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78 lines
3.7 KiB
Go
78 lines
3.7 KiB
Go
/*
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Copyright 2016 The Kubernetes Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package priorities
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import (
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"math"
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utilfeature "k8s.io/apiserver/pkg/util/feature"
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"k8s.io/kubernetes/pkg/features"
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schedulerapi "k8s.io/kubernetes/pkg/scheduler/api"
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schedulernodeinfo "k8s.io/kubernetes/pkg/scheduler/nodeinfo"
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)
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var (
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balancedResourcePriority = &ResourceAllocationPriority{"BalancedResourceAllocation", balancedResourceScorer}
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// BalancedResourceAllocationMap favors nodes with balanced resource usage rate.
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// BalancedResourceAllocationMap should **NOT** be used alone, and **MUST** be used together
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// with LeastRequestedPriority. It calculates the difference between the cpu and memory fraction
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// of capacity, and prioritizes the host based on how close the two metrics are to each other.
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// Detail: score = 10 - variance(cpuFraction,memoryFraction,volumeFraction)*10. The algorithm is partly inspired by:
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// "Wei Huang et al. An Energy Efficient Virtual Machine Placement Algorithm with Balanced
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// Resource Utilization"
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BalancedResourceAllocationMap = balancedResourcePriority.PriorityMap
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)
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func balancedResourceScorer(requested, allocable *schedulernodeinfo.Resource, includeVolumes bool, requestedVolumes int, allocatableVolumes int) int64 {
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cpuFraction := fractionOfCapacity(requested.MilliCPU, allocable.MilliCPU)
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memoryFraction := fractionOfCapacity(requested.Memory, allocable.Memory)
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// This to find a node which has most balanced CPU, memory and volume usage.
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if includeVolumes && utilfeature.DefaultFeatureGate.Enabled(features.BalanceAttachedNodeVolumes) && allocatableVolumes > 0 {
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volumeFraction := float64(requestedVolumes) / float64(allocatableVolumes)
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if cpuFraction >= 1 || memoryFraction >= 1 || volumeFraction >= 1 {
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// if requested >= capacity, the corresponding host should never be preferred.
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return 0
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}
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// Compute variance for all the three fractions.
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mean := (cpuFraction + memoryFraction + volumeFraction) / float64(3)
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variance := float64((((cpuFraction - mean) * (cpuFraction - mean)) + ((memoryFraction - mean) * (memoryFraction - mean)) + ((volumeFraction - mean) * (volumeFraction - mean))) / float64(3))
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// Since the variance is between positive fractions, it will be positive fraction. 1-variance lets the
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// score to be higher for node which has least variance and multiplying it with 10 provides the scaling
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// factor needed.
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return int64((1 - variance) * float64(schedulerapi.MaxPriority))
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}
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if cpuFraction >= 1 || memoryFraction >= 1 {
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// if requested >= capacity, the corresponding host should never be preferred.
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return 0
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}
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// Upper and lower boundary of difference between cpuFraction and memoryFraction are -1 and 1
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// respectively. Multiplying the absolute value of the difference by 10 scales the value to
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// 0-10 with 0 representing well balanced allocation and 10 poorly balanced. Subtracting it from
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// 10 leads to the score which also scales from 0 to 10 while 10 representing well balanced.
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diff := math.Abs(cpuFraction - memoryFraction)
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return int64((1 - diff) * float64(schedulerapi.MaxPriority))
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}
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func fractionOfCapacity(requested, capacity int64) float64 {
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if capacity == 0 {
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return 1
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}
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return float64(requested) / float64(capacity)
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}
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