9dc7358869
* allow exposing meta information for registered metrics New public method `ExposeMetadata` allows enabling exposition of dummy meta-info for all exposed metrics across all Sets. This feature is needed to improve compatibility with 3rd-party scrapers that require meta information to be present. This commit doesn't update exposition of default system/process metrics to keep the list of changes small. This change should be added in a follow-up commit. https://github.com/VictoriaMetrics/metrics/issues/48 * cleanup * wip * wip * wip * wip --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com> |
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| .. | ||
| .travis.yml | ||
| fastrand.go | ||
| LICENSE | ||
| README.md | ||
fastrand
Fast pseudorandom number generator.
Features
- Optimized for speed.
- Performance scales on multiple CPUs.
How does it work?
It abuses sync.Pool for maintaining "per-CPU" pseudorandom number generators.
TODO: firgure out how to use real per-CPU pseudorandom number generators.
Benchmark results
$ GOMAXPROCS=1 go test -bench=. github.com/valyala/fastrand
goos: linux
goarch: amd64
pkg: github.com/valyala/fastrand
BenchmarkUint32n 50000000 29.7 ns/op
BenchmarkRNGUint32n 200000000 6.50 ns/op
BenchmarkRNGUint32nWithLock 100000000 21.5 ns/op
BenchmarkMathRandInt31n 50000000 31.8 ns/op
BenchmarkMathRandRNGInt31n 100000000 17.9 ns/op
BenchmarkMathRandRNGInt31nWithLock 50000000 30.2 ns/op
PASS
ok github.com/valyala/fastrand 10.634s
$ GOMAXPROCS=2 go test -bench=. github.com/valyala/fastrand
goos: linux
goarch: amd64
pkg: github.com/valyala/fastrand
BenchmarkUint32n-2 100000000 17.6 ns/op
BenchmarkRNGUint32n-2 500000000 3.36 ns/op
BenchmarkRNGUint32nWithLock-2 50000000 32.0 ns/op
BenchmarkMathRandInt31n-2 20000000 51.2 ns/op
BenchmarkMathRandRNGInt31n-2 100000000 11.0 ns/op
BenchmarkMathRandRNGInt31nWithLock-2 20000000 91.0 ns/op
PASS
ok github.com/valyala/fastrand 9.543s
$ GOMAXPROCS=4 go test -bench=. github.com/valyala/fastrand
goos: linux
goarch: amd64
pkg: github.com/valyala/fastrand
BenchmarkUint32n-4 100000000 14.2 ns/op
BenchmarkRNGUint32n-4 500000000 3.30 ns/op
BenchmarkRNGUint32nWithLock-4 20000000 88.7 ns/op
BenchmarkMathRandInt31n-4 10000000 145 ns/op
BenchmarkMathRandRNGInt31n-4 200000000 8.35 ns/op
BenchmarkMathRandRNGInt31nWithLock-4 20000000 102 ns/op
PASS
ok github.com/valyala/fastrand 11.534s
As you can see, fastrand.Uint32n
scales on multiple CPUs, while rand.Int31n
doesn't scale. Their performance is comparable on GOMAXPROCS=1,
but fastrand.Uint32n runs 3x faster than rand.Int31n on GOMAXPROCS=2
and 10x faster than rand.Int31n on GOMAXPROCS=4.