79 lines
3.0 KiB
Go
79 lines
3.0 KiB
Go
|
// +build !pro,!ent
|
||
|
|
|
||
|
|
package scheduler
|
||
|
|
|
||
|
|
// 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)
|
||
|
|
|
||
|
|
// 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)
|
||
|
|
|
||
|
|
// 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)
|
||
|
|
|
||
|
|
// 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.wrappedChecks = NewFeasibilityWrapper(ctx, s.quota, jobs, tgs)
|
||
|
|
|
||
|
|
// Filter on distinct host constraints.
|
||
|
|
s.distinctHostsConstraint = NewDistinctHostsIterator(ctx, s.wrappedChecks)
|
||
|
|
|
||
|
|
// Filter on distinct property constraints.
|
||
|
|
s.distinctPropertyConstraint = NewDistinctPropertyIterator(ctx, s.distinctHostsConstraint)
|
||
|
|
|
||
|
|
// Upgrade from feasible to rank iterator
|
||
|
|
rankSource := NewFeasibleRankIterator(ctx, s.distinctPropertyConstraint)
|
||
|
|
|
||
|
|
// 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 stanza
|
||
|
|
s.nodeAffinity = NewNodeAffinityIterator(ctx, s.nodeReschedulingPenalty)
|
||
|
|
|
||
|
|
// Apply scores based on spread stanza
|
||
|
|
s.spread = NewSpreadIterator(ctx, s.nodeAffinity)
|
||
|
|
|
||
|
|
// Normalizes scores by averaging them across various scorers
|
||
|
|
s.scoreNorm = NewScoreNormalizationIterator(ctx, s.spread)
|
||
|
|
|
||
|
|
// 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
|
||
|
|
}
|