.gitignore

@@ -0,0 +1,3 @@
+.idea
+.vscode
+*.out

.gitlint

@@ -0,0 +1,10 @@
+[general]
+fail-without-commits=true
+contrib=CC1
+
+[title-match-regex]
+regex=^\[\#[0-9]+\]\s
+
+[ignore-by-title]
+regex=^Release(.*)
+ignore=title-match-regex

.pre-commit-config.yaml

@@ -0,0 +1,30 @@
+ci:
+  autofix_prs: false
+
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.4.0
+    hooks:
+    - id: check-added-large-files
+    - id: check-case-conflict
+    - id: check-executables-have-shebangs
+    - id: check-shebang-scripts-are-executable
+    - id: check-merge-conflict
+    - id: check-json
+    - id: check-xml
+    - id: check-yaml
+    - id: trailing-whitespace
+      args: [--markdown-linebreak-ext=md]
+    - id: end-of-file-fixer
+      exclude: ".key$"
+
+  - repo: https://github.com/golangci/golangci-lint
+    rev: v1.51.2
+    hooks:
+    - id: golangci-lint
+
+  - repo: https://github.com/jorisroovers/gitlint
+    rev:  v0.18.0
+    hooks:
+      - id: gitlint
+        stages: [commit-msg]

LICENSE

@@ -0,0 +1,22 @@
+MIT License
+
+Copyright (c) 2023-2024 TrueCloudLab
+Copyright (c) 2019-2023 NSPCC
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,3 +1,87 @@
-# WIP area: this repo is just a fork!
+# Golang HRW implementation
 
-Useful things may be published only in [other branches](../../../branches)
+[Rendezvous or highest random weight](https://en.wikipedia.org/wiki/Rendezvous_hashing) (HRW) hashing is an algorithm that allows clients to achieve distributed agreement on a set of k options out of a possible set of n options. A typical application is when clients need to agree on which sites (or proxies) objects are assigned to. When k is 1, it subsumes the goals of consistent hashing, using an entirely different method.
+
+## Install
+
+`go get git.frostfs.info/TrueCloudLab/hrw`
+
+## Benchmark:
+
+```
+BenchmarkSort_fnv_10-8                                           4812801               240.9 ns/op           216 B/op          4 allocs/op
+BenchmarkSort_fnv_100-8                                           434767              2600 ns/op            1848 B/op          4 allocs/op
+BenchmarkSort_fnv_1000-8                                           20428             66116 ns/op           16440 B/op          4 allocs/op
+BenchmarkSortByIndex_fnv_10-8                                    2505410               486.5 ns/op           352 B/op          7 allocs/op
+BenchmarkSortByIndex_fnv_100-8                                    254556              4697 ns/op            1984 B/op          7 allocs/op
+BenchmarkSortByIndex_fnv_1000-8                                    13581             88334 ns/op           16576 B/op          7 allocs/op
+BenchmarkSortByValue_fnv_10-8                                    1761030               682.1 ns/op           592 B/op         18 allocs/op
+BenchmarkSortByValue_fnv_100-8                                    258838              4675 ns/op            4480 B/op        108 allocs/op
+BenchmarkSortByValue_fnv_1000-8                                    27027             44649 ns/op           40768 B/op       1008 allocs/op
+BenchmarkSortHashersByValue_Reflection_fnv_10-8                  1013560              1249 ns/op             768 B/op         29 allocs/op
+BenchmarkSortHashersByValue_Reflection_fnv_100-8                  106029             11414 ns/op            6096 B/op        209 allocs/op
+BenchmarkSortHashersByValue_Reflection_fnv_1000-8                  10000            108977 ns/op           56784 B/op       2009 allocs/op
+BenchmarkSortHashersByValue_Typed_fnv_10-8                       1577814               700.3 ns/op           584 B/op         17 allocs/op
+BenchmarkSortHashersByValue_Typed_fnv_100-8                       215938              5024 ns/op            4472 B/op        107 allocs/op
+BenchmarkSortHashersByValue_Typed_fnv_1000-8                       24447             46889 ns/op           40760 B/op       1007 allocs/op
+
+BenchmarkSortByWeight_fnv_10-8                                   2924833               370.6 ns/op           448 B/op          8 allocs/op
+BenchmarkSortByWeight_fnv_100-8                                   816069              1516 ns/op            2896 B/op          8 allocs/op
+BenchmarkSortByWeight_fnv_1000-8                                   80391             17478 ns/op           24784 B/op          8 allocs/op
+BenchmarkSortByWeightIndex_fnv_10-8                              1945612               550.3 ns/op           368 B/op          7 allocs/op
+BenchmarkSortByWeightIndex_fnv_100-8                              140473              8084 ns/op            2000 B/op          7 allocs/op
+BenchmarkSortByWeightIndex_fnv_1000-8                               5518            200949 ns/op           16592 B/op          7 allocs/op
+BenchmarkSortByWeightValue_fnv_10-8                              1305580               909.8 ns/op           608 B/op         18 allocs/op
+BenchmarkSortByWeightValue_fnv_100-8                              165410              6796 ns/op            4496 B/op        108 allocs/op
+BenchmarkSortByWeightValue_fnv_1000-8                              17922             78555 ns/op           40784 B/op       1008 allocs/op
+BenchmarkSortHashersByWeightValueReflection_fnv_10-8              454976              2229 ns/op             784 B/op         29 allocs/op
+BenchmarkSortHashersByWeightValueReflection_fnv_100-8              76264             15332 ns/op            6112 B/op        209 allocs/op
+BenchmarkSortHashersByWeightValueReflection_fnv_1000-8             80288             13192 ns/op            6112 B/op        209 allocs/op
+BenchmarkSortHashersByWeightValueTyped_fnv_10-8                  1433113               901.4 ns/op           600 B/op         17 allocs/op
+BenchmarkSortHashersByWeightValueTyped_fnv_100-8                  188626              5896 ns/op            4488 B/op        107 allocs/op
+BenchmarkSortHashersByWeightValueTyped_fnv_1000-8                 178131              6518 ns/op            4488 B/op        107 allocs/op
+```
+
+## Example
+
+```go
+package main
+
+import (
+	"fmt"
+
+	"git.frostfs.info/TrueCloudLab/hrw"
+)
+
+func main() {
+	// given a set of servers
+	servers := []string{
+		"one.example.com",
+		"two.example.com",
+		"three.example.com",
+		"four.example.com",
+		"five.example.com",
+		"six.example.com",
+	}
+
+	// HRW can consistently select a uniformly-distributed set of servers for
+	// any given key
+	var (
+		key = []byte("/examples/object-key")
+		h   = hrw.Hash(key)
+	)
+
+	hrw.SortSliceByValue(servers, h)
+	for id := range servers {
+		fmt.Printf("trying GET %s%s\n", servers[id], key)
+	}
+
+	// Output:
+	// trying GET three.example.com/examples/object-key
+	// trying GET two.example.com/examples/object-key
+	// trying GET five.example.com/examples/object-key
+	// trying GET six.example.com/examples/object-key
+	// trying GET one.example.com/examples/object-key
+	// trying GET four.example.com/examples/object-key
+}
+```

go.mod

@@ -0,0 +1,13 @@
+module git.frostfs.info/TrueCloudLab/hrw
+
+go 1.18
+
+require (
+	github.com/stretchr/testify v1.3.0
+	github.com/twmb/murmur3 v1.1.8
+)
+
+require (
+	github.com/davecgh/go-spew v1.1.0 // indirect
+	github.com/pmezard/go-difflib v1.0.0 // indirect
+)

go.sum

@@ -0,0 +1,9 @@
+github.com/davecgh/go-spew v1.1.0 h1:ZDRjVQ15GmhC3fiQ8ni8+OwkZQO4DARzQgrnXU1Liz8=
+github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
+github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
+github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
+github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
+github.com/stretchr/testify v1.3.0 h1:TivCn/peBQ7UY8ooIcPgZFpTNSz0Q2U6UrFlUfqbe0Q=
+github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
+github.com/twmb/murmur3 v1.1.8 h1:8Yt9taO/WN3l08xErzjeschgZU2QSrwm1kclYq+0aRg=
+github.com/twmb/murmur3 v1.1.8/go.mod h1:Qq/R7NUyOfr65zD+6Q5IHKsJLwP7exErjN6lyyq3OSQ=

hrw.go

@@ -0,0 +1,361 @@
+// Package hrw implements Rendezvous hashing.
+// http://en.wikipedia.org/wiki/Rendezvous_hashing.
+package hrw
+
+import (
+	"encoding/binary"
+	"errors"
+	"math"
+	"reflect"
+	"sort"
+
+	"github.com/twmb/murmur3"
+)
+
+type (
+	// Hasher interface used by SortSliceByValue
+	Hasher interface{ Hash() uint64 }
+
+	sorter struct {
+		l    int
+		less func(i, j int) bool
+		swap func(i, j int)
+	}
+
+	hasherSorter[T Hasher, N interface{ ~uint64 | ~float64 }] struct {
+		slice []T
+		dist  []N
+		asc   bool
+	}
+)
+
+// Boundaries of valid normalized weights
+const (
+	NormalizedMaxWeight = 1.0
+	NormalizedMinWeight = 0.0
+)
+
+func (s *sorter) Len() int           { return s.l }
+func (s *sorter) Less(i, j int) bool { return s.less(i, j) }
+func (s *sorter) Swap(i, j int)      { s.swap(i, j) }
+
+func (s *hasherSorter[T, N]) Len() int { return len(s.slice) }
+func (s *hasherSorter[T, N]) Less(i, j int) bool {
+	if s.asc {
+		return s.dist[i] < s.dist[j]
+	}
+	return s.dist[i] > s.dist[j]
+}
+func (s *hasherSorter[T, N]) Swap(i, j int) {
+	s.slice[i], s.slice[j] = s.slice[j], s.slice[i]
+	s.dist[i], s.dist[j] = s.dist[j], s.dist[i]
+}
+
+func distance(x uint64, y uint64) uint64 {
+	acc := x ^ y
+	// here used mmh3 64 bit finalizer
+	// https://github.com/aappleby/smhasher/blob/61a0530f28277f2e850bfc39600ce61d02b518de/src/MurmurHash3.cpp#L81
+	acc ^= acc >> 33
+	acc = acc * 0xff51afd7ed558ccd
+	acc ^= acc >> 33
+	acc = acc * 0xc4ceb9fe1a85ec53
+	acc ^= acc >> 33
+	return acc
+}
+
+// Hash uses murmur3 hash to return uint64
+func Hash(key []byte) uint64 {
+	return murmur3.Sum64(key)
+}
+
+// StringHash uses murmur3 hash to return uint64
+func StringHash(key string) uint64 {
+	return murmur3.StringSum64(key)
+}
+
+// Sort receive nodes and hash, and sort it by distance
+func Sort(nodes []uint64, hash uint64) []uint64 {
+	l := len(nodes)
+	sorted := make([]uint64, l)
+	dist := make([]uint64, l)
+	for i := range nodes {
+		sorted[i] = uint64(i)
+		dist[i] = distance(nodes[i], hash)
+	}
+
+	sort.Slice(sorted, func(i, j int) bool {
+		return dist[sorted[i]] < dist[sorted[j]]
+	})
+	return sorted
+}
+
+// SortByWeight receive nodes, weights and hash, and sort it by distance * weight
+func SortByWeight(nodes []uint64, weights []float64, hash uint64) []uint64 {
+	result := make([]uint64, len(nodes))
+	copy(nodes, result)
+	sortByWeight(len(nodes), false, nodes, weights, hash, reflect.Swapper(result))
+	return result
+}
+
+// SortSliceByValue received []T and hash to sort by value-distance
+func SortSliceByValue(slice interface{}, hash uint64) {
+	rule := prepareRule(slice)
+	if rule != nil {
+		swap := reflect.Swapper(slice)
+		sortByDistance(len(rule), false, rule, hash, swap)
+	}
+}
+
+// SortHasherSliceByValue receives []Hasher and hash to sort by value-distance.
+func SortHasherSliceByValue[T Hasher](slice []T, hash uint64) {
+	if len(slice) == 0 {
+		return
+	}
+
+	dist := make([]uint64, len(slice))
+	for i := range dist {
+		dist[i] = distance(slice[i].Hash(), hash)
+	}
+	sortHasherByDistance(slice, false, dist)
+}
+
+// SortSliceByWeightValue received []T, weights and hash to sort by value-distance * weights
+func SortSliceByWeightValue(slice interface{}, weights []float64, hash uint64) {
+	rule := prepareRule(slice)
+	if rule != nil {
+		swap := reflect.Swapper(slice)
+		sortByWeight(reflect.ValueOf(slice).Len(), false, rule, weights, hash, swap)
+	}
+}
+
+// SortHasherSliceByWeightValue receives []Hasher, weights and hash to sort by value-distance * weights.
+func SortHasherSliceByWeightValue[T Hasher](slice []T, weights []float64, hash uint64) {
+	if len(slice) == 0 {
+		return
+	}
+
+	if allSameF64(weights) {
+		dist := make([]uint64, len(slice))
+		for i := range dist {
+			dist[i] = distance(slice[i].Hash(), hash)
+		}
+		sortHasherByDistance(slice, false, dist)
+		return
+	}
+
+	dist := make([]float64, len(slice))
+	for i := range dist {
+		d := distance(slice[i].Hash(), hash)
+		// `maxUint64 - distance` makes the shorter distance more valuable
+		// it is necessary for operation with normalized values
+		dist[i] = float64(^uint64(0)-d) * weights[i]
+	}
+
+	sort.Sort(&hasherSorter[T, float64]{
+		slice: slice,
+		dist:  dist,
+		asc:   false,
+	})
+}
+
+// sortHasherByDistance is similar to sortByDistance but accepts slice directly.
+func sortHasherByDistance[T Hasher](slice []T, byIndex bool, dist []uint64) {
+	sort.Sort(&hasherSorter[T, uint64]{
+		slice: slice,
+		dist:  dist,
+		asc:   true,
+	})
+}
+
+// SortSliceByIndex received []T and hash to sort by index-distance
+func SortSliceByIndex(slice interface{}, hash uint64) {
+	length := reflect.ValueOf(slice).Len()
+	swap := reflect.Swapper(slice)
+	sortByDistance(length, true, nil, hash, swap)
+}
+
+// SortSliceByWeightIndex received []T, weights and hash to sort by index-distance * weights
+func SortSliceByWeightIndex(slice interface{}, weights []float64, hash uint64) {
+	length := reflect.ValueOf(slice).Len()
+	swap := reflect.Swapper(slice)
+	sortByWeight(length, true, nil, weights, hash, swap)
+}
+
+func prepareRule(slice interface{}) []uint64 {
+	t := reflect.TypeOf(slice)
+	if t.Kind() != reflect.Slice {
+		panic("HRW sort expects slice, got " + t.Kind().String())
+	}
+
+	var (
+		val    = reflect.ValueOf(slice)
+		length = val.Len()
+		rule   = make([]uint64, 0, length)
+	)
+
+	if length == 0 {
+		return nil
+	}
+
+	switch slice := slice.(type) {
+	case []int:
+		var key = make([]byte, 16)
+		for i := 0; i < length; i++ {
+			binary.BigEndian.PutUint64(key, uint64(slice[i]))
+			rule = append(rule, Hash(key))
+		}
+	case []uint:
+		var key = make([]byte, 16)
+		for i := 0; i < length; i++ {
+			binary.BigEndian.PutUint64(key, uint64(slice[i]))
+			rule = append(rule, Hash(key))
+		}
+	case []int8:
+		for i := 0; i < length; i++ {
+			key := byte(slice[i])
+			rule = append(rule, Hash([]byte{key}))
+		}
+	case []uint8:
+		for i := 0; i < length; i++ {
+			key := slice[i]
+			rule = append(rule, Hash([]byte{key}))
+		}
+	case []int16:
+		var key = make([]byte, 8)
+		for i := 0; i < length; i++ {
+			binary.BigEndian.PutUint16(key, uint16(slice[i]))
+			rule = append(rule, Hash(key))
+		}
+	case []uint16:
+		var key = make([]byte, 8)
+		for i := 0; i < length; i++ {
+			binary.BigEndian.PutUint16(key, slice[i])
+			rule = append(rule, Hash(key))
+		}
+	case []int32:
+		var key = make([]byte, 16)
+		for i := 0; i < length; i++ {
+			binary.BigEndian.PutUint32(key, uint32(slice[i]))
+			rule = append(rule, Hash(key))
+		}
+	case []uint32:
+		var key = make([]byte, 16)
+		for i := 0; i < length; i++ {
+			binary.BigEndian.PutUint32(key, slice[i])
+			rule = append(rule, Hash(key))
+		}
+	case []int64:
+		var key = make([]byte, 32)
+		for i := 0; i < length; i++ {
+			binary.BigEndian.PutUint64(key, uint64(slice[i]))
+			rule = append(rule, Hash(key))
+		}
+	case []uint64:
+		var key = make([]byte, 32)
+		for i := 0; i < length; i++ {
+			binary.BigEndian.PutUint64(key, slice[i])
+			rule = append(rule, Hash(key))
+		}
+	case []string:
+		for i := 0; i < length; i++ {
+			rule = append(rule, Hash([]byte(slice[i])))
+		}
+
+	default:
+		if _, ok := val.Index(0).Interface().(Hasher); !ok {
+			panic("slice elements must implement hrw.Hasher")
+		}
+
+		for i := 0; i < length; i++ {
+			h := val.Index(i).Interface().(Hasher)
+			rule = append(rule, h.Hash())
+		}
+	}
+	return rule
+}
+
+// ValidateWeights checks if weights are normalized between 0.0 and 1.0
+func ValidateWeights(weights []float64) error {
+	for i := range weights {
+		if math.IsNaN(weights[i]) || weights[i] > NormalizedMaxWeight || weights[i] < NormalizedMinWeight {
+			return errors.New("weights are not normalized")
+		}
+	}
+	return nil
+}
+
+// sortByWeight sorts nodes by weight using provided swapper.
+// nodes contains hrw hashes. If it is nil, indices are used.
+func sortByWeight(l int, byIndex bool, nodes []uint64, weights []float64, hash uint64, swap func(i, j int)) {
+	// if all nodes have the same distance then sort uniformly
+	if allSameF64(weights) {
+		sortByDistance(l, byIndex, nodes, hash, swap)
+		return
+	}
+
+	dist := make([]float64, l)
+	for i := 0; i < l; i++ {
+		d := getDistance(byIndex, i, nodes, hash)
+		// `maxUint64 - distance` makes the shorter distance more valuable
+		// it is necessary for operation with normalized values
+		dist[i] = float64(^uint64(0)-d) * weights[i]
+	}
+
+	s := &sorter{
+		l: l,
+		swap: func(i, j int) {
+			swap(i, j)
+			dist[i], dist[j] = dist[j], dist[i]
+		},
+		less: func(i, j int) bool {
+			return dist[i] > dist[j] // higher distance must be placed lower to be first
+		},
+	}
+	sort.Sort(s)
+}
+
+// sortByDistance sorts nodes by hrw distance using provided swapper.
+// nodes contains hrw hashes. If it is nil, indices are used.
+func sortByDistance(l int, byIndex bool, nodes []uint64, hash uint64, swap func(i, j int)) {
+	dist := make([]uint64, l)
+	for i := 0; i < l; i++ {
+		dist[i] = getDistance(byIndex, i, nodes, hash)
+	}
+
+	s := &sorter{
+		l: l,
+		swap: func(i, j int) {
+			swap(i, j)
+			dist[i], dist[j] = dist[j], dist[i]
+		},
+		less: func(i, j int) bool {
+			return dist[i] < dist[j]
+		},
+	}
+	sort.Sort(s)
+}
+
+// getDistance return distance from nodes[i] to h.
+// If byIndex is true, nodes index is used.
+// Else if nodes[i] != nil, distance is calculated from this value.
+// Otherwise, and hash from node index is taken.
+func getDistance(byIndex bool, i int, nodes []uint64, h uint64) uint64 {
+	if nodes != nil {
+		return distance(nodes[i], h)
+	} else if byIndex {
+		return distance(uint64(i), h)
+	} else {
+		buf := make([]byte, 8)
+		binary.LittleEndian.PutUint64(buf, uint64(i))
+		return distance(Hash(buf), h)
+	}
+}
+
+func allSameF64(fs []float64) bool {
+	for i := range fs {
+		if fs[i] != fs[0] {
+			return false
+		}
+	}
+	return true
+}

hrw_test.go

@@ -0,0 +1,907 @@
+package hrw
+
+import (
+	"encoding/binary"
+	"fmt"
+	"math"
+	"math/rand"
+	"strconv"
+	"testing"
+
+	"github.com/stretchr/testify/require"
+)
+
+type (
+	hashString string
+	unknown    byte
+	slices     struct {
+		actual interface{}
+		expect interface{}
+	}
+
+	Uint32Slice []uint32
+)
+
+var testKey = []byte("0xff51afd7ed558ccd")
+
+func (p Uint32Slice) Len() int           { return len(p) }
+func (p Uint32Slice) Less(i, j int) bool { return p[i] < p[j] }
+func (p Uint32Slice) Swap(i, j int)      { p[i], p[j] = p[j], p[i] }
+
+func Example() {
+	// given a set of servers
+	servers := []string{
+		"one.example.com",
+		"two.example.com",
+		"three.example.com",
+		"four.example.com",
+		"five.example.com",
+		"six.example.com",
+	}
+
+	// HRW can consistently select a uniformly-distributed set of servers for
+	// any given key
+	var (
+		key = []byte("/examples/object-key")
+		h   = Hash(key)
+	)
+
+	SortSliceByValue(servers, h)
+	for id := range servers {
+		fmt.Printf("trying GET %s%s\n", servers[id], key)
+	}
+
+	// Output:
+	// trying GET three.example.com/examples/object-key
+	// trying GET two.example.com/examples/object-key
+	// trying GET five.example.com/examples/object-key
+	// trying GET six.example.com/examples/object-key
+	// trying GET one.example.com/examples/object-key
+	// trying GET four.example.com/examples/object-key
+}
+
+func (h hashString) Hash() uint64 {
+	return StringHash(string(h))
+}
+
+func TestSortSliceByIndex(t *testing.T) {
+	actual := []string{"a", "b", "c", "d", "e", "f"}
+	expect := []string{"e", "a", "c", "f", "d", "b"}
+	hash := Hash(testKey)
+	SortSliceByIndex(actual, hash)
+	require.Equal(t, expect, actual)
+}
+
+func TestValidateWeights(t *testing.T) {
+	weights := []float64{10, 10, 10, 2, 2, 2}
+	err := ValidateWeights(weights)
+	require.Error(t, err)
+	weights = []float64{math.NaN(), 1, 1, 0.2, 0.2, 0.2}
+	err = ValidateWeights(weights)
+	require.Error(t, err)
+	weights = []float64{1, 1, 1, 0.2, 0.2, 0.2}
+	err = ValidateWeights(weights)
+	require.NoError(t, err)
+}
+
+func TestSortSliceByWeightIndex(t *testing.T) {
+	actual := []string{"a", "b", "c", "d", "e", "f"}
+	weights := []float64{1, 1, 1, 0.2, 0.2, 0.2}
+	expect := []string{"a", "c", "b", "e", "f", "d"}
+	hash := Hash(testKey)
+	SortSliceByWeightIndex(actual, weights, hash)
+	require.Equal(t, expect, actual)
+}
+
+func TestSortSliceByValue(t *testing.T) {
+	actual := []string{"a", "b", "c", "d", "e", "f"}
+	expect := []string{"d", "f", "c", "b", "a", "e"}
+	hash := Hash(testKey)
+	SortSliceByValue(actual, hash)
+	require.Equal(t, expect, actual)
+}
+
+func TestSortSliceByValueFail(t *testing.T) {
+	t.Run("empty slice", func(t *testing.T) {
+		var (
+			actual []int
+			hash   = Hash(testKey)
+		)
+		require.NotPanics(t, func() { SortSliceByValue(actual, hash) })
+	})
+
+	t.Run("must be slice", func(t *testing.T) {
+		actual := 10
+		hash := Hash(testKey)
+		require.Panics(t, func() { SortSliceByValue(actual, hash) })
+	})
+
+	t.Run("must 'fail' for unknown type", func(t *testing.T) {
+		actual := []unknown{1, 2, 3, 4, 5}
+		hash := Hash(testKey)
+		require.Panics(t, func() { SortSliceByValue(actual, hash) })
+	})
+}
+
+func TestSortSliceByValueHasher(t *testing.T) {
+	actual := []hashString{"a", "b", "c", "d", "e", "f"}
+	expect := []hashString{"d", "f", "c", "b", "a", "e"}
+	hash := Hash(testKey)
+	SortSliceByValue(actual, hash)
+	require.Equal(t, expect, actual)
+}
+
+func TestSortHasherSliceByValue(t *testing.T) {
+	actual := []hashString{"a", "b", "c", "d", "e", "f"}
+	expect := []hashString{"d", "f", "c", "b", "a", "e"}
+	hash := Hash(testKey)
+	SortHasherSliceByValue(actual, hash)
+	require.EqualValues(t, expect, actual)
+}
+
+func TestSortHasherSliceByWeightValue(t *testing.T) {
+	actual := []hashString{"a", "b", "c", "d", "e", "f"}
+	weights := []float64{1.0, 1.0, 1.0, 1.0, 1.0, 1.0}
+	expect := []hashString{"d", "f", "c", "b", "a", "e"}
+	hash := Hash(testKey)
+	SortHasherSliceByWeightValue(actual, weights, hash)
+	require.EqualValues(t, expect, actual)
+}
+
+func TestSortSliceByValueIntSlice(t *testing.T) {
+	cases := []slices{
+		{
+			actual: []int{0, 1, 2, 3, 4, 5},
+			expect: []int{2, 0, 5, 3, 1, 4},
+		},
+
+		{
+			actual: []uint{0, 1, 2, 3, 4, 5},
+			expect: []uint{2, 0, 5, 3, 1, 4},
+		},
+
+		{
+			actual: []int8{0, 1, 2, 3, 4, 5},
+			expect: []int8{5, 2, 1, 4, 0, 3},
+		},
+
+		{
+			actual: []uint8{0, 1, 2, 3, 4, 5},
+			expect: []uint8{5, 2, 1, 4, 0, 3},
+		},
+
+		{
+			actual: []int16{0, 1, 2, 3, 4, 5},
+			expect: []int16{1, 0, 3, 2, 4, 5},
+		},
+
+		{
+			actual: []uint16{0, 1, 2, 3, 4, 5},
+			expect: []uint16{1, 0, 3, 2, 4, 5},
+		},
+
+		{
+			actual: []int32{0, 1, 2, 3, 4, 5},
+			expect: []int32{5, 1, 2, 0, 3, 4},
+		},
+
+		{
+			actual: []uint32{0, 1, 2, 3, 4, 5},
+			expect: []uint32{5, 1, 2, 0, 3, 4},
+		},
+
+		{
+			actual: []int64{0, 1, 2, 3, 4, 5},
+			expect: []int64{5, 3, 0, 1, 4, 2},
+		},
+
+		{
+			actual: []uint64{0, 1, 2, 3, 4, 5},
+			expect: []uint64{5, 3, 0, 1, 4, 2},
+		},
+	}
+	hash := Hash(testKey)
+
+	for _, tc := range cases {
+		SortSliceByValue(tc.actual, hash)
+		require.Equal(t, tc.expect, tc.actual)
+	}
+}
+
+func TestSort(t *testing.T) {
+	nodes := []uint64{1, 2, 3, 4, 5}
+	hash := Hash(testKey)
+	actual := Sort(nodes, hash)
+	expected := []uint64{3, 1, 4, 2, 0}
+	require.Equal(t, expected, actual)
+}
+
+func TestDistribution(t *testing.T) {
+	const (
+		size    = 10
+		keys    = 100000
+		percent = 0.03
+	)
+	// We use χ2 method to determine similarity of distribution with uniform distribution.
+	// χ2 = Σ((n-N)**2/N)
+	// https://www.medcalc.org/manual/chi-square-table.php p=0.1
+	var chiTable = map[int]float64{9: 14.68, 99: 117.407}
+
+	t.Run("sort", func(t *testing.T) {
+		var (
+			i      uint64
+			nodes  [size]uint64
+			counts = make(map[uint64]uint64, size)
+			key    = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			nodes[i] = i
+		}
+
+		for i = 0; i < keys; i++ {
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			counts[Sort(nodes[:], hash)[0]]++
+		}
+
+		var chi2 float64
+		mean := float64(keys) / float64(size)
+		delta := mean * percent
+		for node, count := range counts {
+			d := mean - float64(count)
+			chi2 += math.Pow(float64(count)-mean, 2) / mean
+			require.True(t, d < delta && (0-d) < delta,
+				"Node %d received %d keys, expected %.0f (+/- %.2f)", node, count, mean, delta)
+		}
+		require.True(t, chi2 < chiTable[size-1],
+			"Chi2 condition for .9 is not met (expected %.2f <= %.2f)", chi2, chiTable[size-1])
+	})
+
+	t.Run("sortByIndex", func(t *testing.T) {
+		var (
+			i      uint64
+			a, b   [size]uint64
+			counts = make(map[uint64]int, size)
+			key    = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			a[i] = i
+		}
+
+		for i = 0; i < keys; i++ {
+			copy(b[:], a[:])
+
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			SortSliceByIndex(b[:], hash)
+			counts[b[0]]++
+		}
+
+		var chi2 float64
+		mean := float64(keys) / float64(size)
+		delta := mean * percent
+		for node, count := range counts {
+			d := mean - float64(count)
+			chi2 += math.Pow(float64(count)-mean, 2) / mean
+			require.True(t, d < delta && (0-d) < delta,
+				"Node %d received %d keys, expected %.0f (+/- %.2f)", node, count, mean, delta)
+		}
+		require.True(t, chi2 < chiTable[size-1],
+			"Chi2 condition for .9 is not met (expected %.2f <= %.2f)", chi2, chiTable[size-1])
+	})
+
+	t.Run("sortByValue", func(t *testing.T) {
+		var (
+			i      uint64
+			a, b   [size]int
+			counts = make(map[int]int, size)
+			key    = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			a[i] = int(i)
+		}
+
+		for i = 0; i < keys; i++ {
+			copy(b[:], a[:])
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			SortSliceByValue(b[:], hash)
+			counts[b[0]]++
+		}
+
+		var chi2 float64
+		mean := float64(keys) / float64(size)
+		delta := mean * percent
+		for node, count := range counts {
+			d := mean - float64(count)
+			chi2 += math.Pow(float64(count)-mean, 2) / mean
+			require.True(t, d < delta && (0-d) < delta,
+				"Node %d received %d keys, expected %.0f (+/- %.2f)", node, count, mean, delta)
+		}
+		require.True(t, chi2 < chiTable[size-1],
+			"Chi2 condition for .9 is not met (expected %.2f <= %.2f)", chi2, chiTable[size-1])
+	})
+
+	t.Run("sortByStringValue", func(t *testing.T) {
+		var (
+			i      uint64
+			a, b   [size]string
+			counts = make(map[string]int, size)
+			key    = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			a[i] = strconv.FormatUint(i, 10)
+		}
+
+		for i = 0; i < keys; i++ {
+			copy(b[:], a[:])
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			SortSliceByValue(b[:], hash)
+			counts[b[0]]++
+		}
+
+		var chi2 float64
+		mean := float64(keys) / float64(size)
+		delta := mean * percent
+		for node, count := range counts {
+			d := mean - float64(count)
+			chi2 += math.Pow(float64(count)-mean, 2) / mean
+			require.True(t, d < delta && (0-d) < delta,
+				"Node %d received %d keys, expected %.0f (+/- %.2f)", node, count, mean, delta)
+		}
+		require.True(t, chi2 < chiTable[size-1],
+			"Chi2 condition for .9 is not met (expected %.2f <= %.2f)", chi2, chiTable[size-1])
+	})
+
+	t.Run("sortByInt32Value", func(t *testing.T) {
+		var (
+			i      uint64
+			a, b   [size]int32
+			counts = make(map[int32]int, size)
+			key    = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			a[i] = int32(i)
+		}
+
+		for i = 0; i < keys; i++ {
+			copy(b[:], a[:])
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			SortSliceByValue(b[:], hash)
+			counts[b[0]]++
+		}
+
+		var chi2 float64
+		mean := float64(keys) / float64(size)
+		delta := mean * percent
+		for node, count := range counts {
+			d := mean - float64(count)
+			chi2 += math.Pow(float64(count)-mean, 2) / mean
+			require.True(t, d < delta && (0-d) < delta,
+				"Node %d received %d keys, expected %.0f (+/- %.2f)", node, count, mean, delta)
+		}
+		require.True(t, chi2 < chiTable[size-1],
+			"Chi2 condition for .9 is not met (expected %.2f <= %.2f)", chi2, chiTable[size-1])
+	})
+
+	t.Run("sortByWeightValue", func(t *testing.T) {
+		var (
+			i            uint64
+			a, b, result [size]int
+			w            [size]float64
+			key          = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			a[i] = int(i)
+			w[i] = float64(size-i) / float64(size)
+		}
+		for i = 0; i < keys; i++ {
+			copy(b[:], a[:])
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			SortSliceByWeightValue(b[:], w[:], hash)
+			result[b[0]]++
+		}
+
+		for i := 0; i < size-1; i++ {
+			require.True(t, bool(w[i] > w[i+1]) == bool(result[i] > result[i+1]),
+				"result array %v must be corresponded to weights %v", result, w)
+		}
+	})
+
+	t.Run("sortByWeightValueShuffledWeight", func(t *testing.T) {
+		var (
+			i            uint64
+			a, b, result [size]int
+			w            [size]float64
+			key          = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			a[i] = int(i)
+			w[i] = float64(size-i) / float64(size)
+		}
+
+		rand.Shuffle(size, func(i, j int) {
+			w[i], w[j] = w[j], w[i]
+		})
+		for i = 0; i < keys; i++ {
+			copy(b[:], a[:])
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			SortSliceByWeightValue(b[:], w[:], hash)
+			result[b[0]]++
+		}
+		for i := 0; i < size-1; i++ {
+			require.True(t, bool(w[i] > w[i+1]) == bool(result[i] > result[i+1]),
+				"result array %v must be corresponded to weights %v", result, w)
+		}
+	})
+
+	t.Run("sortByWeightValueEmptyWeight", func(t *testing.T) {
+		var (
+			i      uint64
+			a, b   [size]int
+			w      [size]float64
+			counts = make(map[int]int, size)
+			key    = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			a[i] = int(i)
+		}
+
+		for i = 0; i < keys; i++ {
+			copy(b[:], a[:])
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			SortSliceByWeightValue(b[:], w[:], hash)
+			counts[b[0]]++
+		}
+
+		var chi2 float64
+		mean := float64(keys) / float64(size)
+		delta := mean * percent
+		for node, count := range counts {
+			d := mean - float64(count)
+			chi2 += math.Pow(float64(count)-mean, 2) / mean
+			require.True(t, d < delta && (0-d) < delta,
+				"Node %d received %d keys, expected %.0f (+/- %.2f)", node, count, mean, delta)
+		}
+		require.True(t, chi2 < chiTable[size-1],
+			"Chi2 condition for .9 is not met (expected %.2f <= %.2f)", chi2, chiTable[size-1])
+	})
+
+	t.Run("sortByWeightValueUniformWeight", func(t *testing.T) {
+		var (
+			i      uint64
+			a, b   [size]int
+			w      [size]float64
+			counts = make(map[int]int, size)
+			key    = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			a[i] = int(i)
+			w[i] = 0.5
+		}
+
+		for i = 0; i < keys; i++ {
+			copy(b[:], a[:])
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			SortSliceByWeightValue(b[:], w[:], hash)
+			counts[b[0]]++
+		}
+
+		var chi2 float64
+		mean := float64(keys) / float64(size)
+		delta := mean * percent
+		for node, count := range counts {
+			d := mean - float64(count)
+			chi2 += math.Pow(float64(count)-mean, 2) / mean
+			require.True(t, d < delta && (0-d) < delta,
+				"Node %d received %d keys, expected %.0f (+/- %.2f)", node, count, mean, delta)
+		}
+		require.True(t, chi2 < chiTable[size-1],
+			"Chi2 condition for .9 is not met (expected %.2f <= %.2f)", chi2, chiTable[size-1])
+	})
+
+	t.Run("sortByWeightValueAbsoluteW", func(t *testing.T) {
+		const keys = 1
+		var (
+			i    uint64
+			a, b [size]int
+			w    [size]float64
+			key  = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			a[i] = int(i)
+		}
+		w[size-1] = 1
+
+		for i = 0; i < keys; i++ {
+			copy(b[:], a[:])
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			SortSliceByWeightValue(b[:], w[:], hash)
+			require.True(t, b[0] == a[size-1],
+				"expected last value of %v to be the first with highest distance", a)
+		}
+
+	})
+
+	t.Run("sortByWeightValueNormalizedWeight", func(t *testing.T) {
+		var (
+			i              uint64
+			a, b, result   [size]uint64
+			w, normalizedW [size]float64
+			key            = make([]byte, 16)
+		)
+
+		for i = 0; i < size; i++ {
+			a[i] = i
+			w[int(i)] = 10
+		}
+		w[0] = 100
+
+		// Here let's use logarithm normalization
+		for i = 0; i < size; i++ {
+			normalizedW[i] = math.Log2(w[i]) / math.Log2(w[0])
+		}
+
+		for i = 0; i < keys; i++ {
+			copy(b[:], a[:])
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			SortSliceByWeightValue(b[:], normalizedW[:], hash)
+			for j := range b {
+				result[b[j]] += uint64(len(b) - j)
+			}
+		}
+		cutResult := result[1:]
+		var total uint64
+		for i := range cutResult {
+			total += cutResult[i]
+		}
+
+		var chi2 float64
+		mean := float64(total) / float64(len(cutResult))
+		delta := mean * percent
+		for node, count := range cutResult {
+			d := mean - float64(count)
+			chi2 += math.Pow(float64(count)-mean, 2) / mean
+			require.True(t, d < delta && (0-d) < delta,
+				"Node %d received %d keys, expected %.0f (+/- %.2f)", node, count, mean, delta)
+		}
+		require.True(t, chi2 < chiTable[size-1],
+			"Chi2 condition for .9 is not met (expected %.2f <= %.2f)", chi2, chiTable[size-1])
+	})
+
+	t.Run("hash collision", func(t *testing.T) {
+		var (
+			i      uint64
+			counts = make(map[uint64]uint64)
+			key    = make([]byte, 16)
+		)
+
+		for i = 0; i < keys; i++ {
+			binary.BigEndian.PutUint64(key, i+size)
+			hash := Hash(key)
+			counts[hash]++
+		}
+
+		for node, count := range counts {
+			if count > 1 {
+				t.Errorf("Node %d received %d keys", node, count)
+			}
+		}
+	})
+}
+
+func BenchmarkSort_fnv_10(b *testing.B) {
+	hash := Hash(testKey)
+	_ = benchmarkSort(b, 10, hash)
+}
+
+func BenchmarkSort_fnv_100(b *testing.B) {
+	hash := Hash(testKey)
+	_ = benchmarkSort(b, 100, hash)
+}
+
+func BenchmarkSort_fnv_1000(b *testing.B) {
+	hash := Hash(testKey)
+	_ = benchmarkSort(b, 1000, hash)
+}
+
+func BenchmarkSortByIndex_fnv_10(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByIndex(b, 10, hash)
+}
+
+func BenchmarkSortByIndex_fnv_100(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByIndex(b, 100, hash)
+}
+
+func BenchmarkSortByIndex_fnv_1000(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByIndex(b, 1000, hash)
+}
+
+func BenchmarkSortByValue_fnv_10(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByValue(b, 10, hash)
+}
+
+func BenchmarkSortByValue_fnv_100(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByValue(b, 100, hash)
+}
+
+func BenchmarkSortByValue_fnv_1000(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByValue(b, 1000, hash)
+}
+
+func BenchmarkSortHashersByValue_Reflection_fnv_10(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortHashersByValueReflection(b, 10, hash)
+}
+
+func BenchmarkSortHashersByValue_Reflection_fnv_100(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortHashersByValueReflection(b, 100, hash)
+}
+
+func BenchmarkSortHashersByValue_Reflection_fnv_1000(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortHashersByValueReflection(b, 1000, hash)
+}
+
+func BenchmarkSortHashersByValue_Typed_fnv_10(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortHashersByValueTyped(b, 10, hash)
+}
+
+func BenchmarkSortHashersByValue_Typed_fnv_100(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortHashersByValueTyped(b, 100, hash)
+}
+
+func BenchmarkSortHashersByValue_Typed_fnv_1000(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortHashersByValueTyped(b, 1000, hash)
+}
+
+func BenchmarkSortByWeight_fnv_10(b *testing.B) {
+	hash := Hash(testKey)
+	_ = benchmarkSortByWeight(b, 10, hash)
+}
+
+func BenchmarkSortByWeight_fnv_100(b *testing.B) {
+	hash := Hash(testKey)
+	_ = benchmarkSortByWeight(b, 100, hash)
+}
+
+func BenchmarkSortByWeight_fnv_1000(b *testing.B) {
+	hash := Hash(testKey)
+	_ = benchmarkSortByWeight(b, 1000, hash)
+}
+
+func BenchmarkSortByWeightIndex_fnv_10(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByWeightIndex(b, 10, hash)
+}
+
+func BenchmarkSortByWeightIndex_fnv_100(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByWeightIndex(b, 100, hash)
+}
+
+func BenchmarkSortByWeightIndex_fnv_1000(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByWeightIndex(b, 1000, hash)
+}
+
+func BenchmarkSortByWeightValue_fnv_10(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByWeightValue(b, 10, hash)
+}
+
+func BenchmarkSortByWeightValue_fnv_100(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByWeightValue(b, 100, hash)
+}
+
+func BenchmarkSortByWeightValue_fnv_1000(b *testing.B) {
+	hash := Hash(testKey)
+	benchmarkSortByWeightValue(b, 1000, hash)
+}
+
+func BenchmarkSortHashersByWeightValueReflection_fnv_10(b *testing.B) {
+	benchmarkSortHashersByWeightValueRelection(b, 10, Hash(testKey))
+}
+
+func BenchmarkSortHashersByWeightValueReflection_fnv_100(b *testing.B) {
+	benchmarkSortHashersByWeightValueRelection(b, 100, Hash(testKey))
+}
+
+func BenchmarkSortHashersByWeightValueReflection_fnv_1000(b *testing.B) {
+	benchmarkSortHashersByWeightValueRelection(b, 1000, Hash(testKey))
+}
+
+func BenchmarkSortHashersByWeightValueTyped_fnv_10(b *testing.B) {
+	benchmarkSortHashersByWeightValueTyped(b, 10, Hash(testKey))
+}
+
+func BenchmarkSortHashersByWeightValueTyped_fnv_100(b *testing.B) {
+	benchmarkSortHashersByWeightValueTyped(b, 100, Hash(testKey))
+}
+
+func BenchmarkSortHashersByWeightValueTyped_fnv_1000(b *testing.B) {
+	benchmarkSortHashersByWeightValueTyped(b, 1000, Hash(testKey))
+}
+
+func benchmarkSort(b *testing.B, n int, hash uint64) uint64 {
+	servers := make([]uint64, n)
+	for i := uint64(0); i < uint64(len(servers)); i++ {
+		servers[i] = i
+	}
+
+	b.ResetTimer()
+	b.ReportAllocs()
+
+	var x uint64
+	for i := 0; i < b.N; i++ {
+		x += Sort(servers, hash)[0]
+	}
+	return x
+}
+
+func benchmarkSortByIndex(b *testing.B, n int, hash uint64) {
+	servers := make([]uint64, n)
+	for i := uint64(0); i < uint64(len(servers)); i++ {
+		servers[i] = i
+	}
+
+	b.ResetTimer()
+	b.ReportAllocs()
+
+	for i := 0; i < b.N; i++ {
+		SortSliceByIndex(servers, hash)
+	}
+}
+
+func benchmarkSortByValue(b *testing.B, n int, hash uint64) {
+	servers := make([]string, n)
+	for i := uint64(0); i < uint64(len(servers)); i++ {
+		servers[i] = "localhost:" + strconv.FormatUint(60000-i, 10)
+	}
+
+	b.ResetTimer()
+	b.ReportAllocs()
+
+	for i := 0; i < b.N; i++ {
+		SortSliceByValue(servers, hash)
+	}
+}
+
+func benchmarkSortByWeight(b *testing.B, n int, hash uint64) uint64 {
+	servers := make([]uint64, n)
+	weights := make([]float64, n)
+	for i := uint64(0); i < uint64(len(servers)); i++ {
+		weights[i] = float64(uint64(n)-i) / float64(n)
+		servers[i] = i
+	}
+
+	b.ResetTimer()
+	b.ReportAllocs()
+
+	var x uint64
+	for i := 0; i < b.N; i++ {
+		x += SortByWeight(servers, weights, hash)[0]
+	}
+	return x
+}
+
+func benchmarkSortByWeightIndex(b *testing.B, n int, hash uint64) {
+	servers := make([]uint64, n)
+	weights := make([]float64, n)
+	for i := uint64(0); i < uint64(len(servers)); i++ {
+		weights[i] = float64(uint64(n)-i) / float64(n)
+		servers[i] = i
+	}
+
+	b.ResetTimer()
+	b.ReportAllocs()
+
+	for i := 0; i < b.N; i++ {
+		SortSliceByWeightIndex(servers, weights, hash)
+	}
+}
+
+func benchmarkSortByWeightValue(b *testing.B, n int, hash uint64) {
+	servers := make([]string, n)
+	weights := make([]float64, n)
+	for i := uint64(0); i < uint64(len(servers)); i++ {
+		weights[i] = float64(uint64(n)-i) / float64(n)
+		servers[i] = "localhost:" + strconv.FormatUint(60000-i, 10)
+	}
+
+	b.ResetTimer()
+	b.ReportAllocs()
+
+	for i := 0; i < b.N; i++ {
+		SortSliceByWeightValue(servers, weights, hash)
+	}
+}
+
+func benchmarkSortHashersByWeightValueRelection(b *testing.B, n int, hash uint64) {
+	servers := make([]hashString, n)
+	weights := make([]float64, n)
+	for i := uint64(0); i < uint64(len(servers)); i++ {
+		weights[i] = float64(uint64(n)-i) / float64(n)
+		servers[i] = hashString("localhost:" + strconv.FormatUint(60000-i, 10))
+	}
+
+	b.ResetTimer()
+	b.ReportAllocs()
+
+	for i := 0; i < b.N; i++ {
+		SortSliceByWeightValue(servers, weights, hash)
+	}
+}
+
+func benchmarkSortHashersByWeightValueTyped(b *testing.B, n int, hash uint64) {
+	servers := make([]hashString, n)
+	weights := make([]float64, n)
+	for i := uint64(0); i < uint64(len(servers)); i++ {
+		weights[i] = float64(uint64(n)-i) / float64(n)
+		servers[i] = hashString("localhost:" + strconv.FormatUint(60000-i, 10))
+	}
+
+	b.ResetTimer()
+	b.ReportAllocs()
+
+	for i := 0; i < b.N; i++ {
+		SortHasherSliceByWeightValue(servers, weights, hash)
+	}
+}
+
+func benchmarkSortHashersByValueReflection(b *testing.B, n int, hash uint64) {
+	servers := make([]hashString, n)
+	for i := uint64(0); i < uint64(len(servers)); i++ {
+		servers[i] = hashString("localhost:" + strconv.FormatUint(60000-i, 10))
+	}
+
+	b.ResetTimer()
+	b.ReportAllocs()
+
+	for i := 0; i < b.N; i++ {
+		SortSliceByValue(servers, hash)
+	}
+}
+
+func benchmarkSortHashersByValueTyped(b *testing.B, n int, hash uint64) {
+	servers := make([]hashString, n)
+	for i := uint64(0); i < uint64(len(servers)); i++ {
+		servers[i] = hashString("localhost:" + strconv.FormatUint(60000-i, 10))
+	}
+
+	b.ResetTimer()
+	b.ReportAllocs()
+
+	for i := 0; i < b.N; i++ {
+		SortHasherSliceByValue(servers, hash)
+	}
+}