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storage: add constraint rule solver for allocation
Rules are represented as a single function that returns the candidacy of the store as well as a float value representing the score. These scores are then aggregated from all rules and returns the stores sorted by them. Current rules: * ruleReplicasUniqueNodes ensures that no two replicas are put on the same node. * ruleNoProhibitedConstraints ensures that the candidate store has no prohibited constraints. * ruleRequiredConstraints ensures that the candidate store has the required constraints. * rulePositiveConstraints ensures that nodes that match more the positive constraints are given higher priority. * ruleDiversity ensures that nodes that have the fewest locality tiers in common are given higher priority. * ruleCapacity prioritizes placing data on empty nodes when the choice is available and prevents data from going onto mostly full nodes.
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// Copyright 2016 The Cockroach Authors. | ||
// | ||
// Licensed under the Apache License, Version 2.0 (the "License"); | ||
// you may not use this file except in compliance with the License. | ||
// You may obtain a copy of the License at | ||
// | ||
// http://www.apache.org/licenses/LICENSE-2.0 | ||
// | ||
// Unless required by applicable law or agreed to in writing, software | ||
// distributed under the License is distributed on an "AS IS" BASIS, | ||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or | ||
// implied. See the License for the specific language governing | ||
// permissions and limitations under the License. | ||
// | ||
// Author: Tristan Rice ([email protected]) | ||
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package storage | ||
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import ( | ||
"math" | ||
"sort" | ||
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"github.com/cockroachdb/cockroach/config" | ||
"github.com/cockroachdb/cockroach/roachpb" | ||
"github.com/pkg/errors" | ||
) | ||
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type candidate struct { | ||
store roachpb.StoreDescriptor | ||
score float64 | ||
} | ||
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// rule is a generic rule that can be used to solve a constraint problem. | ||
// Returning false will remove the store from the list of candidate stores. The | ||
// score will be weighted and then summed together with the other rule scores to | ||
// create a store ranking (higher is better). | ||
type rule struct { | ||
weight float64 | ||
run func( | ||
c config.Constraints, | ||
store roachpb.StoreDescriptor, | ||
existing []roachpb.ReplicaDescriptor, | ||
sl StoreList, | ||
) (candidate bool, score float64) | ||
} | ||
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// defaultRules is the default rule set to use. | ||
var defaultRules = []rule{ | ||
{ | ||
weight: 1.0, | ||
run: ruleReplicasUniqueNodes, | ||
}, | ||
{ | ||
weight: 1.0, | ||
run: ruleConstraints, | ||
}, | ||
{ | ||
weight: 0.01, | ||
run: ruleCapacity, | ||
}, | ||
{ | ||
weight: 0.1, | ||
run: ruleDiversity, | ||
}, | ||
} | ||
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// makeDefaultRuleSolver returns a ruleSolver with defaultRules. | ||
func makeDefaultRuleSolver(storePool *StorePool) *ruleSolver { | ||
return makeRuleSolver(storePool, defaultRules) | ||
} | ||
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// makeRuleSolver makes a new ruleSolver. The order of the rules is the order in | ||
// which they are run. For optimization purposes, less computationally intense | ||
// rules should run first to eliminate candidates. | ||
func makeRuleSolver(storePool *StorePool, rules []rule) *ruleSolver { | ||
return &ruleSolver{ | ||
storePool: storePool, | ||
rules: rules, | ||
} | ||
} | ||
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// ruleSolver solves a set of rules for a store. | ||
type ruleSolver struct { | ||
storePool *StorePool | ||
rules []rule | ||
} | ||
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// solve solves given constraints. See (*ruleSolver).solveInternal. | ||
func (rs *ruleSolver) solve( | ||
c config.Constraints, existing []roachpb.ReplicaDescriptor, | ||
) ([]roachpb.StoreDescriptor, error) { | ||
candidates, err := rs.solveScores(c, existing) | ||
if err != nil { | ||
return nil, err | ||
} | ||
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candidateStores := make([]roachpb.StoreDescriptor, len(candidates)) | ||
for i, candidate := range candidates { | ||
candidateStores[i] = candidate.store | ||
} | ||
return candidateStores, nil | ||
} | ||
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// solveScores solves given constraints and returns the score. | ||
func (rs *ruleSolver) solveScores( | ||
c config.Constraints, existing []roachpb.ReplicaDescriptor, | ||
) ([]candidate, error) { | ||
sl, _, throttledStoreCount := rs.storePool.getStoreList(config.Constraints{}, false) | ||
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// When there are throttled stores that do match, we shouldn't send | ||
// the replica to purgatory or even consider relaxing the constraints. | ||
if throttledStoreCount > 0 { | ||
return nil, errors.Errorf("%d matching stores are currently throttled", throttledStoreCount) | ||
} | ||
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candidates := make([]candidate, 0, len(sl.stores)) | ||
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for _, store := range sl.stores { | ||
if cand, ok := rs.computeCandidate(c, store, existing, sl); ok { | ||
candidates = append(candidates, cand) | ||
} | ||
} | ||
sort.Sort(byScore(candidates)) | ||
return candidates, nil | ||
} | ||
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func (rs *ruleSolver) computeCandidate( | ||
constraints config.Constraints, | ||
store roachpb.StoreDescriptor, | ||
existing []roachpb.ReplicaDescriptor, | ||
sl StoreList, | ||
) (candidate, bool) { | ||
var totalScore float64 | ||
for _, rule := range rs.rules { | ||
isCandidate, score := rule.run(constraints, store, existing, sl) | ||
if !isCandidate { | ||
return candidate{}, false | ||
} | ||
if !math.IsNaN(score) { | ||
totalScore += score * rule.weight | ||
} | ||
} | ||
return candidate{store: store, score: totalScore}, true | ||
} | ||
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// ruleReplicasUniqueNodes ensures that no two replicas are put on the same | ||
// node. | ||
func ruleReplicasUniqueNodes( | ||
_ config.Constraints, | ||
store roachpb.StoreDescriptor, | ||
existing []roachpb.ReplicaDescriptor, | ||
_ StoreList, | ||
) (candidate bool, score float64) { | ||
for _, r := range existing { | ||
if r.NodeID == store.Node.NodeID { | ||
return false, 0 | ||
} | ||
} | ||
return true, 0 | ||
} | ||
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func storeHasConstraint(store roachpb.StoreDescriptor, c config.Constraint) bool { | ||
var found bool | ||
if c.Key == "" { | ||
for _, attrs := range []roachpb.Attributes{store.Attrs, store.Node.Attrs} { | ||
for _, attr := range attrs.Attrs { | ||
if attr == c.Value { | ||
return true | ||
} | ||
} | ||
} | ||
} else { | ||
for _, tier := range store.Locality.Tiers { | ||
if c.Key == tier.Key && c.Value == tier.Value { | ||
return true | ||
} | ||
} | ||
} | ||
return found | ||
} | ||
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// ruleConstraints enforces that required and prohibited constraints are | ||
// followed, and that stores with more positive constraints are ranked higher. | ||
func ruleConstraints( | ||
constraints config.Constraints, | ||
store roachpb.StoreDescriptor, | ||
_ []roachpb.ReplicaDescriptor, | ||
_ StoreList, | ||
) (candidate bool, score float64) { | ||
matched := 0 | ||
for _, c := range constraints.Constraints { | ||
hasConstraint := storeHasConstraint(store, c) | ||
switch { | ||
case c.Type == config.Constraint_POSITIVE && hasConstraint: | ||
matched++ | ||
case c.Type == config.Constraint_REQUIRED && !hasConstraint: | ||
return false, 0 | ||
case c.Type == config.Constraint_PROHIBITED && hasConstraint: | ||
return false, 0 | ||
} | ||
} | ||
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return true, float64(matched) / float64(len(constraints.Constraints)) | ||
} | ||
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// ruleDiversity ensures that nodes that have the fewest locality tiers in | ||
// common are given higher priority. | ||
func ruleDiversity( | ||
_ config.Constraints, | ||
store roachpb.StoreDescriptor, | ||
existing []roachpb.ReplicaDescriptor, | ||
sl StoreList, | ||
) (candidate bool, score float64) { | ||
stores := map[roachpb.StoreID]roachpb.StoreDescriptor{} | ||
for _, store := range sl.stores { | ||
stores[store.StoreID] = store | ||
} | ||
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var maxScore float64 | ||
tiers := store.Locality.Tiers | ||
for i, tier := range tiers { | ||
tierScore := float64(int(1) << uint(len(tiers)-i-1)) | ||
for _, existing := range existing { | ||
store := stores[existing.StoreID] | ||
st := store.Locality.Tiers | ||
if len(st) < i || st[i].Key != tier.Key { | ||
panic("TODO(d4l3k): Node locality configurations are not equivalent") | ||
} | ||
if st[i].Value != tier.Value { | ||
score += tierScore | ||
} | ||
maxScore += tierScore | ||
} | ||
} | ||
return true, score / maxScore | ||
} | ||
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// ruleCapacity prioritizes placing data on empty nodes when the choice is | ||
// available and prevents data from going onto mostly full nodes. | ||
func ruleCapacity( | ||
_ config.Constraints, | ||
store roachpb.StoreDescriptor, | ||
_ []roachpb.ReplicaDescriptor, | ||
_ StoreList, | ||
) (candidate bool, score float64) { | ||
// Don't overfill stores. | ||
if store.Capacity.FractionUsed() > maxFractionUsedThreshold { | ||
return false, 0 | ||
} | ||
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return true, 1 / float64(store.Capacity.RangeCount+1) | ||
} | ||
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type byScore []candidate | ||
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func (c byScore) Len() int { return len(c) } | ||
func (c byScore) Less(i, j int) bool { return c[i].score > c[j].score } | ||
func (c byScore) Swap(i, j int) { c[i], c[j] = c[j], c[i] } |
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