WIP: Golang HRW implementation
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Alex Vanin aa230933d1
Move normalization routine out of hrw library (#6)
HRW library supports weighted sorting. Weights must be normalized
before applying. Since there could be different types of normalization
for multiple criteria, there is no point to perform simple
normalization in this library. Pass a slice of normalized weights
to the `SortByWeight` functions.

This commit proposes to:
- remove normalization routine from `SortByWeight` function;
- add `ValidateWeights` function to check if weights are normalized;
- rename `weight` -> `distance` to avoid naming confusion between
  hash distance and actual weights;
- use testify lib in the tests;
2019-07-05 09:49:24 +03:00
.gitignore Base HRW implementation in golang 2019-01-30 01:58:30 +03:00
.travis.yml Small refactoring (#2) 2019-03-14 15:48:58 +03:00
go.mod Move normalization routine out of hrw library (#6) 2019-07-05 09:49:24 +03:00
go.sum Move normalization routine out of hrw library (#6) 2019-07-05 09:49:24 +03:00
hrw.go Move normalization routine out of hrw library (#6) 2019-07-05 09:49:24 +03:00
hrw_test.go Move normalization routine out of hrw library (#6) 2019-07-05 09:49:24 +03:00
LICENSE Move repo to NSPCC (#1) 2019-02-01 14:30:34 +03:00
README.md Move normalization routine out of hrw library (#6) 2019-07-05 09:49:24 +03:00

Golang HRW implementation

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Rendezvous or highest random weight (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 github.com/nspcc-dev/hrw

Benchmark:

BenchmarkSort_fnv_10-8                           5000000               365 ns/op             224 B/op          3 allocs/op
BenchmarkSort_fnv_100-8                           300000              5261 ns/op            1856 B/op          3 allocs/op
BenchmarkSort_fnv_1000-8                           10000            119462 ns/op           16448 B/op          3 allocs/op
BenchmarkSortByIndex_fnv_10-8                    3000000               546 ns/op             384 B/op          7 allocs/op
BenchmarkSortByIndex_fnv_100-8                    200000              5965 ns/op            2928 B/op          7 allocs/op
BenchmarkSortByIndex_fnv_1000-8                    10000            127732 ns/op           25728 B/op          7 allocs/op
BenchmarkSortByValue_fnv_10-8                    2000000               962 ns/op             544 B/op         17 allocs/op
BenchmarkSortByValue_fnv_100-8                    200000              9604 ns/op            4528 B/op        107 allocs/op
BenchmarkSortByValue_fnv_1000-8                    10000            111741 ns/op           41728 B/op       1007 allocs/op

BenchmarkSortByWeight_fnv_10-8                   3000000               501 ns/op             320 B/op          4 allocs/op
BenchmarkSortByWeight_fnv_100-8                   200000              8495 ns/op            2768 B/op          4 allocs/op
BenchmarkSortByWeight_fnv_1000-8                   10000            197880 ns/op           24656 B/op          4 allocs/op
BenchmarkSortByWeightIndex_fnv_10-8              2000000               702 ns/op             480 B/op          8 allocs/op
BenchmarkSortByWeightIndex_fnv_100-8              200000              9338 ns/op            3840 B/op          8 allocs/op
BenchmarkSortByWeightIndex_fnv_1000-8              10000            204669 ns/op           33936 B/op          8 allocs/op
BenchmarkSortByWeightValue_fnv_10-8              1000000              1083 ns/op             640 B/op         18 allocs/op
BenchmarkSortByWeightValue_fnv_100-8              200000             11444 ns/op            5440 B/op        108 allocs/op
BenchmarkSortByWeightValue_fnv_1000-8              10000            148471 ns/op           49936 B/op       1008 allocs/op

Example

package main

import (
	"fmt"
	
	"github.com/nspcc-dev/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
}