昨天已經看過我們在實務上可能會遇到的需求，利用多個可能重複範圍的配對池，當作匹配搜尋條件，今天讓我們用實作範例來觀察其效果。

角色等級 Overlapping 範例

本範例同樣基於官方 demo，藉由更改範例內容重新 build images 後完成。

Images

• weiweiwesley/open-match:overlapping
• weiweiwesley/mmf:overlapping

Yaml

• open-match/overlapping.yml at overlapping · WeiWeiWesley/open-match

Install

~ kubectl create namespace open-match-demo

~ kubectl apply -n open-match-demo -f ~/open-match/overlapping.yml

Result

Client

隨機產生不同等級條件 tickets，這段跟之前相同不贅述，請參考 client.go#95

Director

這是產生 overlapping MatchProfile 的部分，不同的 MatchProfile，以不同的等級上下限表示不同的配對池。以下這些 MatchProfile 會被 Director 向核心詢問，並且呼叫 MMF 執行配對判斷，你可以把它想成像是不同的階級如：

• 新手場

  req := &pb.FetchMatchesRequest{
  			Config: &pb.FunctionConfig{
  				Host: "om-function.open-match-demo.svc.cluster.local",
  				Port: 50502,
  				Type: pb.FunctionConfig_GRPC,
  			},
  			Profile: &pb.MatchProfile{
  				Name: "MatchProfile1",
  				Pools: []*pb.Pool{
  					{
  						Name: "low level",
  						DoubleRangeFilters: []*pb.DoubleRangeFilter{
  							{
  								DoubleArg: "level",
  								Max:       10,
  								Min:       0,
  							},
  						},
  					},
  				},
  			},
  		}
  

• 中級場

  req := &pb.FetchMatchesRequest{
  			Config: &pb.FunctionConfig{
  				Host: "om-function.open-match-demo.svc.cluster.local",
  				Port: 50502,
  				Type: pb.FunctionConfig_GRPC,
  			},
  			Profile: &pb.MatchProfile{
  				Name: "MatchProfile2",
  				Pools: []*pb.Pool{
  					{
  						Name: "mid level",
  						DoubleRangeFilters: []*pb.DoubleRangeFilter{
  							{
  								DoubleArg: "level",
  								Max:       28,
  								Min:       10,
  							},
  						},
  					},
  				},
  			},
  		}
  

• 高手場

  req := &pb.FetchMatchesRequest{
  			Config: &pb.FunctionConfig{
  				Host: "om-function.open-match-demo.svc.cluster.local",
  				Port: 50502,
  				Type: pb.FunctionConfig_GRPC,
  			},
  			Profile: &pb.MatchProfile{
  				Name: "MatchProfile3",
  				Pools: []*pb.Pool{
  					{
  						Name: "high level",
  						DoubleRangeFilters: []*pb.DoubleRangeFilter{
  							{
  								DoubleArg: "level",
  								Max:       30,
  								Min:       25,
  							},
  						},
  					},
  				},
  			},
  		}
  

MMF

特此告知 makeMatches() 是直接使用 Skill Based Match Function，我只修改 SearchFields “level” 的部分。說明一下程式內容，與官方 demo 不同的地方在於，建立了 computeQuality() 計算出每場配對的等差，並將這項資訊回填於 Match.Extensions["evaluation_input"]，這個資訊會被我們建立的 default Evaluator 所採用，pb.DefaultEvaluationCriteria 內記載的 Score，將用來比較最適合的配對組合。

From: https://gist.github.com/syntxerror/c634dccb96c686b50fee67f801d6e671

func makeMatches(p *pb.MatchProfile, poolTickets map[string][]*pb.Ticket) ([]*pb.Match, error) {
	// Create a colletion to hold match proposals
	var matches []*pb.Match
	count := 0
	for {
		insufficientTickets := false
		// Create a collection to hold tickets selected for a match
		matchTickets := []*pb.Ticket{}
		for pool, tickets := range poolTickets {
			// Set flag if there are not enough tickets to create a match
			if len(tickets) < ticketsPerPoolPerMatch {
				insufficientTickets = true
				break
			}
			// Sort the tickets based on skill
			sort.Slice(tickets, func(i, j int) bool {
				return tickets[i].SearchFields.DoubleArgs["mmr"] < tickets[j].SearchFields.DoubleArgs["mmr"]
			})

			// Remove the Tickets from this pool and add to the match proposal.
			matchTickets = append(matchTickets, tickets[0:ticketsPerPoolPerMatch]...)
			poolTickets[pool] = tickets[ticketsPerPoolPerMatch:]
		}

		if insufficientTickets {
			break
		}
		// Compute the match quality/score
		matchQuality := computeQuality(matchTickets)
		evaluationInput, err := ptypes.MarshalAny(&pb.DefaultEvaluationCriteria{
			Score: matchQuality,
		})

		if err != nil {
			log.Printf("Failed to marshal DefaultEvaluationCriteria, got %s.", err.Error())
			return nil, fmt.Errorf("Failed to marshal DefaultEvaluationCriteria, got %w", err)
		}
		// Output the match quality for our sanity
		log.Printf("Quality for the generated match is %v", matchQuality)
		// Create a match proposal
		matches = append(matches, &pb.Match{
			MatchId:       fmt.Sprintf("profile-%v-time-%v-%v", p.GetName(), time.Now().Format("2006-01-02T15:04:05.00"), count),
			MatchProfile:  p.GetName(),
			MatchFunction: matchName,
			Tickets:       matchTickets,
			Extensions: map[string]*any.Any{
				"evaluation_input": evaluationInput,
			},
		})

		count++
	}

	return matches, nil
}

// Compute the quality as a difference in the highest and lowest player skill levels. This can be used to determine if the match is outside a given skill differential
func computeQuality(tickets []*pb.Ticket) float64 {
	quality := 0.0
	high := 0.0
	low := tickets[0].SearchFields.DoubleArgs["mmr"]
	for _, ticket := range tickets {
		if high < ticket.SearchFields.DoubleArgs["mmr"] {
			high = ticket.SearchFields.DoubleArgs["mmr"]
		}
		if low > ticket.SearchFields.DoubleArgs["mmr"] {
			low = ticket.SearchFields.DoubleArgs["mmr"]
		}
	}
	quality = high - low

	return quality
}

Reference

• https://open-match.dev/site/docs/
• https://jonfoust.medium.com/open-match-writing-a-skill-based-match-function-b2bc8678bd71