// Copyright (c) HashiCorp, Inc. // SPDX-License-Identifier: MPL-2.0 package scheduler import ( "math" "time" "github.com/hashicorp/nomad/nomad/structs" ) const ( // skipScoreThreshold is a threshold used in the limit iterator to skip nodes // that have a score lower than this. -1 is the lowest possible score for a // node with penalties (based on job anti affinity and node rescheduling penalties skipScoreThreshold = 0.0 // maxSkip limits the number of nodes that can be skipped in the limit iterator maxSkip = 3 ) // Stack is a chained collection of iterators. The stack is used to // make placement decisions. Different schedulers may customize the // stack they use to vary the way placements are made. type Stack interface { // SetNodes is used to set the base set of potential nodes SetNodes([]*structs.Node) // SetTaskGroup is used to set the job for selection SetJob(job *structs.Job) // Select is used to select a node for the task group Select(tg *structs.TaskGroup, options *SelectOptions) *RankedNode } type SelectOptions struct { PenaltyNodeIDs map[string]struct{} PreferredNodes []*structs.Node Preempt bool AllocName string } // GenericStack is the Stack used for the Generic scheduler. It is // designed to make better placement decisions at the cost of performance. type GenericStack struct { batch bool ctx Context source *StaticIterator wrappedChecks *FeasibilityWrapper quota FeasibleIterator jobVersion *uint64 jobConstraint *ConstraintChecker taskGroupDrivers *DriverChecker taskGroupConstraint *ConstraintChecker taskGroupDevices *DeviceChecker taskGroupHostVolumes *HostVolumeChecker taskGroupCSIVolumes *CSIVolumeChecker taskGroupNetwork *NetworkChecker distinctHostsConstraint *DistinctHostsIterator distinctPropertyConstraint *DistinctPropertyIterator binPack *BinPackIterator jobAntiAff *JobAntiAffinityIterator nodeReschedulingPenalty *NodeReschedulingPenaltyIterator limit *LimitIterator maxScore *MaxScoreIterator nodeAffinity *NodeAffinityIterator spread *SpreadIterator scoreNorm *ScoreNormalizationIterator } func (s *GenericStack) SetNodes(baseNodes []*structs.Node) { // Shuffle base nodes idx, _ := s.ctx.State().LatestIndex() shuffleNodes(s.ctx.Plan(), idx, baseNodes) // Update the set of base nodes s.source.SetNodes(baseNodes) // Apply a limit function. This is to avoid scanning *every* possible node. // For batch jobs we only need to evaluate 2 options and depend on the // power of two choices. For services jobs we need to visit "enough". // Using a log of the total number of nodes is a good restriction, with // at least 2 as the floor limit := 2 if n := len(baseNodes); !s.batch && n > 0 { logLimit := int(math.Ceil(math.Log2(float64(n)))) if logLimit > limit { limit = logLimit } } s.limit.SetLimit(limit) } func (s *GenericStack) SetJob(job *structs.Job) { if s.jobVersion != nil && *s.jobVersion == job.Version { return } jobVer := job.Version s.jobVersion = &jobVer s.jobConstraint.SetConstraints(job.Constraints) s.distinctHostsConstraint.SetJob(job) s.distinctPropertyConstraint.SetJob(job) s.binPack.SetJob(job) s.jobAntiAff.SetJob(job) s.nodeAffinity.SetJob(job) s.spread.SetJob(job) s.ctx.Eligibility().SetJob(job) s.taskGroupCSIVolumes.SetNamespace(job.Namespace) s.taskGroupCSIVolumes.SetJobID(job.ID) if contextual, ok := s.quota.(ContextualIterator); ok { contextual.SetJob(job) } } // SetSchedulerConfiguration applies the given scheduler configuration to // process nodes. Scheduler configuration values may change per job depending // on the node pool being used. func (s *GenericStack) SetSchedulerConfiguration(schedConfig *structs.SchedulerConfiguration) { s.binPack.SetSchedulerConfiguration(schedConfig) } func (s *GenericStack) Select(tg *structs.TaskGroup, options *SelectOptions) *RankedNode { // This block handles trying to select from preferred nodes if options specify them // It also sets back the set of nodes to the original nodes if options != nil && len(options.PreferredNodes) > 0 { originalNodes := s.source.nodes s.source.SetNodes(options.PreferredNodes) optionsNew := *options optionsNew.PreferredNodes = nil if option := s.Select(tg, &optionsNew); option != nil { s.source.SetNodes(originalNodes) return option } s.source.SetNodes(originalNodes) return s.Select(tg, &optionsNew) } // Reset the max selector and context s.maxScore.Reset() s.ctx.Reset() start := time.Now() // Get the task groups constraints. tgConstr := taskGroupConstraints(tg) // Update the parameters of iterators s.taskGroupDrivers.SetDrivers(tgConstr.drivers) s.taskGroupConstraint.SetConstraints(tgConstr.constraints) s.taskGroupDevices.SetTaskGroup(tg) s.taskGroupHostVolumes.SetVolumes(options.AllocName, tg.Volumes) s.taskGroupCSIVolumes.SetVolumes(options.AllocName, tg.Volumes) if len(tg.Networks) > 0 { s.taskGroupNetwork.SetNetwork(tg.Networks[0]) } s.distinctHostsConstraint.SetTaskGroup(tg) s.distinctPropertyConstraint.SetTaskGroup(tg) s.wrappedChecks.SetTaskGroup(tg.Name) s.binPack.SetTaskGroup(tg) if options != nil { s.binPack.evict = options.Preempt } s.jobAntiAff.SetTaskGroup(tg) if options != nil { s.nodeReschedulingPenalty.SetPenaltyNodes(options.PenaltyNodeIDs) } s.nodeAffinity.SetTaskGroup(tg) s.spread.SetTaskGroup(tg) if s.nodeAffinity.hasAffinities() || s.spread.hasSpreads() { // scoring spread across all nodes has quadratic behavior, so // we need to consider a subset of nodes to keep evaluaton times // reasonable but enough to ensure spread is correct. this // value was empirically determined. s.limit.SetLimit(tg.Count) if tg.Count < 100 { s.limit.SetLimit(100) } } if contextual, ok := s.quota.(ContextualIterator); ok { contextual.SetTaskGroup(tg) } // Find the node with the max score option := s.maxScore.Next() // Store the compute time s.ctx.Metrics().AllocationTime = time.Since(start) return option } // SystemStack is the Stack used for the System scheduler. It is designed to // attempt to make placements on all nodes. type SystemStack struct { ctx Context source *StaticIterator wrappedChecks *FeasibilityWrapper quota FeasibleIterator jobConstraint *ConstraintChecker taskGroupDrivers *DriverChecker taskGroupConstraint *ConstraintChecker taskGroupDevices *DeviceChecker taskGroupHostVolumes *HostVolumeChecker taskGroupCSIVolumes *CSIVolumeChecker taskGroupNetwork *NetworkChecker distinctPropertyConstraint *DistinctPropertyIterator binPack *BinPackIterator scoreNorm *ScoreNormalizationIterator } // NewSystemStack constructs a stack used for selecting system and sysbatch // job placements. // // sysbatch is used to determine which scheduler config option is used to // control the use of preemption. func NewSystemStack(sysbatch bool, ctx Context) *SystemStack { // Create a new stack s := &SystemStack{ctx: ctx} // Create the source iterator. We visit nodes in a linear order because we // have to evaluate on all nodes. s.source = NewStaticIterator(ctx, nil) // Attach the job constraints. The job is filled in later. s.jobConstraint = NewConstraintChecker(ctx, nil) // Filter on task group drivers first as they are faster s.taskGroupDrivers = NewDriverChecker(ctx, nil) // Filter on task group constraints second s.taskGroupConstraint = NewConstraintChecker(ctx, nil) // Filter on task group host volumes s.taskGroupHostVolumes = NewHostVolumeChecker(ctx) // Filter on available, healthy CSI plugins s.taskGroupCSIVolumes = NewCSIVolumeChecker(ctx) // Filter on task group devices s.taskGroupDevices = NewDeviceChecker(ctx) // Filter on available client networks s.taskGroupNetwork = NewNetworkChecker(ctx) // Create the feasibility wrapper which wraps all feasibility checks in // which feasibility checking can be skipped if the computed node class has // previously been marked as eligible or ineligible. Generally this will be // checks that only needs to examine the single node to determine feasibility. jobs := []FeasibilityChecker{s.jobConstraint} tgs := []FeasibilityChecker{ s.taskGroupDrivers, s.taskGroupConstraint, s.taskGroupDevices, s.taskGroupNetwork, } avail := []FeasibilityChecker{ s.taskGroupHostVolumes, s.taskGroupCSIVolumes, } s.wrappedChecks = NewFeasibilityWrapper(ctx, s.source, jobs, tgs, avail) // Filter on distinct property constraints. s.distinctPropertyConstraint = NewDistinctPropertyIterator(ctx, s.wrappedChecks) // Create the quota iterator to determine if placements would result in // the quota attached to the namespace of the job to go over. // Note: the quota iterator must be the last feasibility iterator before // we upgrade to ranking, or our quota usage will include ineligible // nodes! s.quota = NewQuotaIterator(ctx, s.distinctPropertyConstraint) // Upgrade from feasible to rank iterator rankSource := NewFeasibleRankIterator(ctx, s.quota) // Apply the bin packing, this depends on the resources needed // by a particular task group. Enable eviction as system jobs are high // priority. // // The scheduler configuration is read directly from state but only // values that can't be specified per node pool should be used. Other // values must be merged by calling schedConfig.WithNodePool() and set in // the stack by calling SetSchedulerConfiguration(). _, schedConfig, _ := s.ctx.State().SchedulerConfig() enablePreemption := true if schedConfig != nil { if sysbatch { enablePreemption = schedConfig.PreemptionConfig.SysBatchSchedulerEnabled } else { enablePreemption = schedConfig.PreemptionConfig.SystemSchedulerEnabled } } // Create binpack iterator s.binPack = NewBinPackIterator(ctx, rankSource, enablePreemption, 0) // Apply score normalization s.scoreNorm = NewScoreNormalizationIterator(ctx, s.binPack) return s } func (s *SystemStack) SetNodes(baseNodes []*structs.Node) { // Update the set of base nodes s.source.SetNodes(baseNodes) } func (s *SystemStack) SetJob(job *structs.Job) { s.jobConstraint.SetConstraints(job.Constraints) s.distinctPropertyConstraint.SetJob(job) s.binPack.SetJob(job) s.ctx.Eligibility().SetJob(job) s.taskGroupCSIVolumes.SetNamespace(job.Namespace) s.taskGroupCSIVolumes.SetJobID(job.ID) if contextual, ok := s.quota.(ContextualIterator); ok { contextual.SetJob(job) } } // SetSchedulerConfiguration applies the given scheduler configuration to // process nodes. Scheduler configuration values may change per job depending // on the node pool being used. func (s *SystemStack) SetSchedulerConfiguration(schedConfig *structs.SchedulerConfiguration) { s.binPack.SetSchedulerConfiguration(schedConfig) } func (s *SystemStack) Select(tg *structs.TaskGroup, options *SelectOptions) *RankedNode { // Reset the binpack selector and context s.scoreNorm.Reset() s.ctx.Reset() start := time.Now() // Get the task groups constraints. tgConstr := taskGroupConstraints(tg) // Update the parameters of iterators s.taskGroupDrivers.SetDrivers(tgConstr.drivers) s.taskGroupConstraint.SetConstraints(tgConstr.constraints) s.taskGroupDevices.SetTaskGroup(tg) s.taskGroupHostVolumes.SetVolumes(options.AllocName, tg.Volumes) s.taskGroupCSIVolumes.SetVolumes(options.AllocName, tg.Volumes) if len(tg.Networks) > 0 { s.taskGroupNetwork.SetNetwork(tg.Networks[0]) } s.wrappedChecks.SetTaskGroup(tg.Name) s.distinctPropertyConstraint.SetTaskGroup(tg) s.binPack.SetTaskGroup(tg) if contextual, ok := s.quota.(ContextualIterator); ok { contextual.SetTaskGroup(tg) } // Get the next option that satisfies the constraints. option := s.scoreNorm.Next() // Store the compute time s.ctx.Metrics().AllocationTime = time.Since(start) return option } // NewGenericStack constructs a stack used for selecting service placements func NewGenericStack(batch bool, ctx Context) *GenericStack { // Create a new stack s := &GenericStack{ batch: batch, ctx: ctx, } // Create the source iterator. We randomize the order we visit nodes // to reduce collisions between schedulers and to do a basic load // balancing across eligible nodes. s.source = NewRandomIterator(ctx, nil) // Attach the job constraints. The job is filled in later. s.jobConstraint = NewConstraintChecker(ctx, nil) // Filter on task group drivers first as they are faster s.taskGroupDrivers = NewDriverChecker(ctx, nil) // Filter on task group constraints second s.taskGroupConstraint = NewConstraintChecker(ctx, nil) // Filter on task group devices s.taskGroupDevices = NewDeviceChecker(ctx) // Filter on task group host volumes s.taskGroupHostVolumes = NewHostVolumeChecker(ctx) // Filter on available, healthy CSI plugins s.taskGroupCSIVolumes = NewCSIVolumeChecker(ctx) // Filter on available client networks s.taskGroupNetwork = NewNetworkChecker(ctx) // Create the feasibility wrapper which wraps all feasibility checks in // which feasibility checking can be skipped if the computed node class has // previously been marked as eligible or ineligible. Generally this will be // checks that only needs to examine the single node to determine feasibility. jobs := []FeasibilityChecker{s.jobConstraint} tgs := []FeasibilityChecker{ s.taskGroupDrivers, s.taskGroupConstraint, s.taskGroupDevices, s.taskGroupNetwork, } avail := []FeasibilityChecker{ s.taskGroupHostVolumes, s.taskGroupCSIVolumes, } s.wrappedChecks = NewFeasibilityWrapper(ctx, s.source, jobs, tgs, avail) // Filter on distinct host constraints. s.distinctHostsConstraint = NewDistinctHostsIterator(ctx, s.wrappedChecks) // Filter on distinct property constraints. s.distinctPropertyConstraint = NewDistinctPropertyIterator(ctx, s.distinctHostsConstraint) // Create the quota iterator to determine if placements would result in // the quota attached to the namespace of the job to go over. // Note: the quota iterator must be the last feasibility iterator before // we upgrade to ranking, or our quota usage will include ineligible // nodes! s.quota = NewQuotaIterator(ctx, s.distinctPropertyConstraint) // Upgrade from feasible to rank iterator rankSource := NewFeasibleRankIterator(ctx, s.quota) // Apply the bin packing, this depends on the resources needed // by a particular task group. s.binPack = NewBinPackIterator(ctx, rankSource, false, 0) // Apply the job anti-affinity iterator. This is to avoid placing // multiple allocations on the same node for this job. s.jobAntiAff = NewJobAntiAffinityIterator(ctx, s.binPack, "") // Apply node rescheduling penalty. This tries to avoid placing on a // node where the allocation failed previously s.nodeReschedulingPenalty = NewNodeReschedulingPenaltyIterator(ctx, s.jobAntiAff) // Apply scores based on affinity block s.nodeAffinity = NewNodeAffinityIterator(ctx, s.nodeReschedulingPenalty) // Apply scores based on spread block s.spread = NewSpreadIterator(ctx, s.nodeAffinity) // Add the preemption options scoring iterator preemptionScorer := NewPreemptionScoringIterator(ctx, s.spread) // Normalizes scores by averaging them across various scorers s.scoreNorm = NewScoreNormalizationIterator(ctx, preemptionScorer) // Apply a limit function. This is to avoid scanning *every* possible node. s.limit = NewLimitIterator(ctx, s.scoreNorm, 2, skipScoreThreshold, maxSkip) // Select the node with the maximum score for placement s.maxScore = NewMaxScoreIterator(ctx, s.limit) return s } // taskGroupConstraints collects the constraints, drivers and resources required by each // sub-task to aggregate the TaskGroup totals func taskGroupConstraints(tg *structs.TaskGroup) tgConstrainTuple { c := tgConstrainTuple{ constraints: make([]*structs.Constraint, 0, len(tg.Constraints)), drivers: make(map[string]struct{}), } c.constraints = append(c.constraints, tg.Constraints...) for _, task := range tg.Tasks { c.drivers[task.Driver] = struct{}{} c.constraints = append(c.constraints, task.Constraints...) } return c } // tgConstrainTuple is used to store the total constraints of a task group. type tgConstrainTuple struct { // Holds the combined constraints of the task group and all it's sub-tasks. constraints []*structs.Constraint // The set of required drivers within the task group. drivers map[string]struct{} }