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mmaprototype: rename diversityFunc to diversityOfTwoStoreSets
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pkg/kv/kvserver/allocator/mmaprototype/constraint.go

Lines changed: 6 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -1002,7 +1002,8 @@ func (ac *analyzedConstraints) analyzeFunc(
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}
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}
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1005-
// diversityFunc computes the diversity score between two sets of stores.
1005+
// diversityOfTwoStoreSets computes the diversity score between two sets of
1006+
// stores.
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//
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// When sameStores is false, intersection between this and other is empty and no
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// de-duplication is needed. For example, given two sets of stores [1, 2, 3] and
@@ -1012,7 +1013,7 @@ func (ac *analyzedConstraints) analyzeFunc(
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// When sameStores is true, this and other are the same set and de-duplication
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// is needed. For example, given two sets of stores [1, 2, 3] and [1, 2, 3],
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// diversity score should be computed among pairs (1, 2), (1, 3), (2, 3) only.
1015-
func diversityFunc(
1016+
func diversityOfTwoStoreSets(
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this []storeAndLocality, other []storeAndLocality, sameStores bool,
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) (sumScore float64, numSamples int) {
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for i := range this {
@@ -1052,15 +1053,15 @@ func diversityScore(
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return sumScore / float64(numSamples)
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}
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1055-
voterSum, voterSamples := diversityFunc(replicas[voterIndex], replicas[voterIndex], true)
1056+
voterSum, voterSamples := diversityOfTwoStoreSets(replicas[voterIndex], replicas[voterIndex], true)
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totalSum := voterSum
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totalSamples := voterSamples
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1059-
nonVoterSum, nonVoterSamples := diversityFunc(replicas[nonVoterIndex], replicas[nonVoterIndex], true)
1060+
nonVoterSum, nonVoterSamples := diversityOfTwoStoreSets(replicas[nonVoterIndex], replicas[nonVoterIndex], true)
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totalSum += nonVoterSum
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totalSamples += nonVoterSamples
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1063-
voterNonVoterSum, voterNonVoterSamples := diversityFunc(replicas[voterIndex], replicas[nonVoterIndex], false)
1064+
voterNonVoterSum, voterNonVoterSamples := diversityOfTwoStoreSets(replicas[voterIndex], replicas[nonVoterIndex], false)
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totalSum += voterNonVoterSum
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totalSamples += voterNonVoterSamples
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return scoreFromSumAndSamples(voterSum, voterSamples), scoreFromSumAndSamples(totalSum, totalSamples)

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