// CalculateNodeLabelPriority checks whether a particular label exists on a node or not, regardless of its value.
// If presence is true, prioritizes nodes that have the specified label, regardless of value.
// If presence is false, prioritizes nodes that do not have the specified label.
func (n *NodeLabelPrioritizer) CalculateNodeLabelPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
var score int
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
labeledNodes := map[string]bool{}
for _, node := range nodes.Items {
exists := labels.Set(node.Labels).Has(n.label)
labeledNodes[node.Name] = (exists && n.presence) || (!exists && !n.presence)
}
result := []schedulerapi.HostPriority{}
//score int - scale of 0-10
// 0 being the lowest priority and 10 being the highest
for nodeName, success := range labeledNodes {
if success {
score = 10
} else {
score = 0
}
result = append(result, schedulerapi.HostPriority{Host: nodeName, Score: score})
}
return result, nil
}
// ImageLocalityPriority is a priority function that favors nodes that already have requested pod container's images.
// It will detect whether the requested images are present on a node, and then calculate a score ranging from 0 to 10
// based on the total size of those images.
// - If none of the images are present, this node will be given the lowest priority.
// - If some of the images are present on a node, the larger their sizes' sum, the higher the node's priority.
func ImageLocalityPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
sumSizeMap := make(map[string]int64)
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
for _, container := range pod.Spec.Containers {
for _, node := range nodes.Items {
// Check if this container's image is present and get its size.
imageSize := checkContainerImageOnNode(node, container)
// Add this size to the total result of this node.
sumSizeMap[node.Name] += imageSize
}
}
result := []schedulerapi.HostPriority{}
// score int - scale of 0-10
// 0 being the lowest priority and 10 being the highest.
for nodeName, sumSize := range sumSizeMap {
result = append(result, schedulerapi.HostPriority{Host: nodeName,
Score: calculateScoreFromSize(sumSize)})
}
return result, nil
}
// Schedule tries to schedule the given pod to one of node in the node list.
// If it succeeds, it will return the name of the node.
// If it fails, it will return a Fiterror error with reasons.
func (g *genericScheduler) Schedule(pod *api.Pod, nodeLister algorithm.NodeLister) (string, error) {
nodes, err := nodeLister.List()
if err != nil {
return "", err
}
if len(nodes.Items) == 0 {
return "", ErrNoNodesAvailable
}
// Used for all fit and priority funcs.
nodeNameToInfo, err := g.cache.GetNodeNameToInfoMap()
if err != nil {
return "", err
}
filteredNodes, failedPredicateMap, err := findNodesThatFit(pod, nodeNameToInfo, g.predicates, nodes, g.extenders)
if err != nil {
return "", err
}
if len(filteredNodes.Items) == 0 {
return "", &FitError{
Pod: pod,
FailedPredicates: failedPredicateMap,
}
}
priorityList, err := PrioritizeNodes(pod, nodeNameToInfo, g.prioritizers, algorithm.FakeNodeLister(filteredNodes), g.extenders)
if err != nil {
return "", err
}
return g.selectHost(priorityList)
}
func (g *genericScheduler) Schedule(pod *api.Pod, nodeLister algorithm.NodeLister) (string, error) {
nodes, err := nodeLister.List()
if err != nil {
return "", err
}
if len(nodes.Items) == 0 {
return "", ErrNoNodesAvailable
}
filteredNodes, failedPredicateMap, err := findNodesThatFit(pod, g.pods, g.predicates, nodes)
if err != nil {
return "", err
}
priorityList, err := PrioritizeNodes(pod, g.pods, g.prioritizers, algorithm.FakeNodeLister(filteredNodes))
if err != nil {
return "", err
}
if len(priorityList) == 0 {
return "", &FitError{
Pod: pod,
FailedPredicates: failedPredicateMap,
}
}
return g.selectHost(priorityList)
}
func (g *genericScheduler) Schedule(pod *api.Pod, nodeLister algorithm.NodeLister) (string, error) {
nodes, err := nodeLister.List()
if err != nil {
return "", err
}
if len(nodes.Items) == 0 {
return "", ErrNoNodesAvailable
}
// TODO: we should compute this once and dynamically update it using Watch, not constantly re-compute.
// But at least we're now only doing it in one place
machinesToPods, err := predicates.MapPodsToMachines(g.pods)
if err != nil {
return "", err
}
filteredNodes, failedPredicateMap, err := findNodesThatFit(pod, machinesToPods, g.predicates, nodes, g.extenders)
if err != nil {
return "", err
}
priorityList, err := PrioritizeNodes(pod, machinesToPods, g.pods, g.prioritizers, algorithm.FakeNodeLister(filteredNodes), g.extenders)
if err != nil {
return "", err
}
if len(priorityList) == 0 {
return "", &FitError{
Pod: pod,
FailedPredicates: failedPredicateMap,
}
}
return g.selectHost(priorityList)
}
// CalculateNodeAffinityPriority prioritizes nodes according to node affinity scheduling preferences
// indicated in PreferredDuringSchedulingIgnoredDuringExecution. Each time a node match a preferredSchedulingTerm,
// it will a get an add of preferredSchedulingTerm.Weight. Thus, the more preferredSchedulingTerms
// the node satisfies and the more the preferredSchedulingTerm that is satisfied weights, the higher
// score the node gets.
func CalculateNodeAffinityPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
var maxCount float64
counts := make(map[string]float64, len(nodes.Items))
affinity, err := api.GetAffinityFromPodAnnotations(pod.Annotations)
if err != nil {
return nil, err
}
// A nil element of PreferredDuringSchedulingIgnoredDuringExecution matches no objects.
// An element of PreferredDuringSchedulingIgnoredDuringExecution that refers to an
// empty PreferredSchedulingTerm matches all objects.
if affinity.NodeAffinity != nil && affinity.NodeAffinity.PreferredDuringSchedulingIgnoredDuringExecution != nil {
// Match PreferredDuringSchedulingIgnoredDuringExecution term by term.
for _, preferredSchedulingTerm := range affinity.NodeAffinity.PreferredDuringSchedulingIgnoredDuringExecution {
if preferredSchedulingTerm.Weight == 0 {
continue
}
nodeSelector, err := api.NodeSelectorRequirementsAsSelector(preferredSchedulingTerm.Preference.MatchExpressions)
if err != nil {
return nil, err
}
for _, node := range nodes.Items {
if nodeSelector.Matches(labels.Set(node.Labels)) {
counts[node.Name] += float64(preferredSchedulingTerm.Weight)
}
if counts[node.Name] > maxCount {
maxCount = counts[node.Name]
}
}
}
}
result := make(schedulerapi.HostPriorityList, 0, len(nodes.Items))
for i := range nodes.Items {
node := &nodes.Items[i]
if maxCount > 0 {
fScore := 10 * (counts[node.Name] / maxCount)
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: int(fScore)})
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: NodeAffinityPriority, Score: (%d)", pod.Name, node.Name, int(fScore))
}
} else {
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: 0})
}
}
return result, nil
}
// ComputeTaintTolerationPriority prepares the priority list for all the nodes based on the number of intolerable taints on the node
func ComputeTaintTolerationPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
// the max value of counts
var maxCount float64
// counts hold the count of intolerable taints of a pod for a given node
counts := make(map[string]float64, len(nodes))
tolerations, err := api.GetTolerationsFromPodAnnotations(pod.Annotations)
if err != nil {
return nil, err
}
// Fetch a list of all toleration with effect PreferNoSchedule
tolerationList := getAllTolerationPreferNoSchedule(tolerations)
// calculate the intolerable taints for all the nodes
for _, node := range nodes {
taints, err := api.GetTaintsFromNodeAnnotations(node.Annotations)
if err != nil {
return nil, err
}
count := countIntolerableTaintsPreferNoSchedule(taints, tolerationList)
if count > 0 {
// 0 is default value, so avoid unnecessary map operations.
counts[node.Name] = count
if count > maxCount {
maxCount = count
}
}
}
// The maximum priority value to give to a node
// Priority values range from 0 - maxPriority
const maxPriority = float64(10)
result := make(schedulerapi.HostPriorityList, 0, len(nodes))
for _, node := range nodes {
fScore := maxPriority
if maxCount > 0 {
fScore = (1.0 - counts[node.Name]/maxCount) * 10
}
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: Taint Toleration Priority, Score: (%d)", pod.Name, node.Name, int(fScore))
}
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: int(fScore)})
}
return result, nil
}
// CalculateNodeAffinityPriority prioritizes nodes according to node affinity scheduling preferences
// indicated in PreferredDuringSchedulingIgnoredDuringExecution. Each time a node match a preferredSchedulingTerm,
// it will a get an add of preferredSchedulingTerm.Weight. Thus, the more preferredSchedulingTerms
// the node satisfies and the more the preferredSchedulingTerm that is satisfied weights, the higher
// score the node gets.
func (s *NodeAffinity) CalculateNodeAffinityPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
var maxCount int
counts := map[string]int{}
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
affinity, err := api.GetAffinityFromPodAnnotations(pod.Annotations)
if err != nil {
return nil, err
}
// A nil element of PreferredDuringSchedulingIgnoredDuringExecution matches no objects.
// An element of PreferredDuringSchedulingIgnoredDuringExecution that refers to an
// empty PreferredSchedulingTerm matches all objects.
if affinity.NodeAffinity != nil && affinity.NodeAffinity.PreferredDuringSchedulingIgnoredDuringExecution != nil {
// Match PreferredDuringSchedulingIgnoredDuringExecution term by term.
for _, preferredSchedulingTerm := range affinity.NodeAffinity.PreferredDuringSchedulingIgnoredDuringExecution {
if preferredSchedulingTerm.Weight == 0 {
continue
}
nodeSelector, err := api.NodeSelectorRequirementsAsSelector(preferredSchedulingTerm.Preference.MatchExpressions)
if err != nil {
return nil, err
}
for _, node := range nodes.Items {
if nodeSelector.Matches(labels.Set(node.Labels)) {
counts[node.Name] += preferredSchedulingTerm.Weight
}
if counts[node.Name] > maxCount {
maxCount = counts[node.Name]
}
}
}
}
result := []schedulerapi.HostPriority{}
for _, node := range nodes.Items {
fScore := float64(0)
if maxCount > 0 {
fScore = 10 * (float64(counts[node.Name]) / float64(maxCount))
}
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: int(fScore)})
glog.V(10).Infof("%v -> %v: NodeAffinityPriority, Score: (%d)", pod.Name, node.Name, int(fScore))
}
return result, nil
}
// BalancedResourceAllocation favors nodes with balanced resource usage rate.
// BalancedResourceAllocation should **NOT** be used alone, and **MUST** be used together with LeastRequestedPriority.
// It calculates the difference between the cpu and memory fracion of capacity, and prioritizes the host based on how
// close the two metrics are to each other.
// Detail: score = 10 - abs(cpuFraction-memoryFraction)*10. The algorithm is partly inspired by:
// "Wei Huang et al. An Energy Efficient Virtual Machine Placement Algorithm with Balanced Resource Utilization"
func BalancedResourceAllocation(pod *api.Pod, machinesToPods map[string][]*api.Pod, podLister algorithm.PodLister, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return schedulerapi.HostPriorityList{}, err
}
list := schedulerapi.HostPriorityList{}
for _, node := range nodes.Items {
list = append(list, calculateBalancedResourceAllocation(pod, node, machinesToPods[node.Name]))
}
return list, nil
}
// BalancedResourceAllocation favors nodes with balanced resource usage rate.
// BalancedResourceAllocation should **NOT** be used alone, and **MUST** be used together with LeastRequestedPriority.
// It calculates the difference between the cpu and memory fracion of capacity, and prioritizes the host based on how
// close the two metrics are to each other.
// Detail: score = 10 - abs(cpuFraction-memoryFraction)*10. The algorithm is partly inspired by:
// "Wei Huang et al. An Energy Efficient Virtual Machine Placement Algorithm with Balanced Resource Utilization"
func BalancedResourceAllocation(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return schedulerapi.HostPriorityList{}, err
}
list := schedulerapi.HostPriorityList{}
for _, node := range nodes.Items {
list = append(list, calculateBalancedResourceAllocation(pod, node, nodeNameToInfo[node.Name].Pods()))
}
return list, nil
}
// LeastRequestedPriority is a priority function that favors nodes with fewer requested resources.
// It calculates the percentage of memory and CPU requested by pods scheduled on the node, and 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
func LeastRequestedPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return schedulerapi.HostPriorityList{}, err
}
list := schedulerapi.HostPriorityList{}
for _, node := range nodes.Items {
list = append(list, calculateResourceOccupancy(pod, node, nodeNameToInfo[node.Name]))
}
return list, nil
}
// LeastRequestedPriority is a priority function that favors nodes with fewer requested resources.
// It calculates the percentage of memory and CPU requested by pods scheduled on the node, and 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
func LeastRequestedPriority(pod *api.Pod, podLister algorithm.PodLister, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return schedulerapi.HostPriorityList{}, err
}
podsToMachines, err := predicates.MapPodsToMachines(podLister)
list := schedulerapi.HostPriorityList{}
for _, node := range nodes.Items {
list = append(list, calculateResourceOccupancy(pod, node, podsToMachines[node.Name]))
}
return list, nil
}
// BalancedResourceAllocation favors nodes with balanced resource usage rate.
// BalancedResourceAllocation should **NOT** be used alone, and **MUST** be used together with LeastRequestedPriority.
// It calculates the difference between the cpu and memory fracion of capacity, and prioritizes the host based on how
// close the two metrics are to each other.
// Detail: score = 10 - abs(cpuFraction-memoryFraction)*10. The algorithm is partly inspired by:
// "Wei Huang et al. An Energy Efficient Virtual Machine Placement Algorithm with Balanced Resource Utilization"
func BalancedResourceAllocation(pod *api.Pod, podLister algorithm.PodLister, nodeLister algorithm.NodeLister) (algorithm.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return algorithm.HostPriorityList{}, err
}
podsToMachines, err := predicates.MapPodsToMachines(podLister)
list := algorithm.HostPriorityList{}
for _, node := range nodes.Items {
list = append(list, calculateBalancedResourceAllocation(pod, node, podsToMachines[node.Name]))
}
return list, nil
}
// LeastRequestedPriority is a priority function that favors nodes with fewer requested resources.
// It calculates the percentage of memory and CPU requested by pods scheduled on the node, and 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
func LeastRequestedPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return schedulerapi.HostPriorityList{}, err
}
podResources := getNonZeroRequests(pod)
list := make(schedulerapi.HostPriorityList, 0, len(nodes))
for _, node := range nodes {
list = append(list, calculateResourceOccupancy(pod, podResources, node, nodeNameToInfo[node.Name]))
}
return list, nil
}
// ComputeTaintTolerationPriority prepares the priority list for all the nodes based on the number of intolerable taints on the node
func (s *TaintToleration) ComputeTaintTolerationPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
// counts hold the count of intolerable taints of a pod for a given node
counts := make(map[string]int)
// the max value of counts
var maxCount int
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
tolerations, err := api.GetTolerationsFromPodAnnotations(pod.Annotations)
if err != nil {
return nil, err
}
// Fetch a list of all toleration with effect PreferNoSchedule
tolerationList := getAllTolerationPreferNoSchedule(tolerations)
// calculate the intolerable taints for all the nodes
for i := range nodes.Items {
node := &nodes.Items[i]
taints, err := api.GetTaintsFromNodeAnnotations(node.Annotations)
if err != nil {
return nil, err
}
count := countIntolerableTaintsPreferNoSchedule(taints, tolerationList)
counts[node.Name] = count
if count > maxCount {
maxCount = count
}
}
// The maximum priority value to give to a node
// Priority values range from 0 - maxPriority
const maxPriority = 10
result := make(schedulerapi.HostPriorityList, 0, len(nodes.Items))
for _, node := range nodes.Items {
fScore := float64(maxPriority)
if maxCount > 0 {
fScore = (1.0 - float64(counts[node.Name])/float64(maxCount)) * 10
}
glog.V(10).Infof("%v -> %v: Taint Toleration Priority, Score: (%d)", pod.Name, node.Name, int(fScore))
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: int(fScore)})
}
return result, nil
}
// Prioritizes the nodes by running the individual priority functions sequentially.
// Each priority function is expected to set a score of 0-10
// 0 is the lowest priority score (least preferred node) and 10 is the highest
// Each priority function can also have its own weight
// The node scores returned by the priority function are multiplied by the weights to get weighted scores
// All scores are finally combined (added) to get the total weighted scores of all nodes
func PrioritizeNodes(pod *api.Pod, machinesToPods map[string][]*api.Pod, podLister algorithm.PodLister, priorityConfigs []algorithm.PriorityConfig, nodeLister algorithm.NodeLister, extenders []algorithm.SchedulerExtender) (schedulerapi.HostPriorityList, error) {
result := schedulerapi.HostPriorityList{}
// If no priority configs are provided, then the EqualPriority function is applied
// This is required to generate the priority list in the required format
if len(priorityConfigs) == 0 && len(extenders) == 0 {
return EqualPriority(pod, machinesToPods, podLister, nodeLister)
}
combinedScores := map[string]int{}
for _, priorityConfig := range priorityConfigs {
weight := priorityConfig.Weight
// skip the priority function if the weight is specified as 0
if weight == 0 {
continue
}
priorityFunc := priorityConfig.Function
prioritizedList, err := priorityFunc(pod, machinesToPods, podLister, nodeLister)
if err != nil {
return schedulerapi.HostPriorityList{}, err
}
for _, hostEntry := range prioritizedList {
combinedScores[hostEntry.Host] += hostEntry.Score * weight
}
}
if len(extenders) != 0 && nodeLister != nil {
nodes, err := nodeLister.List()
if err != nil {
return schedulerapi.HostPriorityList{}, err
}
for _, extender := range extenders {
prioritizedList, weight, err := extender.Prioritize(pod, &nodes)
if err != nil {
// Prioritization errors from extender can be ignored, let k8s/other extenders determine the priorities
continue
}
for _, hostEntry := range *prioritizedList {
combinedScores[hostEntry.Host] += hostEntry.Score * weight
}
}
}
for host, score := range combinedScores {
glog.V(10).Infof("Host %s Score %d", host, score)
result = append(result, schedulerapi.HostPriority{Host: host, Score: score})
}
return result, nil
}
// EqualPriority is a prioritizer function that gives an equal weight of one to all nodes
func EqualPriority(_ *api.Pod, podLister algorithm.PodLister, nodeLister algorithm.NodeLister) (algorithm.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
glog.Errorf("failed to list nodes: %v", err)
return []algorithm.HostPriority{}, err
}
result := []algorithm.HostPriority{}
for _, node := range nodes.Items {
result = append(result, algorithm.HostPriority{
Host: node.Name,
Score: 1,
})
}
return result, nil
}
func machine2Prioritizer(_ *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return []schedulerapi.HostPriority{}, err
}
result := []schedulerapi.HostPriority{}
for _, node := range nodes.Items {
score := 1
if node.Name == "machine2" {
score = 10
}
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: score})
}
return result, nil
}
// EqualPriority is a prioritizer function that gives an equal weight of one to all nodes
func EqualPriority(_ *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
glog.Errorf("Failed to list nodes: %v", err)
return []schedulerapi.HostPriority{}, err
}
result := []schedulerapi.HostPriority{}
for _, node := range nodes.Items {
result = append(result, schedulerapi.HostPriority{
Host: node.Name,
Score: 1,
})
}
return result, nil
}
// Schedule tries to schedule the given pod to one of node in the node list.
// If it succeeds, it will return the name of the node.
// If it fails, it will return a Fiterror error with reasons.
func (g *genericScheduler) Schedule(pod *api.Pod, nodeLister algorithm.NodeLister) (string, error) {
var trace *util.Trace
if pod != nil {
trace = util.NewTrace(fmt.Sprintf("Scheduling %s/%s", pod.Namespace, pod.Name))
} else {
trace = util.NewTrace("Scheduling <nil> pod")
}
defer trace.LogIfLong(20 * time.Millisecond)
nodes, err := nodeLister.List()
if err != nil {
return "", err
}
if len(nodes) == 0 {
return "", ErrNoNodesAvailable
}
// Used for all fit and priority funcs.
err = g.cache.UpdateNodeNameToInfoMap(g.cachedNodeInfoMap)
if err != nil {
return "", err
}
trace.Step("Computing predicates")
filteredNodes, failedPredicateMap, err := findNodesThatFit(pod, g.cachedNodeInfoMap, nodes, g.predicates, g.extenders)
if err != nil {
return "", err
}
if len(filteredNodes) == 0 {
return "", &FitError{
Pod: pod,
FailedPredicates: failedPredicateMap,
}
}
trace.Step("Prioritizing")
meta := g.priorityMetaProducer(pod)
priorityList, err := PrioritizeNodes(pod, g.cachedNodeInfoMap, meta, g.prioritizers, filteredNodes, g.extenders)
if err != nil {
return "", err
}
trace.Step("Selecting host")
return g.selectHost(priorityList)
}
func numericPriority(pod *api.Pod, podLister algorithm.PodLister, nodeLister algorithm.NodeLister) (algorithm.HostPriorityList, error) {
nodes, err := nodeLister.List()
result := []algorithm.HostPriority{}
if err != nil {
return nil, fmt.Errorf("failed to list nodes: %v", err)
}
for _, node := range nodes.Items {
score, err := strconv.Atoi(node.Name)
if err != nil {
return nil, err
}
result = append(result, algorithm.HostPriority{
Host: node.Name,
Score: score,
})
}
return result, nil
}
func numericPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
result := []schedulerapi.HostPriority{}
if err != nil {
return nil, fmt.Errorf("failed to list nodes: %v", err)
}
for _, node := range nodes.Items {
score, err := strconv.Atoi(node.Name)
if err != nil {
return nil, err
}
result = append(result, schedulerapi.HostPriority{
Host: node.Name,
Score: score,
})
}
return result, nil
}
// compute a sum by iterating through the elements of weightedPodAffinityTerm and adding
// "weight" to the sum if the corresponding PodAffinityTerm is satisfied for
// that node; the node(s) with the highest sum are the most preferred.
// Symmetry need to be considered for preferredDuringSchedulingIgnoredDuringExecution from podAffinity & podAntiAffinity,
// symmetry need to be considered for hard requirements from podAffinity
func (ipa *InterPodAffinity) CalculateInterPodAffinityPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
allPods, err := ipa.podLister.List(labels.Everything())
if err != nil {
return nil, err
}
affinity, err := api.GetAffinityFromPodAnnotations(pod.Annotations)
if err != nil {
return nil, err
}
// convert the topology key based weights to the node name based weights
var maxCount float64
var minCount float64
// counts store the mapping from node name to so-far computed score of
// the node.
counts := make(map[string]float64, len(nodes))
processTerm := func(term *api.PodAffinityTerm, affinityPod, podToCheck *api.Pod, fixedNode *api.Node, weight float64) error {
match, err := podMatchesNamespaceAndSelector(podToCheck, affinityPod, term)
if err != nil {
return err
}
if match {
for _, node := range nodes {
if ipa.failureDomains.NodesHaveSameTopologyKey(node, fixedNode, term.TopologyKey) {
counts[node.Name] += weight
}
}
}
return nil
}
processTerms := func(terms []api.WeightedPodAffinityTerm, affinityPod, podToCheck *api.Pod, fixedNode *api.Node, multiplier int) error {
for _, weightedTerm := range terms {
if err := processTerm(&weightedTerm.PodAffinityTerm, affinityPod, podToCheck, fixedNode, float64(weightedTerm.Weight*multiplier)); err != nil {
return err
}
}
return nil
}
for _, existingPod := range allPods {
existingPodNode, err := ipa.info.GetNodeInfo(existingPod.Spec.NodeName)
if err != nil {
return nil, err
}
existingPodAffinity, err := api.GetAffinityFromPodAnnotations(existingPod.Annotations)
if err != nil {
return nil, err
}
if affinity.PodAffinity != nil {
// For every soft pod affinity term of <pod>, if <existingPod> matches the term,
// increment <counts> for every node in the cluster with the same <term.TopologyKey>
// value as that of <existingPods>`s node by the term`s weight.
terms := affinity.PodAffinity.PreferredDuringSchedulingIgnoredDuringExecution
if err := processTerms(terms, pod, existingPod, existingPodNode, 1); err != nil {
return nil, err
}
}
if affinity.PodAntiAffinity != nil {
// For every soft pod anti-affinity term of <pod>, if <existingPod> matches the term,
// decrement <counts> for every node in the cluster with the same <term.TopologyKey>
// value as that of <existingPod>`s node by the term`s weight.
terms := affinity.PodAntiAffinity.PreferredDuringSchedulingIgnoredDuringExecution
if err := processTerms(terms, pod, existingPod, existingPodNode, -1); err != nil {
return nil, err
}
}
if existingPodAffinity.PodAffinity != nil {
// For every hard pod affinity term of <existingPod>, if <pod> matches the term,
// increment <counts> for every node in the cluster with the same <term.TopologyKey>
// value as that of <existingPod>'s node by the constant <ipa.hardPodAffinityWeight>
if ipa.hardPodAffinityWeight > 0 {
terms := existingPodAffinity.PodAffinity.RequiredDuringSchedulingIgnoredDuringExecution
// TODO: Uncomment this block when implement RequiredDuringSchedulingRequiredDuringExecution.
//if len(existingPodAffinity.PodAffinity.RequiredDuringSchedulingRequiredDuringExecution) != 0 {
// terms = append(terms, existingPodAffinity.PodAffinity.RequiredDuringSchedulingRequiredDuringExecution...)
//}
for _, term := range terms {
if err := processTerm(&term, existingPod, pod, existingPodNode, float64(ipa.hardPodAffinityWeight)); err != nil {
return nil, err
}
}
}
// For every soft pod affinity term of <existingPod>, if <pod> matches the term,
// increment <counts> for every node in the cluster with the same <term.TopologyKey>
// value as that of <existingPod>'s node by the term's weight.
terms := existingPodAffinity.PodAffinity.PreferredDuringSchedulingIgnoredDuringExecution
if err := processTerms(terms, existingPod, pod, existingPodNode, 1); err != nil {
return nil, err
}
}
if existingPodAffinity.PodAntiAffinity != nil {
// For every soft pod anti-affinity term of <existingPod>, if <pod> matches the term,
// decrement <counts> for every node in the cluster with the same <term.TopologyKey>
// value as that of <existingPod>'s node by the term's weight.
terms := existingPodAffinity.PodAntiAffinity.PreferredDuringSchedulingIgnoredDuringExecution
if err := processTerms(terms, existingPod, pod, existingPodNode, -1); err != nil {
return nil, err
}
}
}
for _, node := range nodes {
if counts[node.Name] > maxCount {
maxCount = counts[node.Name]
}
if counts[node.Name] < minCount {
minCount = counts[node.Name]
}
}
// calculate final priority score for each node
result := make(schedulerapi.HostPriorityList, 0, len(nodes))
for _, node := range nodes {
fScore := float64(0)
if (maxCount - minCount) > 0 {
fScore = 10 * ((counts[node.Name] - minCount) / (maxCount - minCount))
}
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: int(fScore)})
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.V(10).Infof("%v -> %v: InterPodAffinityPriority, Score: (%d)", pod.Name, node.Name, int(fScore))
}
}
return result, nil
}
// compute a sum by iterating through the elements of weightedPodAffinityTerm and adding
// "weight" to the sum if the corresponding PodAffinityTerm is satisfied for
// that node; the node(s) with the highest sum are the most preferred.
// Symmetry need to be considered for preferredDuringSchedulingIgnoredDuringExecution from podAffinity & podAntiAffinity,
// symmetry need to be considered for hard requirements from podAffinity
func (ipa *InterPodAffinity) CalculateInterPodAffinityPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
allPods, err := ipa.podLister.List(labels.Everything())
if err != nil {
return nil, err
}
affinity, err := api.GetAffinityFromPodAnnotations(pod.Annotations)
if err != nil {
return nil, err
}
// convert the topology key based weights to the node name based weights
var maxCount int
var minCount int
counts := map[string]int{}
for _, node := range nodes.Items {
totalCount := 0
// count weights for the weighted pod affinity
if affinity.PodAffinity != nil {
for _, weightedTerm := range affinity.PodAffinity.PreferredDuringSchedulingIgnoredDuringExecution {
weightedCount, err := ipa.CountWeightByPodMatchAffinityTerm(pod, allPods, weightedTerm.Weight, weightedTerm.PodAffinityTerm, &node)
if err != nil {
return nil, err
}
totalCount += weightedCount
}
}
// count weights for the weighted pod anti-affinity
if affinity.PodAntiAffinity != nil {
for _, weightedTerm := range affinity.PodAntiAffinity.PreferredDuringSchedulingIgnoredDuringExecution {
weightedCount, err := ipa.CountWeightByPodMatchAffinityTerm(pod, allPods, (0 - weightedTerm.Weight), weightedTerm.PodAffinityTerm, &node)
if err != nil {
return nil, err
}
totalCount += weightedCount
}
}
// reverse direction checking: count weights for the inter-pod affinity/anti-affinity rules
// that are indicated by existing pods on the node.
for _, ep := range allPods {
epAffinity, err := api.GetAffinityFromPodAnnotations(ep.Annotations)
if err != nil {
return nil, err
}
if epAffinity.PodAffinity != nil {
// count the implicit weight for the hard pod affinity indicated by the existing pod.
if ipa.hardPodAffinityWeight > 0 {
var podAffinityTerms []api.PodAffinityTerm
if len(epAffinity.PodAffinity.RequiredDuringSchedulingIgnoredDuringExecution) != 0 {
podAffinityTerms = epAffinity.PodAffinity.RequiredDuringSchedulingIgnoredDuringExecution
}
// TODO: Uncomment this block when implement RequiredDuringSchedulingRequiredDuringExecution.
//if len(affinity.PodAffinity.RequiredDuringSchedulingRequiredDuringExecution) != 0 {
// podAffinityTerms = append(podAffinityTerms, affinity.PodAffinity.RequiredDuringSchedulingRequiredDuringExecution...)
//}
for _, epAffinityTerm := range podAffinityTerms {
match, err := ipa.failureDomains.CheckIfPodMatchPodAffinityTerm(pod, ep, epAffinityTerm,
func(pod *api.Pod) (*api.Node, error) { return &node, nil },
func(ep *api.Pod) (*api.Node, error) { return ipa.info.GetNodeInfo(ep.Spec.NodeName) },
)
if err != nil {
return nil, err
}
if match {
totalCount += ipa.hardPodAffinityWeight
}
}
}
// count weight for the weighted pod affinity indicated by the existing pod.
for _, epWeightedTerm := range epAffinity.PodAffinity.PreferredDuringSchedulingIgnoredDuringExecution {
match, err := ipa.failureDomains.CheckIfPodMatchPodAffinityTerm(pod, ep, epWeightedTerm.PodAffinityTerm,
func(pod *api.Pod) (*api.Node, error) { return &node, nil },
func(ep *api.Pod) (*api.Node, error) { return ipa.info.GetNodeInfo(ep.Spec.NodeName) },
)
if err != nil {
return nil, err
}
if match {
totalCount += epWeightedTerm.Weight
}
}
}
// count weight for the weighted pod anti-affinity indicated by the existing pod.
if epAffinity.PodAntiAffinity != nil {
for _, epWeightedTerm := range epAffinity.PodAntiAffinity.PreferredDuringSchedulingIgnoredDuringExecution {
match, err := ipa.failureDomains.CheckIfPodMatchPodAffinityTerm(pod, ep, epWeightedTerm.PodAffinityTerm,
func(pod *api.Pod) (*api.Node, error) { return &node, nil },
func(ep *api.Pod) (*api.Node, error) { return ipa.info.GetNodeInfo(ep.Spec.NodeName) },
)
if err != nil {
return nil, err
}
if match {
totalCount -= epWeightedTerm.Weight
}
}
}
}
counts[node.Name] = totalCount
if counts[node.Name] > maxCount {
maxCount = counts[node.Name]
}
if counts[node.Name] < minCount {
minCount = counts[node.Name]
}
}
// calculate final priority score for each node
result := []schedulerapi.HostPriority{}
for _, node := range nodes.Items {
fScore := float64(0)
if (maxCount - minCount) > 0 {
fScore = 10 * (float64(counts[node.Name]-minCount) / float64(maxCount-minCount))
}
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: int(fScore)})
glog.V(10).Infof(
"%v -> %v: InterPodAffinityPriority, Score: (%d)", pod.Name, node.Name, int(fScore),
)
}
return result, nil
}
// Prioritizes the nodes by running the individual priority functions in parallel.
// Each priority function is expected to set a score of 0-10
// 0 is the lowest priority score (least preferred node) and 10 is the highest
// Each priority function can also have its own weight
// The node scores returned by the priority function are multiplied by the weights to get weighted scores
// All scores are finally combined (added) to get the total weighted scores of all nodes
func PrioritizeNodes(
pod *api.Pod,
nodeNameToInfo map[string]*schedulercache.NodeInfo,
priorityConfigs []algorithm.PriorityConfig,
nodeLister algorithm.NodeLister,
extenders []algorithm.SchedulerExtender,
) (schedulerapi.HostPriorityList, error) {
result := schedulerapi.HostPriorityList{}
// If no priority configs are provided, then the EqualPriority function is applied
// This is required to generate the priority list in the required format
if len(priorityConfigs) == 0 && len(extenders) == 0 {
return EqualPriority(pod, nodeNameToInfo, nodeLister)
}
var (
mu = sync.Mutex{}
wg = sync.WaitGroup{}
combinedScores = map[string]int{}
errs []error
)
for _, priorityConfig := range priorityConfigs {
// skip the priority function if the weight is specified as 0
if priorityConfig.Weight == 0 {
continue
}
wg.Add(1)
go func(config algorithm.PriorityConfig) {
defer wg.Done()
weight := config.Weight
priorityFunc := config.Function
prioritizedList, err := priorityFunc(pod, nodeNameToInfo, nodeLister)
mu.Lock()
defer mu.Unlock()
if err != nil {
errs = append(errs, err)
return
}
for i := range prioritizedList {
host, score := prioritizedList[i].Host, prioritizedList[i].Score
combinedScores[host] += score * weight
}
}(priorityConfig)
}
if len(errs) != 0 {
return schedulerapi.HostPriorityList{}, errors.NewAggregate(errs)
}
// wait for all go routines to finish
wg.Wait()
if len(extenders) != 0 && nodeLister != nil {
nodes, err := nodeLister.List()
if err != nil {
return schedulerapi.HostPriorityList{}, err
}
for _, extender := range extenders {
wg.Add(1)
go func(ext algorithm.SchedulerExtender) {
defer wg.Done()
prioritizedList, weight, err := ext.Prioritize(pod, &nodes)
if err != nil {
// Prioritization errors from extender can be ignored, let k8s/other extenders determine the priorities
return
}
mu.Lock()
for i := range *prioritizedList {
host, score := (*prioritizedList)[i].Host, (*prioritizedList)[i].Score
combinedScores[host] += score * weight
}
mu.Unlock()
}(extender)
}
}
// wait for all go routines to finish
wg.Wait()
for host, score := range combinedScores {
glog.V(10).Infof("Host %s Score %d", host, score)
result = append(result, schedulerapi.HostPriority{Host: host, Score: score})
}
return result, nil
}
// CalculateSpreadPriority spreads pods across hosts and zones, considering pods belonging to the same service or replication controller.
// When a pod is scheduled, it looks for services or RCs that match the pod, then finds existing pods that match those selectors.
// It favors nodes that have fewer existing matching pods.
// i.e. it pushes the scheduler towards a node where there's the smallest number of
// pods which match the same service selectors or RC selectors as the pod being scheduled.
// Where zone information is included on the nodes, it favors nodes in zones with fewer existing matching pods.
func (s *SelectorSpread) CalculateSpreadPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
selectors := make([]labels.Selector, 0)
services, err := s.serviceLister.GetPodServices(pod)
if err == nil {
for _, service := range services {
selectors = append(selectors, labels.SelectorFromSet(service.Spec.Selector))
}
}
rcs, err := s.controllerLister.GetPodControllers(pod)
if err == nil {
for _, rc := range rcs {
selectors = append(selectors, labels.SelectorFromSet(rc.Spec.Selector))
}
}
rss, err := s.replicaSetLister.GetPodReplicaSets(pod)
if err == nil {
for _, rs := range rss {
if selector, err := unversioned.LabelSelectorAsSelector(rs.Spec.Selector); err == nil {
selectors = append(selectors, selector)
}
}
}
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
// Count similar pods by node
countsByNodeName := map[string]int{}
countsByNodeNameLock := sync.Mutex{}
if len(selectors) > 0 {
// Create a number of go-routines that will be computing number
// of "similar" pods for given nodes.
workers := 16
toProcess := make(chan string, len(nodes.Items))
for i := range nodes.Items {
toProcess <- nodes.Items[i].Name
}
close(toProcess)
wg := sync.WaitGroup{}
wg.Add(workers)
for i := 0; i < workers; i++ {
go func() {
defer utilruntime.HandleCrash()
defer wg.Done()
for {
nodeName, ok := <-toProcess
if !ok {
return
}
count := 0
for _, nodePod := range nodeNameToInfo[nodeName].Pods() {
if pod.Namespace != nodePod.Namespace {
continue
}
// When we are replacing a failed pod, we often see the previous
// deleted version while scheduling the replacement.
// Ignore the previous deleted version for spreading purposes
// (it can still be considered for resource restrictions etc.)
if nodePod.DeletionTimestamp != nil {
glog.V(4).Infof("skipping pending-deleted pod: %s/%s", nodePod.Namespace, nodePod.Name)
continue
}
matches := false
for _, selector := range selectors {
if selector.Matches(labels.Set(nodePod.ObjectMeta.Labels)) {
matches = true
break
}
}
if matches {
count++
}
}
func() {
countsByNodeNameLock.Lock()
defer countsByNodeNameLock.Unlock()
countsByNodeName[nodeName] = count
}()
}
}()
}
wg.Wait()
}
// Aggregate by-node information
// Compute the maximum number of pods hosted on any node
maxCountByNodeName := 0
for _, count := range countsByNodeName {
if count > maxCountByNodeName {
maxCountByNodeName = count
}
}
// Count similar pods by zone, if zone information is present
countsByZone := map[string]int{}
for i := range nodes.Items {
node := &nodes.Items[i]
count, found := countsByNodeName[node.Name]
if !found {
continue
}
zoneId := getZoneKey(node)
if zoneId == "" {
continue
}
countsByZone[zoneId] += count
}
// Aggregate by-zone information
// Compute the maximum number of pods hosted in any zone
haveZones := len(countsByZone) != 0
maxCountByZone := 0
for _, count := range countsByZone {
if count > maxCountByZone {
maxCountByZone = count
}
}
result := []schedulerapi.HostPriority{}
//score int - scale of 0-maxPriority
// 0 being the lowest priority and maxPriority being the highest
for i := range nodes.Items {
node := &nodes.Items[i]
// initializing to the default/max node score of maxPriority
fScore := float32(maxPriority)
if maxCountByNodeName > 0 {
fScore = maxPriority * (float32(maxCountByNodeName-countsByNodeName[node.Name]) / float32(maxCountByNodeName))
}
// If there is zone information present, incorporate it
if haveZones {
zoneId := getZoneKey(node)
if zoneId != "" {
zoneScore := maxPriority * (float32(maxCountByZone-countsByZone[zoneId]) / float32(maxCountByZone))
fScore = (fScore * (1.0 - zoneWeighting)) + (zoneWeighting * zoneScore)
}
}
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: int(fScore)})
glog.V(10).Infof(
"%v -> %v: SelectorSpreadPriority, Score: (%d)", pod.Name, node.Name, int(fScore),
)
}
return result, nil
}
// CalculateSpreadPriority spreads pods by minimizing the number of pods belonging to the same service or replication controller. It counts number of pods that run under
// Services or RCs as the pod being scheduled and tries to minimize the number of conflicts. I.e. pushes scheduler towards a Node where there's a smallest number of
// pods which match the same selectors of Services and RCs as current pod.
func (s *SelectorSpread) CalculateSpreadPriority(pod *api.Pod, podLister algorithm.PodLister, nodeLister algorithm.NodeLister) (algorithm.HostPriorityList, error) {
var maxCount int
var nsPods []*api.Pod
selectors := make([]labels.Selector, 0)
services, err := s.serviceLister.GetPodServices(pod)
if err == nil {
for _, service := range services {
selectors = append(selectors, labels.SelectorFromSet(service.Spec.Selector))
}
}
controllers, err := s.controllerLister.GetPodControllers(pod)
if err == nil {
for _, controller := range controllers {
selectors = append(selectors, labels.SelectorFromSet(controller.Spec.Selector))
}
}
if len(selectors) > 0 {
pods, err := podLister.List(labels.Everything())
if err != nil {
return nil, err
}
// consider only the pods that belong to the same namespace
for _, nsPod := range pods {
if nsPod.Namespace == pod.Namespace {
nsPods = append(nsPods, nsPod)
}
}
}
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
counts := map[string]int{}
if len(nsPods) > 0 {
for _, pod := range nsPods {
matches := false
for _, selector := range selectors {
if selector.Matches(labels.Set(pod.ObjectMeta.Labels)) {
matches = true
break
}
}
if matches {
counts[pod.Spec.NodeName]++
// Compute the maximum number of pods hosted on any node
if counts[pod.Spec.NodeName] > maxCount {
maxCount = counts[pod.Spec.NodeName]
}
}
}
}
result := []algorithm.HostPriority{}
//score int - scale of 0-10
// 0 being the lowest priority and 10 being the highest
for _, node := range nodes.Items {
// initializing to the default/max node score of 10
fScore := float32(10)
if maxCount > 0 {
fScore = 10 * (float32(maxCount-counts[node.Name]) / float32(maxCount))
}
result = append(result, algorithm.HostPriority{Host: node.Name, Score: int(fScore)})
glog.V(10).Infof(
"%v -> %v: SelectorSpreadPriority, Score: (%d)", pod.Name, node.Name, int(fScore),
)
}
return result, nil
}
func (npa *NodePreferAvoidPod) CalculateNodePreferAvoidPodsPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
// TODO: Once we have ownerReference fully implemented, use it to find controller for the pod.
rcs, err := npa.controllerLister.GetPodControllers(pod)
rss, err := npa.replicaSetLister.GetPodReplicaSets(pod)
if len(rcs) == 0 && len(rss) == 0 {
result := make(schedulerapi.HostPriorityList, 0, len(nodes))
for _, node := range nodes {
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: 10})
}
return result, nil
}
avoidNodes := make(map[string]bool, len(nodes))
avoidNode := false
for _, node := range nodes {
avoids, err := api.GetAvoidPodsFromNodeAnnotations(node.Annotations)
if err != nil {
continue
}
avoidNode = false
for i := range avoids.PreferAvoidPods {
avoid := &avoids.PreferAvoidPods[i]
// TODO: Once we have controllerRef implemented there will be at most one owner
// of our pod. That said we won't even need loop theoretically. That said for
// code simplicity, we can get rid of all breaks.
// Also, we can simply compare fields from ownerRef with avoid.
for _, rc := range rcs {
if avoid.PodSignature.PodController.Kind == "ReplicationController" && avoid.PodSignature.PodController.UID == rc.UID {
avoidNode = true
}
}
for _, rs := range rss {
if avoid.PodSignature.PodController.Kind == "ReplicaSet" && avoid.PodSignature.PodController.UID == rs.UID {
avoidNode = true
}
}
if avoidNode {
// false is default value, so we don't even need to set it
// to avoid unnecessary map operations.
avoidNodes[node.Name] = true
break
}
}
}
var score int
result := make(schedulerapi.HostPriorityList, 0, len(nodes))
//score int - scale of 0-10
// 0 being the lowest priority and 10 being the highest
for _, node := range nodes {
if avoidNodes[node.Name] {
score = 0
} else {
score = 10
}
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: score})
}
return result, nil
}
// CalculateSpreadPriority spreads pods across hosts and zones, considering pods belonging to the same service or replication controller.
// When a pod is scheduled, it looks for services or RCs that match the pod, then finds existing pods that match those selectors.
// It favors nodes that have fewer existing matching pods.
// i.e. it pushes the scheduler towards a node where there's the smallest number of
// pods which match the same service selectors or RC selectors as the pod being scheduled.
// Where zone information is included on the nodes, it favors nodes in zones with fewer existing matching pods.
func (s *SelectorSpread) CalculateSpreadPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
var nsPods []*api.Pod
selectors := make([]labels.Selector, 0)
services, err := s.serviceLister.GetPodServices(pod)
if err == nil {
for _, service := range services {
selectors = append(selectors, labels.SelectorFromSet(service.Spec.Selector))
}
}
controllers, err := s.controllerLister.GetPodControllers(pod)
if err == nil {
for _, controller := range controllers {
selectors = append(selectors, labels.SelectorFromSet(controller.Spec.Selector))
}
}
if len(selectors) > 0 {
pods, err := s.podLister.List(labels.Everything())
if err != nil {
return nil, err
}
// consider only the pods that belong to the same namespace
for _, nsPod := range pods {
if nsPod.Namespace == pod.Namespace {
nsPods = append(nsPods, nsPod)
}
}
}
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
// Count similar pods by node
countsByNodeName := map[string]int{}
for _, pod := range nsPods {
// When we are replacing a failed pod, we often see the previous deleted version
// while scheduling the replacement. Ignore the previous deleted version for spreading
// purposes (it can still be considered for resource restrictions etc.)
if pod.DeletionTimestamp != nil {
glog.V(2).Infof("skipping pending-deleted pod: %s/%s", pod.Namespace, pod.Name)
continue
}
matches := false
for _, selector := range selectors {
if selector.Matches(labels.Set(pod.ObjectMeta.Labels)) {
matches = true
break
}
}
if !matches {
continue
}
countsByNodeName[pod.Spec.NodeName]++
}
// Aggregate by-node information
// Compute the maximum number of pods hosted on any node
maxCountByNodeName := 0
for _, count := range countsByNodeName {
if count > maxCountByNodeName {
maxCountByNodeName = count
}
}
// Count similar pods by zone, if zone information is present
countsByZone := map[string]int{}
for i := range nodes.Items {
node := &nodes.Items[i]
count, found := countsByNodeName[node.Name]
if !found {
continue
}
zoneId := getZoneKey(node)
if zoneId == "" {
continue
}
countsByZone[zoneId] += count
}
// Aggregate by-zone information
// Compute the maximum number of pods hosted in any zone
haveZones := len(countsByZone) != 0
maxCountByZone := 0
for _, count := range countsByZone {
if count > maxCountByZone {
maxCountByZone = count
}
}
result := []schedulerapi.HostPriority{}
//score int - scale of 0-maxPriority
// 0 being the lowest priority and maxPriority being the highest
for i := range nodes.Items {
node := &nodes.Items[i]
// initializing to the default/max node score of maxPriority
fScore := float32(maxPriority)
if maxCountByNodeName > 0 {
fScore = maxPriority * (float32(maxCountByNodeName-countsByNodeName[node.Name]) / float32(maxCountByNodeName))
}
// If there is zone information present, incorporate it
if haveZones {
zoneId := getZoneKey(node)
if zoneId != "" {
zoneScore := maxPriority * (float32(maxCountByZone-countsByZone[zoneId]) / float32(maxCountByZone))
fScore = (fScore * (1.0 - zoneWeighting)) + (zoneWeighting * zoneScore)
}
}
result = append(result, schedulerapi.HostPriority{Host: node.Name, Score: int(fScore)})
glog.V(10).Infof(
"%v -> %v: SelectorSpreadPriority, Score: (%d)", pod.Name, node.Name, int(fScore),
)
}
return result, nil
}
// CalculateAntiAffinityPriority spreads pods by minimizing the number of pods belonging to the same service
// on machines with the same value for a particular label.
// The label to be considered is provided to the struct (ServiceAntiAffinity).
func (s *ServiceAntiAffinity) CalculateAntiAffinityPriority(pod *api.Pod, nodeNameToInfo map[string]*schedulercache.NodeInfo, nodeLister algorithm.NodeLister) (schedulerapi.HostPriorityList, error) {
var nsServicePods []*api.Pod
services, err := s.serviceLister.GetPodServices(pod)
if err == nil {
// just use the first service and get the other pods within the service
// TODO: a separate predicate can be created that tries to handle all services for the pod
selector := labels.SelectorFromSet(services[0].Spec.Selector)
pods, err := s.podLister.List(selector)
if err != nil {
return nil, err
}
// consider only the pods that belong to the same namespace
for _, nsPod := range pods {
if nsPod.Namespace == pod.Namespace {
nsServicePods = append(nsServicePods, nsPod)
}
}
}
nodes, err := nodeLister.List()
if err != nil {
return nil, err
}
// separate out the nodes that have the label from the ones that don't
otherNodes := []string{}
labeledNodes := map[string]string{}
for _, node := range nodes.Items {
if labels.Set(node.Labels).Has(s.label) {
label := labels.Set(node.Labels).Get(s.label)
labeledNodes[node.Name] = label
} else {
otherNodes = append(otherNodes, node.Name)
}
}
podCounts := map[string]int{}
for _, pod := range nsServicePods {
label, exists := labeledNodes[pod.Spec.NodeName]
if !exists {
continue
}
podCounts[label]++
}
numServicePods := len(nsServicePods)
result := []schedulerapi.HostPriority{}
//score int - scale of 0-maxPriority
// 0 being the lowest priority and maxPriority being the highest
for node := range labeledNodes {
// initializing to the default/max node score of maxPriority
fScore := float32(maxPriority)
if numServicePods > 0 {
fScore = maxPriority * (float32(numServicePods-podCounts[labeledNodes[node]]) / float32(numServicePods))
}
result = append(result, schedulerapi.HostPriority{Host: node, Score: int(fScore)})
}
// add the open nodes with a score of 0
for _, node := range otherNodes {
result = append(result, schedulerapi.HostPriority{Host: node, Score: 0})
}
return result, nil
}
