storage: Re-apply the rule solver.

Instead of applying 1ef40f3
or cockroachdb#10252, this finishes the reapplication of the rule solver. However, this
also puts the rule solver under the environment flag
COCKROACH_ENABLE_RULE_SOLVER for ease of testing and defaults to not enabled.

This commit re-applies the rule solver, specifically the following commits:

1) 4446345
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.
- ruleConstraints enforces that required and prohibited constraints are
  followed, and that stores with more positive constraints are ranked higher.
- 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.

2) dd3229a
storage: implemented RuleSolver into allocator

The follow up to this commit is cockroachdb#10275 and a lot of testing to ensure that the
rule solver does indeed perform as expected.

Closes cockroachdb#9336

pkg/storage/allocator.go

@@ -20,13 +20,15 @@ package storage
 
 import (
 	"fmt"
+	"math"
 	"math/rand"
 
 	"golang.org/x/net/context"
 
 	"github.com/cockroachdb/cockroach/pkg/config"
 	"github.com/cockroachdb/cockroach/pkg/roachpb"
 	"github.com/cockroachdb/cockroach/pkg/util"
+	"github.com/cockroachdb/cockroach/pkg/util/envutil"
 	"github.com/cockroachdb/cockroach/pkg/util/log"
 	"github.com/cockroachdb/cockroach/pkg/util/syncutil"
 	"github.com/pkg/errors"
@@ -123,28 +125,37 @@ type AllocatorOptions struct {
 	// AllowRebalance allows this store to attempt to rebalance its own
 	// replicas to other stores.
 	AllowRebalance bool
+
+	// UseRuleSolver enables this store to use the updated rules based
+	// constraint solver instead of the original rebalancer.
+	UseRuleSolver bool
 }
 
 // Allocator tries to spread replicas as evenly as possible across the stores
 // in the cluster.
 type Allocator struct {
-	storePool *StorePool
-	randGen   allocatorRand
-	options   AllocatorOptions
+	storePool  *StorePool
+	randGen    allocatorRand
+	options    AllocatorOptions
+	ruleSolver ruleSolver
 }
 
 // MakeAllocator creates a new allocator using the specified StorePool.
 func MakeAllocator(storePool *StorePool, options AllocatorOptions) Allocator {
 	var randSource rand.Source
+	// There are number of test cases that make a test store but don't add
+	// gossip or a store pool. So we can't rely on the existence of the
+	// store pool in those cases.
 	if storePool != nil && storePool.deterministic {
 		randSource = rand.NewSource(777)
 	} else {
 		randSource = rand.NewSource(rand.Int63())
 	}
 	return Allocator{
-		storePool: storePool,
-		options:   options,
-		randGen:   makeAllocatorRand(randSource),
+		storePool:  storePool,
+		options:    options,
+		randGen:    makeAllocatorRand(randSource),
+		ruleSolver: makeRuleSolver(defaultSolverRules),
 	}
 }
 
@@ -203,6 +214,28 @@ func (a *Allocator) AllocateTarget(
 	rangeID roachpb.RangeID,
 	relaxConstraints bool,
 ) (*roachpb.StoreDescriptor, error) {
+	if a.options.UseRuleSolver {
+		sl, _, throttledStoreCount := a.storePool.getStoreList(rangeID)
+		// When there are throttled stores that do match, we shouldn't send
+		// the replica to purgatory.
+		if throttledStoreCount > 0 {
+			return nil, errors.Errorf("%d matching stores are currently throttled", throttledStoreCount)
+		}
+
+		candidates, err := a.ruleSolver.Solve(sl, constraints, existing)
+		if err != nil {
+			return nil, err
+		}
+
+		if len(candidates) == 0 {
+			return nil, &allocatorError{
+				required: constraints.Constraints,
+			}
+		}
+		// TODO(bram): #10275 Need some randomness here!
+		return &candidates[0].store, nil
+	}
+
 	existingNodes := make(nodeIDSet, len(existing))
 	for _, repl := range existing {
 		existingNodes[repl.NodeID] = struct{}{}
@@ -244,12 +277,55 @@ func (a *Allocator) AllocateTarget(
 // make correct decisions in the case of ranges with heterogeneous replica
 // requirements (i.e. multiple data centers).
 func (a Allocator) RemoveTarget(
-	existing []roachpb.ReplicaDescriptor, leaseStoreID roachpb.StoreID,
+	constraints config.Constraints,
+	existing []roachpb.ReplicaDescriptor,
+	leaseStoreID roachpb.StoreID,
 ) (roachpb.ReplicaDescriptor, error) {
 	if len(existing) == 0 {
 		return roachpb.ReplicaDescriptor{}, errors.Errorf("must supply at least one replica to allocator.RemoveTarget()")
 	}
 
+	if a.options.UseRuleSolver {
+		// TODO(bram): #10275 Is this getStoreList call required? Compute candidate
+		// requires a store list, but we should be able to create one using only
+		// the stores that belong to the range.
+		// Use an invalid range ID as we don't care about a corrupt replicas since
+		// as we are removing a replica and not trying to add one.
+		sl, _, _ := a.storePool.getStoreList(roachpb.RangeID(0))
+
+		var worst roachpb.ReplicaDescriptor
+		worstScore := math.Inf(0)
+		for _, exist := range existing {
+			if exist.StoreID == leaseStoreID {
+				continue
+			}
+			desc, ok := a.storePool.getStoreDescriptor(exist.StoreID)
+			if !ok {
+				continue
+			}
+
+			// When a candidate is not valid, the score will be 0 and it should
+			// be chosen for removal.
+			if candidate, _ := a.ruleSolver.computeCandidate(solveState{
+				constraints: constraints,
+				store:       desc,
+				existing:    nil,
+				sl:          sl,
+				tierOrder:   canonicalTierOrder(sl),
+				tiers:       storeTierMap(sl),
+			}); candidate.score < worstScore {
+				worstScore = candidate.score
+				worst = exist
+			}
+		}
+
+		if !math.IsInf(worstScore, 0) {
+			return worst, nil
+		}
+
+		return roachpb.ReplicaDescriptor{}, errors.New("could not select an appropriate replica to be removed")
+	}
+
 	// Retrieve store descriptors for the provided replicas from the StorePool.
 	var descriptors []roachpb.StoreDescriptor
 	for _, exist := range existing {
@@ -269,7 +345,7 @@ func (a Allocator) RemoveTarget(
 			}
 		}
 	}
-	return roachpb.ReplicaDescriptor{}, errors.Errorf("RemoveTarget() could not select an appropriate replica to be remove")
+	return roachpb.ReplicaDescriptor{}, errors.New("could not select an appropriate replica to be removed")
 }
 
 // RebalanceTarget returns a suitable store for a rebalance target with
@@ -297,9 +373,80 @@ func (a Allocator) RebalanceTarget(
 	existing []roachpb.ReplicaDescriptor,
 	leaseStoreID roachpb.StoreID,
 	rangeID roachpb.RangeID,
-) *roachpb.StoreDescriptor {
+) (*roachpb.StoreDescriptor, error) {
 	if !a.options.AllowRebalance {
-		return nil
+		return nil, nil
+	}
+
+	if a.options.UseRuleSolver {
+		sl, _, _ := a.storePool.getStoreList(rangeID)
+		if log.V(3) {
+			log.Infof(context.TODO(), "rebalance-target (lease-holder=%d):\n%s", leaseStoreID, sl)
+		}
+
+		var shouldRebalance bool
+		for _, repl := range existing {
+			if leaseStoreID == repl.StoreID {
+				continue
+			}
+			storeDesc, ok := a.storePool.getStoreDescriptor(repl.StoreID)
+			if ok && a.shouldRebalance(storeDesc, sl) {
+				shouldRebalance = true
+				break
+			}
+		}
+		if !shouldRebalance {
+			return nil, nil
+		}
+
+		// Load the exiting storesIDs into a map so to eliminate having to loop
+		// through the existing descriptors more than once.
+		existingStoreIDs := make(map[roachpb.StoreID]struct{})
+		for _, repl := range existing {
+			existingStoreIDs[repl.StoreID] = struct{}{}
+		}
+
+		// Split the store list into existing and candidate stores lists so that
+		// we can call solve independently on both store lists.
+		var existingDescs []roachpb.StoreDescriptor
+		var candidateDescs []roachpb.StoreDescriptor
+		for _, desc := range sl.stores {
+			if _, ok := existingStoreIDs[desc.StoreID]; ok {
+				existingDescs = append(existingDescs, desc)
+			} else {
+				candidateDescs = append(candidateDescs, desc)
+			}
+		}
+
+		existingStoreList := makeStoreList(existingDescs)
+		candidateStoreList := makeStoreList(candidateDescs)
+
+		existingCandidates, err := a.ruleSolver.Solve(existingStoreList, constraints, nil)
+		if err != nil {
+			return nil, err
+		}
+		candidates, err := a.ruleSolver.Solve(candidateStoreList, constraints, nil)
+		if err != nil {
+			return nil, err
+		}
+
+		// Find all candidates that are better than the worst existing store.
+		var worstCandidateStore float64
+		// If any store from existing is not included in existingCandidates, it
+		// is because it no longer meets the constraints. If so, its score is
+		// considered to be 0.
+		if len(existingCandidates) == len(existing) {
+			worstCandidateStore = existingCandidates[len(existingCandidates)-1].score
+		}
+
+		// TODO(bram): #10275 Need some randomness here!
+		for _, cand := range candidates {
+			if cand.score > worstCandidateStore {
+				return &candidates[0].store, nil
+			}
+		}
+
+		return nil, nil
 	}
 
 	sl, _, _ := a.storePool.getStoreList(rangeID)
@@ -320,14 +467,14 @@ func (a Allocator) RebalanceTarget(
 		}
 	}
 	if !shouldRebalance {
-		return nil
+		return nil, nil
 	}
 
 	existingNodes := make(nodeIDSet, len(existing))
 	for _, repl := range existing {
 		existingNodes[repl.NodeID] = struct{}{}
 	}
-	return a.improve(sl, existingNodes)
+	return a.improve(sl, existingNodes), nil
 }
 
 // selectGood attempts to select a store from the supplied store list that it
@@ -356,11 +503,53 @@ func (a Allocator) improve(sl StoreList, excluded nodeIDSet) *roachpb.StoreDescr
 	return rcb.improve(sl, excluded)
 }
 
+// rebalanceThreshold is the minimum ratio of a store's range surplus to the
+// mean range count that permits rebalances away from that store.
+var rebalanceThreshold = envutil.EnvOrDefaultFloat("COCKROACH_REBALANCE_THRESHOLD", 0.05)
+
 // shouldRebalance returns whether the specified store is a candidate for
 // having a replica removed from it given the candidate store list.
 func (a Allocator) shouldRebalance(store roachpb.StoreDescriptor, sl StoreList) bool {
-	rcb := rangeCountBalancer{a.randGen}
-	return rcb.shouldRebalance(store, sl)
+	// TODO(peter,bram,cuong): The FractionUsed check seems suspicious. When a
+	// node becomes fuller than maxFractionUsedThreshold we will always select it
+	// for rebalancing.
+	maxCapacityUsed := store.Capacity.FractionUsed() >= maxFractionUsedThreshold
+
+	// Rebalance if we're above the rebalance target, which is
+	// mean*(1+rebalanceThreshold).
+	target := int32(math.Ceil(sl.candidateCount.mean * (1 + rebalanceThreshold)))
+	rangeCountAboveTarget := store.Capacity.RangeCount > target
+
+	// Rebalance if the candidate store has a range count above the mean, and
+	// there exists another store that is underfull: its range count is smaller
+	// than mean*(1-rebalanceThreshold).
+	var rebalanceToUnderfullStore bool
+	if float64(store.Capacity.RangeCount) > sl.candidateCount.mean {
+		underfullThreshold := int32(math.Floor(sl.candidateCount.mean * (1 - rebalanceThreshold)))
+		for _, desc := range sl.stores {
+			if desc.Capacity.RangeCount < underfullThreshold {
+				rebalanceToUnderfullStore = true
+				break
+			}
+		}
+	}
+
+	// Require that moving a replica from the given store makes its range count
+	// converge on the mean range count. This only affects clusters with a
+	// small number of ranges.
+	rebalanceConvergesOnMean := rebalanceFromConvergesOnMean(sl, store)
+
+	result :=
+		(maxCapacityUsed || rangeCountAboveTarget || rebalanceToUnderfullStore) && rebalanceConvergesOnMean
+	if log.V(2) {
+		log.Infof(context.TODO(),
+			"%d: should-rebalance=%t: fraction-used=%.2f range-count=%d "+
+				"(mean=%.1f, target=%d, fraction-used=%t, above-target=%t, underfull=%t, converges=%t)",
+			store.StoreID, result, store.Capacity.FractionUsed(), store.Capacity.RangeCount,
+			sl.candidateCount.mean, target, maxCapacityUsed, rangeCountAboveTarget,
+			rebalanceToUnderfullStore, rebalanceConvergesOnMean)
+	}
+	return result
 }
 
 // computeQuorum computes the quorum value for the given number of nodes.