gRPC負載均衡（自定義負載均衡策略）

時間 2020-05-21

原文原文鏈接

前言

上篇文章介紹瞭如何實現gRPC負載均衡，但目前官方只提供了pick_first和round_robin兩種負載均衡策略，輪詢法round_robin不能知足因服務器配置不一樣而承擔不一樣負載量，這篇文章將介紹如何實現自定義負載均衡策略--加權隨機法。node

加權隨機法能夠根據服務器的處理能力而分配不一樣的權重，從而實現處理能力高的服務器可承擔更多的請求，處理能力低的服務器少承擔請求。git

自定義負載均衡策略

gRPC提供了V2PickerBuilder和V2Picker接口讓咱們實現本身的負載均衡策略。github

type V2PickerBuilder interface {
	Build(info PickerBuildInfo) balancer.V2Picker
}

V2PickerBuilder接口：建立V2版本的子鏈接選擇器。服務器

Build方法：返回一個V2選擇器，將用於gRPC選擇子鏈接。app

type V2Picker interface {
	Pick(info PickInfo) (PickResult, error)
}

V2Picker 接口：用於gRPC選擇子鏈接去發送請求。
Pick方法：子鏈接選擇負載均衡

問題來了，咱們須要把服務器地址的權重添加進去，可是地址resolver.Address並無提供權重的屬性。官方給的答覆是：把權重存儲到地址的元數據metadata中。ide

// attributeKey is the type used as the key to store AddrInfo in the Attributes
// field of resolver.Address.
type attributeKey struct{}

// AddrInfo will be stored inside Address metadata in order to use weighted balancer.
type AddrInfo struct {
	Weight int
}

// SetAddrInfo returns a copy of addr in which the Attributes field is updated
// with addrInfo.
func SetAddrInfo(addr resolver.Address, addrInfo AddrInfo) resolver.Address {
	addr.Attributes = attributes.New()
	addr.Attributes = addr.Attributes.WithValues(attributeKey{}, addrInfo)
	return addr
}

// GetAddrInfo returns the AddrInfo stored in the Attributes fields of addr.
func GetAddrInfo(addr resolver.Address) AddrInfo {
	v := addr.Attributes.Value(attributeKey{})
	ai, _ := v.(AddrInfo)
	return ai
}

定義AddrInfo結構體並添加權重Weight屬性，Set方法把Weight存儲到resolver.Address中，Get方法從resolver.Address獲取Weight。ui

解決權重存儲問題後，接下來咱們實現加權隨機法負載均衡策略。code

首先實現V2PickerBuilder接口，返回子鏈接選擇器。server

func (*rrPickerBuilder) Build(info base.PickerBuildInfo) balancer.V2Picker {
	grpclog.Infof("weightPicker: newPicker called with info: %v", info)
	if len(info.ReadySCs) == 0 {
		return base.NewErrPickerV2(balancer.ErrNoSubConnAvailable)
	}
	var scs []balancer.SubConn
	for subConn, addr := range info.ReadySCs {
		node := GetAddrInfo(addr.Address)
		if node.Weight <= 0 {
			node.Weight = minWeight
		} else if node.Weight > 5 {
			node.Weight = maxWeight
		}
		for i := 0; i < node.Weight; i++ {
			scs = append(scs, subConn)
		}
	}
	return &rrPicker{
		subConns: scs,
	}
}

加權隨機法中，我使用空間換時間的方式，把權重轉成地址個數（例如addr1的權重是3，那麼添加3個子鏈接到切片中；addr2權重爲1，則添加1個子鏈接；選擇子鏈接時候，按子鏈接切片長度生成隨機數，以隨機數做爲下標就是選中的子鏈接），避免重複計算權重。考慮到內存佔用，權重定義從1到5權重。

接下來實現子鏈接的選擇，獲取隨機數，選擇子鏈接

type rrPicker struct {
	subConns []balancer.SubConn
	mu sync.Mutex
}

func (p *rrPicker) Pick(balancer.PickInfo) (balancer.PickResult, error) {
	p.mu.Lock()
	index := rand.Intn(len(p.subConns))
	sc := p.subConns[index]
	p.mu.Unlock()
	return balancer.PickResult{SubConn: sc}, nil
}

關鍵代碼完成後，咱們把加權隨機法負載均衡策略命名爲weight，並註冊到gRPC的負載均衡策略中。

// Name is the name of weight balancer.
const Name = "weight"
// NewBuilder creates a new weight balancer builder.
func newBuilder() balancer.Builder {
	return base.NewBalancerBuilderV2(Name, &rrPickerBuilder{}, base.Config{HealthCheck: false})
}

func init() {
	balancer.Register(newBuilder())
}

完整代碼weight.go

最後，咱們只須要在服務端註冊服務時候附帶權重，而後客戶端在服務發現時把權重Set到resolver.Address中，最後客戶端把負載論衡策略改爲weight就完成了。

//SetServiceList 設置服務地址
func (s *ServiceDiscovery) SetServiceList(key, val string) {
	s.lock.Lock()
	defer s.lock.Unlock()
	//獲取服務地址
	addr := resolver.Address{Addr: strings.TrimPrefix(key, s.prefix)}
	//獲取服務地址權重
	nodeWeight, err := strconv.Atoi(val)
	if err != nil {
		//非數字字符默認權重爲1
		nodeWeight = 1
	}
	//把服務地址權重存儲到resolver.Address的元數據中
	addr = weight.SetAddrInfo(addr, weight.AddrInfo{Weight: nodeWeight})
	s.serverList[key] = addr
	s.cc.UpdateState(resolver.State{Addresses: s.getServices()})
	log.Println("put key :", key, "wieght:", val)
}

客戶端使用weight負載均衡策略

func main() {
	r := etcdv3.NewServiceDiscovery(EtcdEndpoints)
	resolver.Register(r)
	// 鏈接服務器
	conn, err := grpc.Dial(
		fmt.Sprintf("%s:///%s", r.Scheme(), SerName),
		grpc.WithBalancerName("weight"),
		grpc.WithInsecure(),
	)
	if err != nil {
		log.Fatalf("net.Connect err: %v", err)
	}
	defer conn.Close()

運行效果：

運行服務1，權重爲1