forked from TrueCloudLab/hrw
58a8ce4e47
* Added weighted HRW sorting This commit proposes renaming of old `SortByWeight` functions to `Sort` and implementation of `SortByWeight` function with explicit weights in arguments. `SortByWeight` function calculates normalized hashes of nodes and normalized input weights. Then multiplies these values to obtain node's actual weight for later sorting. - renamed `SortByWeight` function to `Sort` - added `SortByWeight`, `SortSliceByWeightValue` and `SortSliceBeWeightIndex` functions - moved code with reflection processing into `prepareRule` function - added tests and benchmarks for new weighted functions - added benchmark results into README * Fixed comments
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81 lines
No EOL
4 KiB
Markdown
# Golang HRW implementation
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[](https://travis-ci.org/nspcc-dev/hrw)
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[](https://codecov.io/gh/nspcc-dev/hrw)
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[](https://goreportcard.com/report/github.com/nspcc-dev/hrw)
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[](https://github.com/nspcc-dev/hrw)
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[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.
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## Install
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`go get github.com/nspcc-dev/hrw`
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## Benchmark:
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```
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BenchmarkSort_fnv_10-8 5000000 354 ns/op 224 B/op 3 allocs/op
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BenchmarkSort_fnv_100-8 300000 5103 ns/op 1856 B/op 3 allocs/op
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BenchmarkSort_fnv_1000-8 10000 115874 ns/op 16448 B/op 3 allocs/op
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BenchmarkSortByIndex_fnv_10-8 3000000 562 ns/op 384 B/op 7 allocs/op
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BenchmarkSortByIndex_fnv_100-8 200000 5819 ns/op 2928 B/op 7 allocs/op
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BenchmarkSortByIndex_fnv_1000-8 10000 125859 ns/op 25728 B/op 7 allocs/op
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BenchmarkSortByValue_fnv_10-8 2000000 1056 ns/op 544 B/op 17 allocs/op
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BenchmarkSortByValue_fnv_100-8 200000 9593 ns/op 4528 B/op 107 allocs/op
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BenchmarkSortByValue_fnv_1000-8 10000 109272 ns/op 41728 B/op 1007 allocs/op
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BenchmarkSortByWeight_fnv_10-8 3000000 500 ns/op 320 B/op 4 allocs/op
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BenchmarkSortByWeight_fnv_100-8 200000 8257 ns/op 2768 B/op 4 allocs/op
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BenchmarkSortByWeight_fnv_1000-8 10000 197938 ns/op 24656 B/op 4 allocs/op
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BenchmarkSortByWeightIndex_fnv_10-8 2000000 760 ns/op 480 B/op 8 allocs/op
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BenchmarkSortByWeightIndex_fnv_100-8 200000 9191 ns/op 3840 B/op 8 allocs/op
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BenchmarkSortByWeightIndex_fnv_1000-8 10000 208204 ns/op 33936 B/op 8 allocs/op
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BenchmarkSortByWeightValue_fnv_10-8 1000000 1095 ns/op 640 B/op 18 allocs/op
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BenchmarkSortByWeightValue_fnv_100-8 200000 12291 ns/op 5440 B/op 108 allocs/op
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BenchmarkSortByWeightValue_fnv_1000-8 10000 145125 ns/op 49936 B/op 1008 allocs/op
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```
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## Example
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```go
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package main
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import (
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"fmt"
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"github.com/nspcc-dev/hrw"
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)
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func main() {
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// given a set of servers
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servers := []string{
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"one.example.com",
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"two.example.com",
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"three.example.com",
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"four.example.com",
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"five.example.com",
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"six.example.com",
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}
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// HRW can consistently select a uniformly-distributed set of servers for
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// any given key
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var (
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key = []byte("/examples/object-key")
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h = hrw.Hash(key)
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)
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hrw.SortSliceByValue(servers, h)
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for id := range servers {
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fmt.Printf("trying GET %s%s\n", servers[id], key)
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}
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// Output:
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// trying GET four.example.com/examples/object-key
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// trying GET three.example.com/examples/object-key
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// trying GET one.example.com/examples/object-key
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// trying GET two.example.com/examples/object-key
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// trying GET six.example.com/examples/object-key
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// trying GET five.example.com/examples/object-key
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}
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``` |