open-nomad/scheduler/stack.go

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package scheduler
import (
"math"
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"time"
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"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
)
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// 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.
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type Stack interface {
// SetNodes is used to set the base set of potential nodes
SetNodes([]*structs.Node)
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// 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, *structs.Resources)
}
type SelectOptions struct {
PenaltyNodeIDs map[string]struct{}
PreferredNodes []*structs.Node
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}
// GenericStack is the Stack used for the Generic scheduler. It is
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// designed to make better placement decisions at the cost of performance.
type GenericStack struct {
batch bool
ctx Context
source *StaticIterator
wrappedChecks *FeasibilityWrapper
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quota FeasibleIterator
jobConstraint *ConstraintChecker
taskGroupDrivers *DriverChecker
taskGroupConstraint *ConstraintChecker
distinctHostsConstraint *DistinctHostsIterator
distinctPropertyConstraint *DistinctPropertyIterator
binPack *BinPackIterator
jobAntiAff *JobAntiAffinityIterator
nodeReschedulingPenalty *NodeReschedulingPenaltyIterator
limit *LimitIterator
maxScore *MaxScoreIterator
nodeAffinity *NodeAffinityIterator
spread *SpreadIterator
scoreNorm *ScoreNormalizationIterator
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}
// NewGenericStack constructs a stack used for selecting service placements
func NewGenericStack(batch bool, ctx Context) *GenericStack {
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// Create a new stack
s := &GenericStack{
batch: batch,
ctx: ctx,
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}
// 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)
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// Create the quota iterator to determine if placements would result in the
// quota attached to the namespace of the job to go over.
s.quota = NewQuotaIterator(ctx, s.source)
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// Attach the job constraints. The job is filled in later.
s.jobConstraint = NewConstraintChecker(ctx, nil)
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// Filter on task group drivers first as they are faster
s.taskGroupDrivers = NewDriverChecker(ctx, nil)
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// Filter on task group constraints second
s.taskGroupConstraint = NewConstraintChecker(ctx, nil)
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// 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}
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s.wrappedChecks = NewFeasibilityWrapper(ctx, s.quota, jobs, tgs)
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// Filter on distinct host constraints.
s.distinctHostsConstraint = NewDistinctHostsIterator(ctx, s.wrappedChecks)
// Filter on distinct property constraints.
s.distinctPropertyConstraint = NewDistinctPropertyIterator(ctx, s.distinctHostsConstraint)
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// Upgrade from feasible to rank iterator
rankSource := NewFeasibleRankIterator(ctx, s.distinctPropertyConstraint)
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// Apply the bin packing, this depends on the resources needed
// by a particular task group. Only enable eviction for the service
// scheduler as that logic is expensive.
evict := !batch
s.binPack = NewBinPackIterator(ctx, rankSource, evict, 0)
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// 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, "")
s.nodeReschedulingPenalty = NewNodeReschedulingPenaltyIterator(ctx, s.jobAntiAff)
s.nodeAffinity = NewNodeAffinityIterator(ctx, s.nodeReschedulingPenalty)
s.spread = NewSpreadIterator(ctx, s.nodeAffinity)
s.scoreNorm = NewScoreNormalizationIterator(ctx, s.spread)
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// Apply a limit function. This is to avoid scanning *every* possible node.
s.limit = NewLimitIterator(ctx, s.scoreNorm, 2, skipScoreThreshold, maxSkip)
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// Select the node with the maximum score for placement
s.maxScore = NewMaxScoreIterator(ctx, s.limit)
return s
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}
func (s *GenericStack) SetNodes(baseNodes []*structs.Node) {
// Shuffle base nodes
shuffleNodes(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
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// 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) {
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s.jobConstraint.SetConstraints(job.Constraints)
s.distinctHostsConstraint.SetJob(job)
s.distinctPropertyConstraint.SetJob(job)
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s.binPack.SetPriority(job.Priority)
s.jobAntiAff.SetJob(job)
s.nodeAffinity.SetJob(job)
s.spread.SetJob(job)
s.ctx.Eligibility().SetJob(job)
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if contextual, ok := s.quota.(ContextualIterator); ok {
contextual.SetJob(job)
}
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}
func (s *GenericStack) Select(tg *structs.TaskGroup, options *SelectOptions) (*RankedNode, *structs.Resources) {
// 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, resources := s.Select(tg, &optionsNew); option != nil {
s.source.SetNodes(originalNodes)
return option, resources
}
s.source.SetNodes(originalNodes)
return s.Select(tg, &optionsNew)
}
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// Reset the max selector and context
s.maxScore.Reset()
s.ctx.Reset()
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start := time.Now()
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// Get the task groups constraints.
tgConstr := taskGroupConstraints(tg)
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// Update the parameters of iterators
s.taskGroupDrivers.SetDrivers(tgConstr.drivers)
s.taskGroupConstraint.SetConstraints(tgConstr.constraints)
s.distinctHostsConstraint.SetTaskGroup(tg)
s.distinctPropertyConstraint.SetTaskGroup(tg)
s.wrappedChecks.SetTaskGroup(tg.Name)
s.binPack.SetTaskGroup(tg)
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() {
s.limit.SetLimit(math.MaxInt32)
}
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if contextual, ok := s.quota.(ContextualIterator); ok {
contextual.SetTaskGroup(tg)
}
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// Find the node with the max score
option := s.maxScore.Next()
// Ensure that the task resources were specified
if option != nil && len(option.TaskResources) != len(tg.Tasks) {
for _, task := range tg.Tasks {
option.SetTaskResources(task, task.Resources)
}
}
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// Store the compute time
s.ctx.Metrics().AllocationTime = time.Since(start)
return option, tgConstr.size
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}
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// 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
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quota FeasibleIterator
jobConstraint *ConstraintChecker
taskGroupDrivers *DriverChecker
taskGroupConstraint *ConstraintChecker
distinctPropertyConstraint *DistinctPropertyIterator
binPack *BinPackIterator
scoreNorm *ScoreNormalizationIterator
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}
// NewSystemStack constructs a stack used for selecting service placements
func NewSystemStack(ctx Context) *SystemStack {
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// 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)
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// Create the quota iterator to determine if placements would result in the
// quota attached to the namespace of the job to go over.
s.quota = NewQuotaIterator(ctx, s.source)
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// Attach the job constraints. The job is filled in later.
s.jobConstraint = NewConstraintChecker(ctx, nil)
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// Filter on task group drivers first as they are faster
s.taskGroupDrivers = NewDriverChecker(ctx, nil)
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// Filter on task group constraints second
s.taskGroupConstraint = NewConstraintChecker(ctx, nil)
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// 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}
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s.wrappedChecks = NewFeasibilityWrapper(ctx, s.quota, jobs, tgs)
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// Filter on distinct property constraints.
s.distinctPropertyConstraint = NewDistinctPropertyIterator(ctx, s.wrappedChecks)
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// Upgrade from feasible to rank iterator
rankSource := NewFeasibleRankIterator(ctx, s.distinctPropertyConstraint)
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// Apply the bin packing, this depends on the resources needed
// by a particular task group. Enable eviction as system jobs are high
// priority.
s.binPack = NewBinPackIterator(ctx, rankSource, true, 0)
// Apply score normalization
s.scoreNorm = NewScoreNormalizationIterator(ctx, s.binPack)
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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)
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s.binPack.SetPriority(job.Priority)
s.ctx.Eligibility().SetJob(job)
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if contextual, ok := s.quota.(ContextualIterator); ok {
contextual.SetJob(job)
}
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}
func (s *SystemStack) Select(tg *structs.TaskGroup, options *SelectOptions) (*RankedNode, *structs.Resources) {
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// Reset the binpack selector and context
s.scoreNorm.Reset()
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s.ctx.Reset()
start := time.Now()
// Get the task groups constraints.
tgConstr := taskGroupConstraints(tg)
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// Update the parameters of iterators
s.taskGroupDrivers.SetDrivers(tgConstr.drivers)
s.taskGroupConstraint.SetConstraints(tgConstr.constraints)
s.wrappedChecks.SetTaskGroup(tg.Name)
s.distinctPropertyConstraint.SetTaskGroup(tg)
s.binPack.SetTaskGroup(tg)
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if contextual, ok := s.quota.(ContextualIterator); ok {
contextual.SetTaskGroup(tg)
}
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// Get the next option that satisfies the constraints.
option := s.scoreNorm.Next()
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// Ensure that the task resources were specified
if option != nil && len(option.TaskResources) != len(tg.Tasks) {
for _, task := range tg.Tasks {
option.SetTaskResources(task, task.Resources)
}
}
// Store the compute time
s.ctx.Metrics().AllocationTime = time.Since(start)
return option, tgConstr.size
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}