Implement resource limit priority function. This function checks if the input pod's

resource limits are satisfied by the input node's allocatable resources or not.
If yes, the node is assigned a score of 1, otherwise the node's score is not changed.

plugin/pkg/scheduler/algorithm/priorities/resource_limits.go

@@ -0,0 +1,128 @@
+/*
+Copyright 2017 The Kubernetes Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+*/
+
+package priorities
+
+import (
+	"fmt"
+
+	"k8s.io/api/core/v1"
+	v1helper "k8s.io/kubernetes/pkg/apis/core/v1/helper"
+	schedulerapi "k8s.io/kubernetes/plugin/pkg/scheduler/api"
+	"k8s.io/kubernetes/plugin/pkg/scheduler/schedulercache"
+
+	"github.com/golang/glog"
+)
+
+// ResourceLimitsPriorityMap is a priority function that increases score of input node by 1 if the node satisfies
+// input pod's resource limits. In detail, this priority function works as follows: If a node does not publish its
+// allocatable resources (cpu and memory both), the node score is not affected. If a pod does not specify
+// its cpu and memory limits both, the node score is not affected. If one or both of cpu and memory limits
+// of the pod are satisfied, the node is assigned a score of 1.
+// Rationale of choosing the lowest score of 1 is that this is mainly selected to break ties between nodes that have
+// same scores assigned by one of least and most requested priority functions.
+func ResourceLimitsPriorityMap(pod *v1.Pod, meta interface{}, nodeInfo *schedulercache.NodeInfo) (schedulerapi.HostPriority, error) {
+	node := nodeInfo.Node()
+	if node == nil {
+		return schedulerapi.HostPriority{}, fmt.Errorf("node not found")
+	}
+
+	allocatableResources := nodeInfo.AllocatableResource()
+
+	// compute pod limits
+	podLimits := getResourceLimits(pod)
+
+	cpuScore := computeScore(podLimits.MilliCPU, allocatableResources.MilliCPU)
+	memScore := computeScore(podLimits.Memory, allocatableResources.Memory)
+
+	score := int(0)
+	if cpuScore == 1 || memScore == 1 {
+		score = 1
+	}
+
+	if glog.V(10) {
+		// We explicitly don't do glog.V(10).Infof() to avoid computing all the parameters if this is
+		// not logged. There is visible performance gain from it.
+		glog.Infof(
+			"%v -> %v: Resource Limits Priority, allocatable %d millicores %d memory bytes, pod limits %d millicores %d memory bytes, score %d",
+			pod.Name, node.Name,
+			allocatableResources.MilliCPU, allocatableResources.Memory,
+			podLimits.MilliCPU, podLimits.Memory,
+			score,
+		)
+	}
+
+	return schedulerapi.HostPriority{
+		Host:  node.Name,
+		Score: score,
+	}, nil
+}
+
+// computeScore return 1 if limit value is less than or equal to allocable
+// value, otherwise it returns 0.
+func computeScore(limit, allocatable int64) int64 {
+	if limit != 0 && allocatable != 0 && limit <= allocatable {
+		return 1
+	}
+	return 0
+}
+
+// getResourceLimits computes resource limits for input pod.
+// The reason to create this new function is to be consistent with other
+// priority functions because most or perhaps all priority functions work
+// with schedulercache.Resource.
+// TODO: cache it as part of metadata passed to priority functions.
+func getResourceLimits(pod *v1.Pod) *schedulercache.Resource {
+	result := &schedulercache.Resource{}
+	for _, container := range pod.Spec.Containers {
+		result.Add(container.Resources.Limits)
+	}
+
+	// take max_resource(sum_pod, any_init_container)
+	for _, container := range pod.Spec.InitContainers {
+		for rName, rQuantity := range container.Resources.Limits {
+			switch rName {
+			case v1.ResourceMemory:
+				if mem := rQuantity.Value(); mem > result.Memory {
+					result.Memory = mem
+				}
+			case v1.ResourceCPU:
+				if cpu := rQuantity.MilliValue(); cpu > result.MilliCPU {
+					result.MilliCPU = cpu
+				}
+				// keeping these resources though score computation in other priority functions and in this
+				// are only computed based on cpu and memory only.
+			case v1.ResourceEphemeralStorage:
+				if ephemeralStorage := rQuantity.Value(); ephemeralStorage > result.EphemeralStorage {
+					result.EphemeralStorage = ephemeralStorage
+				}
+			case v1.ResourceNvidiaGPU:
+				if gpu := rQuantity.Value(); gpu > result.NvidiaGPU {
+					result.NvidiaGPU = gpu
+				}
+			default:
+				if v1helper.IsScalarResourceName(rName) {
+					value := rQuantity.Value()
+					if value > result.ScalarResources[rName] {
+						result.SetScalar(rName, value)
+					}
+				}
+			}
+		}
+	}
+
+	return result
+}