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481f4983f7
Part of https://github.com/open-telemetry/opentelemetry-go/issues/5249 This makes all existing types designed to implement the public Exemplar API public by moving most of `internal/exemplar` to `exemplar`. The only types that are not being made public are `exemplar.Drop`, and `exemplar.FilteredReservoir`. Those types are moved to `internal/aggregate`, and are renamed to `DropReservoir` and `FilteredExemplarReservoir`. The following types are made public: * `exemplar.Exemplar` * `exemplar.Filter` * `exemplar.SampledFilter` * `exemplar.AlwaysOnFilter` * `exemplar.HistogramReservoir` * `exemplar.FixedSizeReservoir` * `exemplar.Reservoir` * `exemplar.Value` * `exemplar.ValueType`
56 lines
1.3 KiB
Go
56 lines
1.3 KiB
Go
// Copyright The OpenTelemetry Authors
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// SPDX-License-Identifier: Apache-2.0
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package exemplar
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import (
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"context"
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"math"
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"math/rand"
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"slices"
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"testing"
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"time"
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"github.com/stretchr/testify/assert"
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)
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func TestNewFixedSizeReservoir(t *testing.T) {
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t.Run("Int64", ReservoirTest[int64](func(n int) (Reservoir, int) {
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return NewFixedSizeReservoir(n), n
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}))
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t.Run("Float64", ReservoirTest[float64](func(n int) (Reservoir, int) {
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return NewFixedSizeReservoir(n), n
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}))
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}
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func TestNewFixedSizeReservoirSamplingCorrectness(t *testing.T) {
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intensity := 0.1
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sampleSize := 1000
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rng := rand.New(rand.NewSource(time.Now().UnixNano()))
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data := make([]float64, sampleSize*1000)
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for i := range data {
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// Generate exponentially distributed data.
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data[i] = (-1.0 / intensity) * math.Log(rng.Float64())
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}
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// Sort to test position bias.
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slices.Sort(data)
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r := NewFixedSizeReservoir(sampleSize)
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for _, value := range data {
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r.Offer(context.Background(), staticTime, NewValue(value), nil)
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}
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var sum float64
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for _, m := range r.store {
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sum += m.Value.Float64()
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}
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mean := sum / float64(sampleSize)
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// Check the intensity/rate of the sampled distribution is preserved
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// ensuring no bias in our random sampling algorithm.
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assert.InDelta(t, 1/mean, intensity, 0.02) // Within 5σ.
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}
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