traefik/vendor/github.com/openzipkin-contrib/zipkin-go-opentracing/sample.go
2019-04-05 11:58:06 +02:00

99 lines
2.3 KiB
Go

package zipkintracer
import (
"math"
"math/rand"
"sync"
"time"
)
// Sampler functions return if a Zipkin span should be sampled, based on its
// traceID.
type Sampler func(id uint64) bool
func neverSample(_ uint64) bool { return false }
func alwaysSample(_ uint64) bool { return true }
// ModuloSampler provides a typical OpenTracing type Sampler.
func ModuloSampler(mod uint64) Sampler {
if mod < 2 {
return alwaysSample
}
return func(id uint64) bool {
return (id % mod) == 0
}
}
// NewBoundarySampler is appropriate for high-traffic instrumentation who
// provision random trace ids, and make the sampling decision only once.
// It defends against nodes in the cluster selecting exactly the same ids.
func NewBoundarySampler(rate float64, salt int64) Sampler {
if rate <= 0 {
return neverSample
}
if rate >= 1.0 {
return alwaysSample
}
var (
boundary = int64(rate * 10000)
usalt = uint64(salt)
)
return func(id uint64) bool {
return int64(math.Abs(float64(id^usalt)))%10000 < boundary
}
}
// NewCountingSampler is appropriate for low-traffic instrumentation or
// those who do not provision random trace ids. It is not appropriate for
// collectors as the sampling decision isn't idempotent (consistent based
// on trace id).
func NewCountingSampler(rate float64) Sampler {
if rate <= 0 {
return neverSample
}
if rate >= 1.0 {
return alwaysSample
}
var (
i = 0
outOf100 = int(rate*100 + math.Copysign(0.5, rate*100)) // for rounding float to int conversion instead of truncation
decisions = randomBitSet(100, outOf100, rand.New(rand.NewSource(time.Now().UnixNano())))
mtx = &sync.Mutex{}
)
return func(_ uint64) bool {
mtx.Lock()
defer mtx.Unlock()
result := decisions[i]
i++
if i == 100 {
i = 0
}
return result
}
}
/**
* Reservoir sampling algorithm borrowed from Stack Overflow.
*
* http://stackoverflow.com/questions/12817946/generate-a-random-bitset-with-n-1s
*/
func randomBitSet(size int, cardinality int, rnd *rand.Rand) []bool {
result := make([]bool, size)
chosen := make([]int, cardinality)
var i int
for i = 0; i < cardinality; i++ {
chosen[i] = i
result[i] = true
}
for ; i < size; i++ {
j := rnd.Intn(i + 1)
if j < cardinality {
result[chosen[j]] = false
result[i] = true
chosen[j] = i
}
}
return result
}