.Println("entry select", notification)
			select {
			// 初始时，一个未初始化的channel，nil，形成一个阻塞（单channel下是死锁）
			case nextCh <- notification:
				fmt.Println("entry nextCh", notification)
				var ok bool
				// 读不到数据代表已处理完，置空锁
				notification, ok = pendding.ReadOne()
				if !ok {
					fmt.Println("unactive nextch")
					nextCh = nil
				}
			// 事件的分发，监听，初始时也是一个阻塞
			case notificationToAdd, ok := <-addCh:
				fmt.Println(notificationToAdd, notification)
				if !ok {
					return
				}
				// 线程安全
				// 当消息为空时，没有被处理
				// 锁为空，就分发数据
				if notification == nil {
					fmt.Println("frist notification nil")
					notification = notificationToAdd
					nextCh = nextCh1 // 这步骤等于初始化了局部的nextCh，会触发上面的流程
				} else {
					// 在第三次时，会走到这里，数据进入环
					fmt.Println("into ring", notificationToAdd)
					pendding.WriteOne(notificationToAdd)
				}
			}
		}
	}()
	// producer
	go func() {
		i := 0
		for {
			i++
			if i%5 == 0 {
				addCh <- fmt.Sprintf("thread 2 inner -- %d", i)
				time.Sleep(time.Millisecond * 9000)
			} else {
				addCh <- fmt.Sprintf("thread 2 outer -- %d", i)
				time.Sleep(time.Millisecond * 500)
			}
		}
	}()
	// subsriber
	go func() {
		for {
			for next := range nextCh1 {
				time.Sleep(time.Millisecond * 300)
				fmt.Println("consumer", next)
			}
		}
	}()
	<-stopper
}

总结，这里的机制类似于线程安全，进入临界区的一些算法，临界区就是 nextCh，notification 就是保证了至少有一个进程可以进入临界区（要么分发事件，要么生产事件）；nextCh 和 nextCh1 一个是局部管道一个是全局的，管道未初始化代表了死锁（阻塞）；当有消息要处理时，会将局部管道 nextCh 赋值给 全局 nextCh1 此时相当于解除了分发的步骤（对管道赋值，触发分发操作）；ringbuffer 实际上是提供了一个对 notification 加锁的操作，在没有处理的消息时，需要保障 notification 为空，同时也关闭了流程 nextCh 的写入。这里主要是考虑对golang中channel的用法