647 lines
25 KiB
Go
647 lines
25 KiB
Go
package core
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import (
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"context"
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"fmt"
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"math"
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"sort"
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corev1 "k8s.io/api/core/v1"
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"k8s.io/apimachinery/pkg/util/sets"
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"k8s.io/klog/v2"
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clusterv1alpha1 "github.com/karmada-io/karmada/pkg/apis/cluster/v1alpha1"
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policyv1alpha1 "github.com/karmada-io/karmada/pkg/apis/policy/v1alpha1"
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workv1alpha1 "github.com/karmada-io/karmada/pkg/apis/work/v1alpha1"
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lister "github.com/karmada-io/karmada/pkg/generated/listers/policy/v1alpha1"
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"github.com/karmada-io/karmada/pkg/scheduler/cache"
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"github.com/karmada-io/karmada/pkg/scheduler/framework"
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"github.com/karmada-io/karmada/pkg/scheduler/framework/runtime"
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"github.com/karmada-io/karmada/pkg/util"
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"github.com/karmada-io/karmada/pkg/util/helper"
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)
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// ScheduleAlgorithm is the interface that should be implemented to schedule a resource to the target clusters.
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type ScheduleAlgorithm interface {
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Schedule(context.Context, *policyv1alpha1.Placement, *workv1alpha1.ResourceBindingSpec) (scheduleResult ScheduleResult, err error)
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ScaleSchedule(context.Context, *policyv1alpha1.Placement, *workv1alpha1.ResourceBindingSpec) (scheduleResult ScheduleResult, err error)
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FailoverSchedule(context.Context, *policyv1alpha1.Placement, *workv1alpha1.ResourceBindingSpec) (scheduleResult ScheduleResult, err error)
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}
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// ScheduleResult includes the clusters selected.
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type ScheduleResult struct {
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SuggestedClusters []workv1alpha1.TargetCluster
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}
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type genericScheduler struct {
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schedulerCache cache.Cache
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// TODO: move it into schedulerCache
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policyLister lister.PropagationPolicyLister
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scheduleFramework framework.Framework
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}
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// NewGenericScheduler creates a genericScheduler object.
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func NewGenericScheduler(
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schedCache cache.Cache,
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policyLister lister.PropagationPolicyLister,
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plugins []string,
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) ScheduleAlgorithm {
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return &genericScheduler{
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schedulerCache: schedCache,
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policyLister: policyLister,
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scheduleFramework: runtime.NewFramework(plugins),
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}
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}
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func (g *genericScheduler) Schedule(ctx context.Context, placement *policyv1alpha1.Placement, spec *workv1alpha1.ResourceBindingSpec) (result ScheduleResult, err error) {
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clusterInfoSnapshot := g.schedulerCache.Snapshot()
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if clusterInfoSnapshot.NumOfClusters() == 0 {
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return result, fmt.Errorf("no clusters available to schedule")
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}
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feasibleClusters, err := g.findClustersThatFit(ctx, g.scheduleFramework, placement, &spec.Resource, clusterInfoSnapshot)
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if err != nil {
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return result, fmt.Errorf("failed to findClustersThatFit: %v", err)
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}
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if len(feasibleClusters) == 0 {
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return result, fmt.Errorf("no clusters fit")
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}
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klog.V(4).Infof("feasible clusters found: %v", feasibleClusters)
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clustersScore, err := g.prioritizeClusters(ctx, g.scheduleFramework, placement, feasibleClusters)
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if err != nil {
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return result, fmt.Errorf("failed to prioritizeClusters: %v", err)
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}
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klog.V(4).Infof("feasible clusters scores: %v", clustersScore)
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clusters := g.selectClusters(clustersScore, placement.SpreadConstraints, feasibleClusters)
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clustersWithReplicas, err := g.assignReplicas(clusters, placement.ReplicaScheduling, spec)
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if err != nil {
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return result, fmt.Errorf("failed to assignReplicas: %v", err)
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}
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result.SuggestedClusters = clustersWithReplicas
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return result, nil
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}
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// findClustersThatFit finds the clusters that are fit for the placement based on running the filter plugins.
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func (g *genericScheduler) findClustersThatFit(
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ctx context.Context,
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fwk framework.Framework,
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placement *policyv1alpha1.Placement,
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resource *workv1alpha1.ObjectReference,
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clusterInfo *cache.Snapshot) ([]*clusterv1alpha1.Cluster, error) {
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var out []*clusterv1alpha1.Cluster
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clusters := clusterInfo.GetReadyClusters()
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for _, c := range clusters {
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resMap := fwk.RunFilterPlugins(ctx, placement, resource, c.Cluster())
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res := resMap.Merge()
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if !res.IsSuccess() {
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klog.V(4).Infof("cluster %q is not fit", c.Cluster().Name)
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} else {
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out = append(out, c.Cluster())
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}
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}
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return out, nil
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}
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// prioritizeClusters prioritize the clusters by running the score plugins.
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func (g *genericScheduler) prioritizeClusters(
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ctx context.Context,
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fwk framework.Framework,
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placement *policyv1alpha1.Placement,
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clusters []*clusterv1alpha1.Cluster) (result framework.ClusterScoreList, err error) {
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scoresMap, err := fwk.RunScorePlugins(ctx, placement, clusters)
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if err != nil {
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return result, err
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}
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result = make(framework.ClusterScoreList, len(clusters))
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for i := range clusters {
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result[i] = framework.ClusterScore{Name: clusters[i].Name, Score: 0}
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for j := range scoresMap {
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result[i].Score += scoresMap[j][i].Score
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}
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}
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return result, nil
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}
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func (g *genericScheduler) selectClusters(clustersScore framework.ClusterScoreList, spreadConstraints []policyv1alpha1.SpreadConstraint, clusters []*clusterv1alpha1.Cluster) []*clusterv1alpha1.Cluster {
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if len(spreadConstraints) != 0 {
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return g.matchSpreadConstraints(clusters, spreadConstraints)
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}
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return clusters
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}
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func (g *genericScheduler) matchSpreadConstraints(clusters []*clusterv1alpha1.Cluster, spreadConstraints []policyv1alpha1.SpreadConstraint) []*clusterv1alpha1.Cluster {
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state := util.NewSpreadGroup()
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g.runSpreadConstraintsFilter(clusters, spreadConstraints, state)
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return g.calSpreadResult(state)
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}
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// Now support spread by cluster. More rules will be implemented later.
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func (g *genericScheduler) runSpreadConstraintsFilter(clusters []*clusterv1alpha1.Cluster, spreadConstraints []policyv1alpha1.SpreadConstraint, spreadGroup *util.SpreadGroup) {
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for _, spreadConstraint := range spreadConstraints {
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spreadGroup.InitialGroupRecord(spreadConstraint)
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if spreadConstraint.SpreadByField == policyv1alpha1.SpreadByFieldCluster {
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g.groupByFieldCluster(clusters, spreadConstraint, spreadGroup)
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}
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}
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}
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func (g *genericScheduler) groupByFieldCluster(clusters []*clusterv1alpha1.Cluster, spreadConstraint policyv1alpha1.SpreadConstraint, spreadGroup *util.SpreadGroup) {
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for _, cluster := range clusters {
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clusterGroup := cluster.Name
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spreadGroup.GroupRecord[spreadConstraint][clusterGroup] = append(spreadGroup.GroupRecord[spreadConstraint][clusterGroup], cluster)
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}
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}
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func (g *genericScheduler) calSpreadResult(spreadGroup *util.SpreadGroup) []*clusterv1alpha1.Cluster {
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// TODO: now support single spread constraint
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if len(spreadGroup.GroupRecord) > 1 {
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return nil
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}
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return g.chooseSpreadGroup(spreadGroup)
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}
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func (g *genericScheduler) chooseSpreadGroup(spreadGroup *util.SpreadGroup) []*clusterv1alpha1.Cluster {
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var feasibleClusters []*clusterv1alpha1.Cluster
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for spreadConstraint, clusterGroups := range spreadGroup.GroupRecord {
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if spreadConstraint.SpreadByField == policyv1alpha1.SpreadByFieldCluster {
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if len(clusterGroups) < spreadConstraint.MinGroups {
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return nil
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}
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if len(clusterGroups) <= spreadConstraint.MaxGroups {
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for _, v := range clusterGroups {
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feasibleClusters = append(feasibleClusters, v...)
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}
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break
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}
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if spreadConstraint.MaxGroups > 0 && len(clusterGroups) > spreadConstraint.MaxGroups {
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var groups []string
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for group := range clusterGroups {
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groups = append(groups, group)
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}
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for i := 0; i < spreadConstraint.MaxGroups; i++ {
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feasibleClusters = append(feasibleClusters, clusterGroups[groups[i]]...)
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}
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}
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}
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}
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return feasibleClusters
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}
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func (g *genericScheduler) assignReplicas(clusters []*clusterv1alpha1.Cluster, replicaSchedulingStrategy *policyv1alpha1.ReplicaSchedulingStrategy, object *workv1alpha1.ResourceBindingSpec) ([]workv1alpha1.TargetCluster, error) {
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if len(clusters) == 0 {
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return nil, fmt.Errorf("no clusters available to schedule")
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}
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targetClusters := make([]workv1alpha1.TargetCluster, len(clusters))
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if object.Replicas > 0 && replicaSchedulingStrategy != nil {
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if replicaSchedulingStrategy.ReplicaSchedulingType == policyv1alpha1.ReplicaSchedulingTypeDuplicated {
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for i, cluster := range clusters {
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targetClusters[i] = workv1alpha1.TargetCluster{Name: cluster.Name, Replicas: object.Replicas}
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}
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return targetClusters, nil
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}
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if replicaSchedulingStrategy.ReplicaSchedulingType == policyv1alpha1.ReplicaSchedulingTypeDivided {
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if replicaSchedulingStrategy.ReplicaDivisionPreference == policyv1alpha1.ReplicaDivisionPreferenceWeighted {
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if replicaSchedulingStrategy.WeightPreference == nil {
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// if ReplicaDivisionPreference is set to "Weighted" and WeightPreference is not set, scheduler will weight all clusters the same.
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replicaSchedulingStrategy.WeightPreference = getDefaultWeightPreference(clusters)
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}
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return g.divideReplicasByStaticWeight(clusters, replicaSchedulingStrategy.WeightPreference.StaticWeightList, object.Replicas)
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}
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if replicaSchedulingStrategy.ReplicaDivisionPreference == policyv1alpha1.ReplicaDivisionPreferenceAggregated {
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return g.divideReplicasAggregatedWithResource(clusters, object)
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}
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// will never reach here, only "Aggregated" and "Weighted" are support
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return nil, nil
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}
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}
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for i, cluster := range clusters {
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targetClusters[i] = workv1alpha1.TargetCluster{Name: cluster.Name}
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}
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return targetClusters, nil
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}
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func getDefaultWeightPreference(clusters []*clusterv1alpha1.Cluster) *policyv1alpha1.ClusterPreferences {
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staticWeightLists := make([]policyv1alpha1.StaticClusterWeight, 0)
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for _, cluster := range clusters {
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staticWeightList := policyv1alpha1.StaticClusterWeight{
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TargetCluster: policyv1alpha1.ClusterAffinity{
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ClusterNames: []string{cluster.Name},
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},
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Weight: 1,
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}
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staticWeightLists = append(staticWeightLists, staticWeightList)
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}
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return &policyv1alpha1.ClusterPreferences{
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StaticWeightList: staticWeightLists,
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}
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}
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// divideReplicasByStaticWeight assigns a total number of replicas to the selected clusters by the weight list.
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func (g *genericScheduler) divideReplicasByStaticWeight(clusters []*clusterv1alpha1.Cluster, staticWeightList []policyv1alpha1.StaticClusterWeight, replicas int32) ([]workv1alpha1.TargetCluster, error) {
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weightSum := int64(0)
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matchClusters := make(map[string]int64)
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desireReplicaInfos := make(map[string]int64)
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for _, cluster := range clusters {
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for _, staticWeightRule := range staticWeightList {
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if util.ClusterMatches(cluster, staticWeightRule.TargetCluster) {
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weightSum += staticWeightRule.Weight
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matchClusters[cluster.Name] = staticWeightRule.Weight
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break
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}
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}
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}
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if weightSum == 0 {
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for _, cluster := range clusters {
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weightSum++
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matchClusters[cluster.Name] = 1
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}
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}
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allocatedReplicas := int32(0)
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for clusterName, weight := range matchClusters {
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desireReplicaInfos[clusterName] = weight * int64(replicas) / weightSum
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allocatedReplicas += int32(desireReplicaInfos[clusterName])
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}
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if remainReplicas := replicas - allocatedReplicas; remainReplicas > 0 {
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sortedClusters := helper.SortClusterByWeight(matchClusters)
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for i := 0; remainReplicas > 0; i++ {
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desireReplicaInfos[sortedClusters[i].ClusterName]++
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remainReplicas--
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if i == len(desireReplicaInfos) {
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i = 0
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}
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}
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}
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for _, cluster := range clusters {
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if _, exist := matchClusters[cluster.Name]; !exist {
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desireReplicaInfos[cluster.Name] = 0
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}
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}
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targetClusters := make([]workv1alpha1.TargetCluster, len(desireReplicaInfos))
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i := 0
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for key, value := range desireReplicaInfos {
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targetClusters[i] = workv1alpha1.TargetCluster{Name: key, Replicas: int32(value)}
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i++
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}
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return targetClusters, nil
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}
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// TargetClustersList is a slice of TargetCluster that implements sort.Interface to sort by Value.
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type TargetClustersList []workv1alpha1.TargetCluster
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func (a TargetClustersList) Len() int { return len(a) }
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func (a TargetClustersList) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
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func (a TargetClustersList) Less(i, j int) bool { return a[i].Replicas > a[j].Replicas }
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// divideReplicasAggregatedWithResource assigns a total number of replicas to the selected clusters aggregated according to the resource
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func (g *genericScheduler) divideReplicasAggregatedWithResource(clusters []*clusterv1alpha1.Cluster, spec *workv1alpha1.ResourceBindingSpec,
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preUsedClustersName ...string) ([]workv1alpha1.TargetCluster, error) {
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// preUsedClustersName is used to prioritize the clusters
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for _, value := range spec.ReplicaResourceRequirements {
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if value.Value() > 0 {
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return g.divideReplicasAggregatedWithResourceRequirements(clusters, spec, preUsedClustersName...)
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}
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}
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return g.divideReplicasAggregatedWithoutResourceRequirements(clusters, spec, preUsedClustersName...)
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}
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func (g *genericScheduler) divideReplicasAggregatedWithoutResourceRequirements(clusters []*clusterv1alpha1.Cluster,
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spec *workv1alpha1.ResourceBindingSpec, preUsedClustersName ...string) ([]workv1alpha1.TargetCluster, error) {
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preUsedClusters, unUsedClusters := g.getPreUsed(clusters, preUsedClustersName...)
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clusters = append(preUsedClusters, unUsedClusters...)
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targetClusters := make([]workv1alpha1.TargetCluster, len(clusters))
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for i, clusterInfo := range clusters {
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targetClusters[i] = workv1alpha1.TargetCluster{Name: clusterInfo.Name, Replicas: 0}
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}
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targetClusters[0] = workv1alpha1.TargetCluster{Name: clusters[0].Name, Replicas: spec.Replicas}
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return targetClusters, nil
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}
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func (g *genericScheduler) divideReplicasAggregatedWithResourceRequirements(clusters []*clusterv1alpha1.Cluster,
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spec *workv1alpha1.ResourceBindingSpec, preUsedClustersName ...string) ([]workv1alpha1.TargetCluster, error) {
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// make sure preUsedClusters are in front of the unUsedClusters in the list of clusterAvailableReplicas
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// so that we can assign new replicas to them preferentially when scale up.
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// preUsedClusters have none items during first scheduler
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preUsedClusters, unUsedClusters := g.getPreUsed(clusters, preUsedClustersName...)
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preUsedClustersAvailableReplicas := g.calAvailableReplicas(preUsedClusters, spec.ReplicaResourceRequirements)
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unUsedClustersAvailableReplicas := g.calAvailableReplicas(unUsedClusters, spec.ReplicaResourceRequirements)
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clusterAvailableReplicas := append(preUsedClustersAvailableReplicas, unUsedClustersAvailableReplicas...)
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return g.divideReplicasAggregatedWithClusterReplicas(clusterAvailableReplicas, spec.Replicas)
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}
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func (g *genericScheduler) calAvailableReplicas(clusters []*clusterv1alpha1.Cluster, replicaResourceRequirements corev1.ResourceList) []workv1alpha1.TargetCluster {
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availableTargetClusters := make([]workv1alpha1.TargetCluster, len(clusters))
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for i, cluster := range clusters {
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maxReplicas := g.calClusterAvailableReplicas(cluster, replicaResourceRequirements)
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availableTargetClusters[i] = workv1alpha1.TargetCluster{Name: cluster.Name, Replicas: maxReplicas}
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}
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sort.Sort(TargetClustersList(availableTargetClusters))
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return availableTargetClusters
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}
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// calClusterAvailableReplicas calculates how many replicas can be applied to the target cluster.
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func (g *genericScheduler) calClusterAvailableReplicas(cluster *clusterv1alpha1.Cluster, resourcePerReplicas corev1.ResourceList) int32 {
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var maximumReplicas int64 = math.MaxInt32
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resourceSummary := cluster.Status.ResourceSummary
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for key, value := range resourcePerReplicas {
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requestedQuantity := value.Value()
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if requestedQuantity <= 0 {
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continue
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}
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// calculates available resource quantity
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// available = allocatable - allocated - allocating
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allocatable, ok := resourceSummary.Allocatable[key]
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if !ok {
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return 0
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}
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allocated, ok := resourceSummary.Allocated[key]
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if ok {
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allocatable.Sub(allocated)
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}
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allocating, ok := resourceSummary.Allocating[key]
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if ok {
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allocatable.Sub(allocating)
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}
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availableQuantity := allocatable.Value()
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// short path: no more resource left.
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if availableQuantity <= 0 {
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return 0
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}
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if key == corev1.ResourceCPU {
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requestedQuantity = value.MilliValue()
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availableQuantity = allocatable.MilliValue()
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}
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maximumReplicasForResource := availableQuantity / requestedQuantity
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if maximumReplicasForResource < maximumReplicas {
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maximumReplicas = maximumReplicasForResource
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}
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}
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return int32(maximumReplicas)
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}
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func (g *genericScheduler) divideReplicasAggregatedWithClusterReplicas(clusterAvailableReplicas []workv1alpha1.TargetCluster, replicas int32) ([]workv1alpha1.TargetCluster, error) {
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clustersNum := 0
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clustersMaxReplicas := int32(0)
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for _, clusterInfo := range clusterAvailableReplicas {
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clustersNum++
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clustersMaxReplicas += clusterInfo.Replicas
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if clustersMaxReplicas >= replicas {
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break
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}
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}
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if clustersMaxReplicas < replicas {
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return nil, fmt.Errorf("clusters resources are not enough to schedule, max %v replicas are support", clustersMaxReplicas)
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}
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desireReplicaInfos := make(map[string]int32)
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allocatedReplicas := int32(0)
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for i, clusterInfo := range clusterAvailableReplicas {
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if i >= clustersNum {
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desireReplicaInfos[clusterInfo.Name] = 0
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continue
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}
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desireReplicaInfos[clusterInfo.Name] = clusterInfo.Replicas * replicas / clustersMaxReplicas
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allocatedReplicas += desireReplicaInfos[clusterInfo.Name]
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}
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if remainReplicas := replicas - allocatedReplicas; remainReplicas > 0 {
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for i := 0; remainReplicas > 0; i++ {
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desireReplicaInfos[clusterAvailableReplicas[i].Name]++
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remainReplicas--
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if i == clustersNum {
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i = 0
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}
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}
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}
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targetClusters := make([]workv1alpha1.TargetCluster, len(clusterAvailableReplicas))
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i := 0
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for key, value := range desireReplicaInfos {
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targetClusters[i] = workv1alpha1.TargetCluster{Name: key, Replicas: value}
|
|
i++
|
|
}
|
|
return targetClusters, nil
|
|
}
|
|
|
|
func (g *genericScheduler) ScaleSchedule(ctx context.Context, placement *policyv1alpha1.Placement,
|
|
spec *workv1alpha1.ResourceBindingSpec) (result ScheduleResult, err error) {
|
|
newTargetClusters := make([]workv1alpha1.TargetCluster, len(spec.Clusters))
|
|
|
|
if spec.Replicas > 0 {
|
|
if placement.ReplicaScheduling.ReplicaSchedulingType == policyv1alpha1.ReplicaSchedulingTypeDuplicated {
|
|
for i, cluster := range spec.Clusters {
|
|
newTargetClusters[i] = workv1alpha1.TargetCluster{Name: cluster.Name, Replicas: spec.Replicas}
|
|
}
|
|
result.SuggestedClusters = newTargetClusters
|
|
return result, nil
|
|
}
|
|
if placement.ReplicaScheduling.ReplicaSchedulingType == policyv1alpha1.ReplicaSchedulingTypeDivided {
|
|
if placement.ReplicaScheduling.ReplicaDivisionPreference == policyv1alpha1.ReplicaDivisionPreferenceWeighted {
|
|
preSelectedClusters := g.getPreSelected(spec.Clusters)
|
|
if placement.ReplicaScheduling.WeightPreference == nil {
|
|
// if ReplicaDivisionPreference is set to "Weighted" and WeightPreference is not set, scheduler will weight all clusters the same.
|
|
placement.ReplicaScheduling.WeightPreference = getDefaultWeightPreference(preSelectedClusters)
|
|
}
|
|
clustersWithReplicase, err := g.divideReplicasByStaticWeight(preSelectedClusters, placement.ReplicaScheduling.WeightPreference.StaticWeightList, spec.Replicas)
|
|
if err != nil {
|
|
return result, fmt.Errorf("failed to assignReplicas with Weight: %v", err)
|
|
}
|
|
result.SuggestedClusters = clustersWithReplicase
|
|
return result, nil
|
|
}
|
|
if placement.ReplicaScheduling.ReplicaDivisionPreference == policyv1alpha1.ReplicaDivisionPreferenceAggregated {
|
|
return g.scaleScheduleWithReplicaDivisionPreferenceAggregated(spec)
|
|
}
|
|
|
|
// will never reach here, only "Aggregated" and "Weighted" are support
|
|
return result, nil
|
|
}
|
|
}
|
|
|
|
for i, cluster := range spec.Clusters {
|
|
newTargetClusters[i] = workv1alpha1.TargetCluster{Name: cluster.Name}
|
|
}
|
|
result.SuggestedClusters = newTargetClusters
|
|
return result, nil
|
|
}
|
|
|
|
func (g *genericScheduler) scaleScheduleWithReplicaDivisionPreferenceAggregated(spec *workv1alpha1.ResourceBindingSpec) (result ScheduleResult, err error) {
|
|
assignedReplicas := util.GetSumOfReplicas(spec.Clusters)
|
|
if assignedReplicas > spec.Replicas {
|
|
newTargetClusters, err := g.scaleDownScheduleWithReplicaDivisionPreferenceAggregated(spec)
|
|
if err != nil {
|
|
return result, fmt.Errorf("failed to scaleDown: %v", err)
|
|
}
|
|
result.SuggestedClusters = newTargetClusters
|
|
} else if assignedReplicas < spec.Replicas {
|
|
newTargetClusters, err := g.scaleUpScheduleWithReplicaDivisionPreferenceAggregated(spec)
|
|
if err != nil {
|
|
return result, fmt.Errorf("failed to scaleUp: %v", err)
|
|
}
|
|
result.SuggestedClusters = newTargetClusters
|
|
} else {
|
|
result.SuggestedClusters = spec.Clusters
|
|
}
|
|
return result, nil
|
|
}
|
|
|
|
func (g *genericScheduler) scaleDownScheduleWithReplicaDivisionPreferenceAggregated(spec *workv1alpha1.ResourceBindingSpec) ([]workv1alpha1.TargetCluster, error) {
|
|
return g.divideReplicasAggregatedWithClusterReplicas(spec.Clusters, spec.Replicas)
|
|
}
|
|
|
|
func (g *genericScheduler) scaleUpScheduleWithReplicaDivisionPreferenceAggregated(spec *workv1alpha1.ResourceBindingSpec) ([]workv1alpha1.TargetCluster, error) {
|
|
// find the clusters that have old replicas so we can assign new replicas to them preferentially
|
|
// targetMap map of the result for the old replicas so that it can be merged with the new result easily
|
|
targetMap := make(map[string]int32)
|
|
usedTargetClusters := make([]string, 0)
|
|
assignedReplicas := int32(0)
|
|
for _, cluster := range spec.Clusters {
|
|
targetMap[cluster.Name] = cluster.Replicas
|
|
assignedReplicas += cluster.Replicas
|
|
if cluster.Replicas > 0 {
|
|
usedTargetClusters = append(usedTargetClusters, cluster.Name)
|
|
}
|
|
}
|
|
preSelected := g.getPreSelected(spec.Clusters)
|
|
// only the new replicas are considered during this scheduler, the old replicas will not be moved.
|
|
// if not the old replicas may be recreated which is not expected during scaling up
|
|
// use usedTargetClusters to make sure that we assign new replicas to them preferentially so that all the replicas are aggregated
|
|
newObject := spec.DeepCopy()
|
|
newObject.Replicas = spec.Replicas - assignedReplicas
|
|
result, err := g.divideReplicasAggregatedWithResource(preSelected, newObject, usedTargetClusters...)
|
|
if err != nil {
|
|
return result, err
|
|
}
|
|
// merge the result of this scheduler for new replicas and the data of old replicas
|
|
for i, cluster := range result {
|
|
value, ok := targetMap[cluster.Name]
|
|
if ok {
|
|
result[i].Replicas = cluster.Replicas + value
|
|
delete(targetMap, cluster.Name)
|
|
}
|
|
}
|
|
for key, value := range targetMap {
|
|
result = append(result, workv1alpha1.TargetCluster{Name: key, Replicas: value})
|
|
}
|
|
return result, nil
|
|
}
|
|
|
|
func (g *genericScheduler) getPreSelected(targetClusters []workv1alpha1.TargetCluster) []*clusterv1alpha1.Cluster {
|
|
var preSelectedClusters []*clusterv1alpha1.Cluster
|
|
clusterInfoSnapshot := g.schedulerCache.Snapshot()
|
|
for _, targetCluster := range targetClusters {
|
|
for _, cluster := range clusterInfoSnapshot.GetClusters() {
|
|
if targetCluster.Name == cluster.Cluster().Name {
|
|
preSelectedClusters = append(preSelectedClusters, cluster.Cluster())
|
|
break
|
|
}
|
|
}
|
|
}
|
|
return preSelectedClusters
|
|
}
|
|
|
|
func (g *genericScheduler) getPreUsed(clusters []*clusterv1alpha1.Cluster, preUsedClustersName ...string) ([]*clusterv1alpha1.Cluster, []*clusterv1alpha1.Cluster) {
|
|
if len(preUsedClustersName) == 0 {
|
|
return clusters, nil
|
|
}
|
|
preUsedClusterSet := sets.NewString(preUsedClustersName...)
|
|
var preUsedCluster []*clusterv1alpha1.Cluster
|
|
var unUsedCluster []*clusterv1alpha1.Cluster
|
|
for i := range clusters {
|
|
if preUsedClusterSet.Has(clusters[i].Name) {
|
|
preUsedCluster = append(preUsedCluster, clusters[i])
|
|
} else {
|
|
unUsedCluster = append(unUsedCluster, clusters[i])
|
|
}
|
|
}
|
|
return preUsedCluster, unUsedCluster
|
|
}
|
|
|
|
func (g *genericScheduler) FailoverSchedule(ctx context.Context, placement *policyv1alpha1.Placement,
|
|
spec *workv1alpha1.ResourceBindingSpec) (result ScheduleResult, err error) {
|
|
readyClusters := g.schedulerCache.Snapshot().GetReadyClusterNames()
|
|
totalClusters := util.ConvertToClusterNames(spec.Clusters)
|
|
|
|
reservedClusters := calcReservedCluster(totalClusters, readyClusters)
|
|
availableClusters := calcAvailableCluster(totalClusters, readyClusters)
|
|
|
|
candidateClusters := sets.NewString()
|
|
for clusterName := range availableClusters {
|
|
clusterObj := g.schedulerCache.Snapshot().GetCluster(clusterName)
|
|
if clusterObj == nil {
|
|
return result, fmt.Errorf("failed to get clusterObj by clusterName: %s", clusterName)
|
|
}
|
|
|
|
resMap := g.scheduleFramework.RunFilterPlugins(ctx, placement, &spec.Resource, clusterObj.Cluster())
|
|
res := resMap.Merge()
|
|
if !res.IsSuccess() {
|
|
klog.V(4).Infof("cluster %q is not fit", clusterName)
|
|
} else {
|
|
candidateClusters.Insert(clusterName)
|
|
}
|
|
}
|
|
|
|
klog.V(4).Infof("Reserved bindingClusters : %v", reservedClusters.List())
|
|
klog.V(4).Infof("Candidate bindingClusters: %v", candidateClusters.List())
|
|
|
|
// TODO: should schedule as much as possible?
|
|
deltaLen := len(spec.Clusters) - len(reservedClusters)
|
|
if len(candidateClusters) < deltaLen {
|
|
// for ReplicaSchedulingTypeDivided, we will try to migrate replicas to the other health clusters
|
|
if placement.ReplicaScheduling == nil || placement.ReplicaScheduling.ReplicaSchedulingType == policyv1alpha1.ReplicaSchedulingTypeDuplicated {
|
|
klog.Warningf("ignore reschedule binding as insufficient available cluster")
|
|
return ScheduleResult{}, nil
|
|
}
|
|
}
|
|
|
|
// TODO: check if the final result meets the spread constraints.
|
|
targetClusters := reservedClusters
|
|
clusterList := candidateClusters.List()
|
|
for i := 0; i < deltaLen && i < len(candidateClusters); i++ {
|
|
targetClusters.Insert(clusterList[i])
|
|
}
|
|
|
|
var reScheduleResult []workv1alpha1.TargetCluster
|
|
for cluster := range targetClusters {
|
|
reScheduleResult = append(reScheduleResult, workv1alpha1.TargetCluster{Name: cluster})
|
|
}
|
|
|
|
return ScheduleResult{reScheduleResult}, nil
|
|
}
|
|
|
|
// calcReservedCluster eliminates the not-ready clusters from the 'bindClusters'.
|
|
func calcReservedCluster(bindClusters, readyClusters sets.String) sets.String {
|
|
return bindClusters.Difference(bindClusters.Difference(readyClusters))
|
|
}
|
|
|
|
// calcAvailableCluster returns a list of ready clusters that not in 'bindClusters'.
|
|
func calcAvailableCluster(bindCluster, readyClusters sets.String) sets.String {
|
|
return readyClusters.Difference(bindCluster)
|
|
}
|