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Merge pull request #89459 from chendave/scorer_desc

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Trival fix: update the desc on the score plugins
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Kubernetes Prow Robot 2020-03-26 07:56:39 -07:00 committed by GitHub
commit 894916b665
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2 changed files with 8 additions and 8 deletions
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10
pkg/scheduler/framework/plugins/noderesources/balanced_allocation.go
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@ -56,7 +56,7 @@ func (ba *BalancedAllocation) Score(ctx context.Context, state *framework.CycleS
// It should **NOT** be used alone, and **MUST** be used together
// with NodeResourcesLeastAllocated plugin. It calculates the difference between the cpu and memory fraction
// of capacity, and prioritizes the host based on how close the two metrics are to each other.
// Detail: score = 10 - variance(cpuFraction,memoryFraction,volumeFraction)*10. The algorithm is partly inspired by:
// Detail: score = (1 - variance(cpuFraction,memoryFraction,volumeFraction)) * MaxNodeScore. The algorithm is partly inspired by:
// "Wei Huang et al. An Energy Efficient Virtual Machine Placement Algorithm with Balanced
// Resource Utilization"
return ba.score(pod, nodeInfo)
@ -99,15 +99,15 @@ func balancedResourceScorer(requested, allocable resourceToValueMap, includeVolu
mean := (cpuFraction + memoryFraction + volumeFraction) / float64(3)
variance := float64((((cpuFraction - mean) * (cpuFraction - mean)) + ((memoryFraction - mean) * (memoryFraction - mean)) + ((volumeFraction - mean) * (volumeFraction - mean))) / float64(3))
// Since the variance is between positive fractions, it will be positive fraction. 1-variance lets the
// score to be higher for node which has least variance and multiplying it with 10 provides the scaling
// score to be higher for node which has least variance and multiplying it with `MaxNodeScore` provides the scaling
// factor needed.
return int64((1 - variance) * float64(framework.MaxNodeScore))
}
// Upper and lower boundary of difference between cpuFraction and memoryFraction are -1 and 1
// respectively. Multiplying the absolute value of the difference by 10 scales the value to
// 0-10 with 0 representing well balanced allocation and 10 poorly balanced. Subtracting it from
// 10 leads to the score which also scales from 0 to 10 while 10 representing well balanced.
// respectively. Multiplying the absolute value of the difference by `MaxNodeScore` scales the value to
// 0-MaxNodeScore with 0 representing well balanced allocation and `MaxNodeScore` poorly balanced. Subtracting it from
// `MaxNodeScore` leads to the score which also scales from 0 to `MaxNodeScore` while `MaxNodeScore` representing well balanced.
diff := math.Abs(cpuFraction - memoryFraction)
return int64((1 - diff) * float64(framework.MaxNodeScore))
}

6
pkg/scheduler/framework/plugins/noderesources/least_allocated.go
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@ -53,7 +53,7 @@ func (la *LeastAllocated) Score(ctx context.Context, state *framework.CycleState
// prioritizes based on the minimum of the average of the fraction of requested to capacity.
//
// Details:
// (cpu((capacity-sum(requested))*10/capacity) + memory((capacity-sum(requested))*10/capacity))/2
// (cpu((capacity-sum(requested))*MaxNodeScore/capacity) + memory((capacity-sum(requested))*MaxNodeScore/capacity))/weightSum
return la.score(pod, nodeInfo)
}
@ -84,8 +84,8 @@ func leastResourceScorer(requested, allocable resourceToValueMap, includeVolumes
return nodeScore / weightSum
}
// The unused capacity is calculated on a scale of 0-10
// 0 being the lowest priority and 10 being the highest.
// The unused capacity is calculated on a scale of 0-MaxNodeScore
// 0 being the lowest priority and `MaxNodeScore` being the highest.
// The more unused resources the higher the score is.
func leastRequestedScore(requested, capacity int64) int64 {
if capacity == 0 {