349 lines
7.8 KiB
Go
349 lines
7.8 KiB
Go
// Copyright 2015 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package prometheus
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import (
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"math"
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"math/rand"
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"reflect"
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"sort"
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"sync"
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"testing"
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"testing/quick"
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dto "github.com/prometheus/client_model/go"
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)
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func benchmarkHistogramObserve(w int, b *testing.B) {
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b.StopTimer()
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wg := new(sync.WaitGroup)
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wg.Add(w)
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g := new(sync.WaitGroup)
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g.Add(1)
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s := NewHistogram(HistogramOpts{})
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for i := 0; i < w; i++ {
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go func() {
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g.Wait()
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for i := 0; i < b.N; i++ {
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s.Observe(float64(i))
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}
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wg.Done()
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}()
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}
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b.StartTimer()
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g.Done()
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wg.Wait()
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}
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func BenchmarkHistogramObserve1(b *testing.B) {
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benchmarkHistogramObserve(1, b)
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}
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func BenchmarkHistogramObserve2(b *testing.B) {
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benchmarkHistogramObserve(2, b)
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}
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func BenchmarkHistogramObserve4(b *testing.B) {
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benchmarkHistogramObserve(4, b)
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}
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func BenchmarkHistogramObserve8(b *testing.B) {
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benchmarkHistogramObserve(8, b)
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}
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func benchmarkHistogramWrite(w int, b *testing.B) {
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b.StopTimer()
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wg := new(sync.WaitGroup)
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wg.Add(w)
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g := new(sync.WaitGroup)
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g.Add(1)
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s := NewHistogram(HistogramOpts{})
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for i := 0; i < 1000000; i++ {
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s.Observe(float64(i))
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}
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for j := 0; j < w; j++ {
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outs := make([]dto.Metric, b.N)
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go func(o []dto.Metric) {
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g.Wait()
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for i := 0; i < b.N; i++ {
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s.Write(&o[i])
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}
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wg.Done()
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}(outs)
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}
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b.StartTimer()
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g.Done()
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wg.Wait()
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}
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func BenchmarkHistogramWrite1(b *testing.B) {
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benchmarkHistogramWrite(1, b)
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}
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func BenchmarkHistogramWrite2(b *testing.B) {
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benchmarkHistogramWrite(2, b)
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}
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func BenchmarkHistogramWrite4(b *testing.B) {
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benchmarkHistogramWrite(4, b)
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}
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func BenchmarkHistogramWrite8(b *testing.B) {
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benchmarkHistogramWrite(8, b)
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}
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func TestHistogramNonMonotonicBuckets(t *testing.T) {
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testCases := map[string][]float64{
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"not strictly monotonic": {1, 2, 2, 3},
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"not monotonic at all": {1, 2, 4, 3, 5},
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"have +Inf in the middle": {1, 2, math.Inf(+1), 3},
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}
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for name, buckets := range testCases {
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func() {
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defer func() {
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if r := recover(); r == nil {
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t.Errorf("Buckets %v are %s but NewHistogram did not panic.", buckets, name)
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}
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}()
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_ = NewHistogram(HistogramOpts{
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Name: "test_histogram",
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Help: "helpless",
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Buckets: buckets,
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})
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}()
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}
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}
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// Intentionally adding +Inf here to test if that case is handled correctly.
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// Also, getCumulativeCounts depends on it.
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var testBuckets = []float64{-2, -1, -0.5, 0, 0.5, 1, 2, math.Inf(+1)}
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func TestHistogramConcurrency(t *testing.T) {
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if testing.Short() {
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t.Skip("Skipping test in short mode.")
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}
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rand.Seed(42)
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it := func(n uint32) bool {
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mutations := int(n%1e4 + 1e4)
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concLevel := int(n%5 + 1)
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total := mutations * concLevel
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var start, end sync.WaitGroup
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start.Add(1)
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end.Add(concLevel)
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sum := NewHistogram(HistogramOpts{
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Name: "test_histogram",
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Help: "helpless",
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Buckets: testBuckets,
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})
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allVars := make([]float64, total)
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var sampleSum float64
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for i := 0; i < concLevel; i++ {
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vals := make([]float64, mutations)
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for j := 0; j < mutations; j++ {
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v := rand.NormFloat64()
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vals[j] = v
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allVars[i*mutations+j] = v
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sampleSum += v
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}
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go func(vals []float64) {
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start.Wait()
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for _, v := range vals {
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sum.Observe(v)
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}
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end.Done()
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}(vals)
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}
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sort.Float64s(allVars)
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start.Done()
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end.Wait()
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m := &dto.Metric{}
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sum.Write(m)
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if got, want := int(*m.Histogram.SampleCount), total; got != want {
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t.Errorf("got sample count %d, want %d", got, want)
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}
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if got, want := *m.Histogram.SampleSum, sampleSum; math.Abs((got-want)/want) > 0.001 {
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t.Errorf("got sample sum %f, want %f", got, want)
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}
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wantCounts := getCumulativeCounts(allVars)
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if got, want := len(m.Histogram.Bucket), len(testBuckets)-1; got != want {
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t.Errorf("got %d buckets in protobuf, want %d", got, want)
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}
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for i, wantBound := range testBuckets {
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if i == len(testBuckets)-1 {
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break // No +Inf bucket in protobuf.
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}
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if gotBound := *m.Histogram.Bucket[i].UpperBound; gotBound != wantBound {
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t.Errorf("got bound %f, want %f", gotBound, wantBound)
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}
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if gotCount, wantCount := *m.Histogram.Bucket[i].CumulativeCount, wantCounts[i]; gotCount != wantCount {
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t.Errorf("got count %d, want %d", gotCount, wantCount)
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}
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}
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return true
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}
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if err := quick.Check(it, nil); err != nil {
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t.Error(err)
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}
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}
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func TestHistogramVecConcurrency(t *testing.T) {
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if testing.Short() {
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t.Skip("Skipping test in short mode.")
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}
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rand.Seed(42)
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objectives := make([]float64, 0, len(DefObjectives))
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for qu := range DefObjectives {
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objectives = append(objectives, qu)
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}
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sort.Float64s(objectives)
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it := func(n uint32) bool {
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mutations := int(n%1e4 + 1e4)
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concLevel := int(n%7 + 1)
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vecLength := int(n%3 + 1)
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var start, end sync.WaitGroup
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start.Add(1)
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end.Add(concLevel)
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his := NewHistogramVec(
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HistogramOpts{
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Name: "test_histogram",
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Help: "helpless",
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Buckets: []float64{-2, -1, -0.5, 0, 0.5, 1, 2, math.Inf(+1)},
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},
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[]string{"label"},
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)
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allVars := make([][]float64, vecLength)
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sampleSums := make([]float64, vecLength)
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for i := 0; i < concLevel; i++ {
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vals := make([]float64, mutations)
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picks := make([]int, mutations)
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for j := 0; j < mutations; j++ {
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v := rand.NormFloat64()
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vals[j] = v
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pick := rand.Intn(vecLength)
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picks[j] = pick
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allVars[pick] = append(allVars[pick], v)
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sampleSums[pick] += v
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}
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go func(vals []float64) {
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start.Wait()
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for i, v := range vals {
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his.WithLabelValues(string('A' + picks[i])).Observe(v)
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}
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end.Done()
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}(vals)
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}
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for _, vars := range allVars {
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sort.Float64s(vars)
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}
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start.Done()
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end.Wait()
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for i := 0; i < vecLength; i++ {
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m := &dto.Metric{}
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s := his.WithLabelValues(string('A' + i))
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s.(Histogram).Write(m)
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if got, want := len(m.Histogram.Bucket), len(testBuckets)-1; got != want {
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t.Errorf("got %d buckets in protobuf, want %d", got, want)
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}
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if got, want := int(*m.Histogram.SampleCount), len(allVars[i]); got != want {
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t.Errorf("got sample count %d, want %d", got, want)
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}
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if got, want := *m.Histogram.SampleSum, sampleSums[i]; math.Abs((got-want)/want) > 0.001 {
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t.Errorf("got sample sum %f, want %f", got, want)
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}
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wantCounts := getCumulativeCounts(allVars[i])
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for j, wantBound := range testBuckets {
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if j == len(testBuckets)-1 {
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break // No +Inf bucket in protobuf.
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}
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if gotBound := *m.Histogram.Bucket[j].UpperBound; gotBound != wantBound {
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t.Errorf("got bound %f, want %f", gotBound, wantBound)
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}
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if gotCount, wantCount := *m.Histogram.Bucket[j].CumulativeCount, wantCounts[j]; gotCount != wantCount {
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t.Errorf("got count %d, want %d", gotCount, wantCount)
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}
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}
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}
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return true
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}
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if err := quick.Check(it, nil); err != nil {
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t.Error(err)
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}
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}
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func getCumulativeCounts(vars []float64) []uint64 {
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counts := make([]uint64, len(testBuckets))
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for _, v := range vars {
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for i := len(testBuckets) - 1; i >= 0; i-- {
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if v > testBuckets[i] {
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break
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}
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counts[i]++
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}
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}
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return counts
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}
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func TestBuckets(t *testing.T) {
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got := LinearBuckets(-15, 5, 6)
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want := []float64{-15, -10, -5, 0, 5, 10}
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if !reflect.DeepEqual(got, want) {
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t.Errorf("linear buckets: got %v, want %v", got, want)
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}
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got = ExponentialBuckets(100, 1.2, 3)
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want = []float64{100, 120, 144}
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if !reflect.DeepEqual(got, want) {
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t.Errorf("linear buckets: got %v, want %v", got, want)
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}
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}
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