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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

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