forked from mirror/client_golang
549 lines
15 KiB
Go
549 lines
15 KiB
Go
// Copyright 2015 The Prometheus Authors
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
package prometheus
|
|
|
|
import (
|
|
"math"
|
|
"math/rand"
|
|
"reflect"
|
|
"runtime"
|
|
"sort"
|
|
"sync"
|
|
"testing"
|
|
"testing/quick"
|
|
"time"
|
|
|
|
//nolint:staticcheck // Ignore SA1019. Need to keep deprecated package for compatibility.
|
|
"github.com/golang/protobuf/proto"
|
|
"github.com/golang/protobuf/ptypes"
|
|
|
|
dto "github.com/prometheus/client_model/go"
|
|
)
|
|
|
|
func benchmarkHistogramObserve(w int, b *testing.B) {
|
|
b.StopTimer()
|
|
|
|
wg := new(sync.WaitGroup)
|
|
wg.Add(w)
|
|
|
|
g := new(sync.WaitGroup)
|
|
g.Add(1)
|
|
|
|
s := NewHistogram(HistogramOpts{})
|
|
|
|
for i := 0; i < w; i++ {
|
|
go func() {
|
|
g.Wait()
|
|
|
|
for i := 0; i < b.N; i++ {
|
|
s.Observe(float64(i))
|
|
}
|
|
|
|
wg.Done()
|
|
}()
|
|
}
|
|
|
|
b.StartTimer()
|
|
g.Done()
|
|
wg.Wait()
|
|
}
|
|
|
|
func BenchmarkHistogramObserve1(b *testing.B) {
|
|
benchmarkHistogramObserve(1, b)
|
|
}
|
|
|
|
func BenchmarkHistogramObserve2(b *testing.B) {
|
|
benchmarkHistogramObserve(2, b)
|
|
}
|
|
|
|
func BenchmarkHistogramObserve4(b *testing.B) {
|
|
benchmarkHistogramObserve(4, b)
|
|
}
|
|
|
|
func BenchmarkHistogramObserve8(b *testing.B) {
|
|
benchmarkHistogramObserve(8, b)
|
|
}
|
|
|
|
func benchmarkHistogramWrite(w int, b *testing.B) {
|
|
b.StopTimer()
|
|
|
|
wg := new(sync.WaitGroup)
|
|
wg.Add(w)
|
|
|
|
g := new(sync.WaitGroup)
|
|
g.Add(1)
|
|
|
|
s := NewHistogram(HistogramOpts{})
|
|
|
|
for i := 0; i < 1000000; i++ {
|
|
s.Observe(float64(i))
|
|
}
|
|
|
|
for j := 0; j < w; j++ {
|
|
outs := make([]dto.Metric, b.N)
|
|
|
|
go func(o []dto.Metric) {
|
|
g.Wait()
|
|
|
|
for i := 0; i < b.N; i++ {
|
|
s.Write(&o[i])
|
|
}
|
|
|
|
wg.Done()
|
|
}(outs)
|
|
}
|
|
|
|
b.StartTimer()
|
|
g.Done()
|
|
wg.Wait()
|
|
}
|
|
|
|
func BenchmarkHistogramWrite1(b *testing.B) {
|
|
benchmarkHistogramWrite(1, b)
|
|
}
|
|
|
|
func BenchmarkHistogramWrite2(b *testing.B) {
|
|
benchmarkHistogramWrite(2, b)
|
|
}
|
|
|
|
func BenchmarkHistogramWrite4(b *testing.B) {
|
|
benchmarkHistogramWrite(4, b)
|
|
}
|
|
|
|
func BenchmarkHistogramWrite8(b *testing.B) {
|
|
benchmarkHistogramWrite(8, b)
|
|
}
|
|
|
|
func TestHistogramNonMonotonicBuckets(t *testing.T) {
|
|
testCases := map[string][]float64{
|
|
"not strictly monotonic": {1, 2, 2, 3},
|
|
"not monotonic at all": {1, 2, 4, 3, 5},
|
|
"have +Inf in the middle": {1, 2, math.Inf(+1), 3},
|
|
}
|
|
for name, buckets := range testCases {
|
|
func() {
|
|
defer func() {
|
|
if r := recover(); r == nil {
|
|
t.Errorf("Buckets %v are %s but NewHistogram did not panic.", buckets, name)
|
|
}
|
|
}()
|
|
_ = NewHistogram(HistogramOpts{
|
|
Name: "test_histogram",
|
|
Help: "helpless",
|
|
Buckets: buckets,
|
|
})
|
|
}()
|
|
}
|
|
}
|
|
|
|
// Intentionally adding +Inf here to test if that case is handled correctly.
|
|
// Also, getCumulativeCounts depends on it.
|
|
var testBuckets = []float64{-2, -1, -0.5, 0, 0.5, 1, 2, math.Inf(+1)}
|
|
|
|
func TestHistogramConcurrency(t *testing.T) {
|
|
if testing.Short() {
|
|
t.Skip("Skipping test in short mode.")
|
|
}
|
|
|
|
rand.Seed(42)
|
|
|
|
it := func(n uint32) bool {
|
|
mutations := int(n%1e4 + 1e4)
|
|
concLevel := int(n%5 + 1)
|
|
total := mutations * concLevel
|
|
|
|
var start, end sync.WaitGroup
|
|
start.Add(1)
|
|
end.Add(concLevel)
|
|
|
|
sum := NewHistogram(HistogramOpts{
|
|
Name: "test_histogram",
|
|
Help: "helpless",
|
|
Buckets: testBuckets,
|
|
})
|
|
|
|
allVars := make([]float64, total)
|
|
var sampleSum float64
|
|
for i := 0; i < concLevel; i++ {
|
|
vals := make([]float64, mutations)
|
|
for j := 0; j < mutations; j++ {
|
|
v := rand.NormFloat64()
|
|
vals[j] = v
|
|
allVars[i*mutations+j] = v
|
|
sampleSum += v
|
|
}
|
|
|
|
go func(vals []float64) {
|
|
start.Wait()
|
|
for _, v := range vals {
|
|
if n%2 == 0 {
|
|
sum.Observe(v)
|
|
} else {
|
|
sum.(ExemplarObserver).ObserveWithExemplar(v, Labels{"foo": "bar"})
|
|
}
|
|
}
|
|
end.Done()
|
|
}(vals)
|
|
}
|
|
sort.Float64s(allVars)
|
|
start.Done()
|
|
end.Wait()
|
|
|
|
m := &dto.Metric{}
|
|
sum.Write(m)
|
|
if got, want := int(*m.Histogram.SampleCount), total; got != want {
|
|
t.Errorf("got sample count %d, want %d", got, want)
|
|
}
|
|
if got, want := *m.Histogram.SampleSum, sampleSum; math.Abs((got-want)/want) > 0.001 {
|
|
t.Errorf("got sample sum %f, want %f", got, want)
|
|
}
|
|
|
|
wantCounts := getCumulativeCounts(allVars)
|
|
wantBuckets := len(testBuckets)
|
|
if !math.IsInf(m.Histogram.Bucket[len(m.Histogram.Bucket)-1].GetUpperBound(), +1) {
|
|
wantBuckets--
|
|
}
|
|
|
|
if got := len(m.Histogram.Bucket); got != wantBuckets {
|
|
t.Errorf("got %d buckets in protobuf, want %d", got, wantBuckets)
|
|
}
|
|
for i, wantBound := range testBuckets {
|
|
if i == len(testBuckets)-1 {
|
|
break // No +Inf bucket in protobuf.
|
|
}
|
|
if gotBound := *m.Histogram.Bucket[i].UpperBound; gotBound != wantBound {
|
|
t.Errorf("got bound %f, want %f", gotBound, wantBound)
|
|
}
|
|
if gotCount, wantCount := *m.Histogram.Bucket[i].CumulativeCount, wantCounts[i]; gotCount != wantCount {
|
|
t.Errorf("got count %d, want %d", gotCount, wantCount)
|
|
}
|
|
}
|
|
return true
|
|
}
|
|
|
|
if err := quick.Check(it, nil); err != nil {
|
|
t.Error(err)
|
|
}
|
|
}
|
|
|
|
func TestHistogramVecConcurrency(t *testing.T) {
|
|
if testing.Short() {
|
|
t.Skip("Skipping test in short mode.")
|
|
}
|
|
|
|
rand.Seed(42)
|
|
|
|
it := func(n uint32) bool {
|
|
mutations := int(n%1e4 + 1e4)
|
|
concLevel := int(n%7 + 1)
|
|
vecLength := int(n%3 + 1)
|
|
|
|
var start, end sync.WaitGroup
|
|
start.Add(1)
|
|
end.Add(concLevel)
|
|
|
|
his := NewHistogramVec(
|
|
HistogramOpts{
|
|
Name: "test_histogram",
|
|
Help: "helpless",
|
|
Buckets: []float64{-2, -1, -0.5, 0, 0.5, 1, 2, math.Inf(+1)},
|
|
},
|
|
[]string{"label"},
|
|
)
|
|
|
|
allVars := make([][]float64, vecLength)
|
|
sampleSums := make([]float64, vecLength)
|
|
for i := 0; i < concLevel; i++ {
|
|
vals := make([]float64, mutations)
|
|
picks := make([]int, mutations)
|
|
for j := 0; j < mutations; j++ {
|
|
v := rand.NormFloat64()
|
|
vals[j] = v
|
|
pick := rand.Intn(vecLength)
|
|
picks[j] = pick
|
|
allVars[pick] = append(allVars[pick], v)
|
|
sampleSums[pick] += v
|
|
}
|
|
|
|
go func(vals []float64) {
|
|
start.Wait()
|
|
for i, v := range vals {
|
|
his.WithLabelValues(string('A' + rune(picks[i]))).Observe(v)
|
|
}
|
|
end.Done()
|
|
}(vals)
|
|
}
|
|
for _, vars := range allVars {
|
|
sort.Float64s(vars)
|
|
}
|
|
start.Done()
|
|
end.Wait()
|
|
|
|
for i := 0; i < vecLength; i++ {
|
|
m := &dto.Metric{}
|
|
s := his.WithLabelValues(string('A' + rune(i)))
|
|
s.(Histogram).Write(m)
|
|
|
|
if got, want := len(m.Histogram.Bucket), len(testBuckets)-1; got != want {
|
|
t.Errorf("got %d buckets in protobuf, want %d", got, want)
|
|
}
|
|
if got, want := int(*m.Histogram.SampleCount), len(allVars[i]); got != want {
|
|
t.Errorf("got sample count %d, want %d", got, want)
|
|
}
|
|
if got, want := *m.Histogram.SampleSum, sampleSums[i]; math.Abs((got-want)/want) > 0.001 {
|
|
t.Errorf("got sample sum %f, want %f", got, want)
|
|
}
|
|
|
|
wantCounts := getCumulativeCounts(allVars[i])
|
|
|
|
for j, wantBound := range testBuckets {
|
|
if j == len(testBuckets)-1 {
|
|
break // No +Inf bucket in protobuf.
|
|
}
|
|
if gotBound := *m.Histogram.Bucket[j].UpperBound; gotBound != wantBound {
|
|
t.Errorf("got bound %f, want %f", gotBound, wantBound)
|
|
}
|
|
if gotCount, wantCount := *m.Histogram.Bucket[j].CumulativeCount, wantCounts[j]; gotCount != wantCount {
|
|
t.Errorf("got count %d, want %d", gotCount, wantCount)
|
|
}
|
|
}
|
|
}
|
|
return true
|
|
}
|
|
|
|
if err := quick.Check(it, nil); err != nil {
|
|
t.Error(err)
|
|
}
|
|
}
|
|
|
|
func getCumulativeCounts(vars []float64) []uint64 {
|
|
counts := make([]uint64, len(testBuckets))
|
|
for _, v := range vars {
|
|
for i := len(testBuckets) - 1; i >= 0; i-- {
|
|
if v > testBuckets[i] {
|
|
break
|
|
}
|
|
counts[i]++
|
|
}
|
|
}
|
|
return counts
|
|
}
|
|
|
|
func TestBuckets(t *testing.T) {
|
|
got := LinearBuckets(-15, 5, 6)
|
|
want := []float64{-15, -10, -5, 0, 5, 10}
|
|
if !reflect.DeepEqual(got, want) {
|
|
t.Errorf("linear buckets: got %v, want %v", got, want)
|
|
}
|
|
|
|
got = ExponentialBuckets(100, 1.2, 3)
|
|
want = []float64{100, 120, 144}
|
|
if !reflect.DeepEqual(got, want) {
|
|
t.Errorf("exponential buckets: got %v, want %v", got, want)
|
|
}
|
|
}
|
|
|
|
func TestHistogramAtomicObserve(t *testing.T) {
|
|
var (
|
|
quit = make(chan struct{})
|
|
his = NewHistogram(HistogramOpts{
|
|
Buckets: []float64{0.5, 10, 20},
|
|
})
|
|
)
|
|
|
|
defer func() { close(quit) }()
|
|
|
|
observe := func() {
|
|
for {
|
|
select {
|
|
case <-quit:
|
|
return
|
|
default:
|
|
his.Observe(1)
|
|
}
|
|
}
|
|
}
|
|
|
|
go observe()
|
|
go observe()
|
|
go observe()
|
|
|
|
for i := 0; i < 100; i++ {
|
|
m := &dto.Metric{}
|
|
if err := his.Write(m); err != nil {
|
|
t.Fatal("unexpected error writing histogram:", err)
|
|
}
|
|
h := m.GetHistogram()
|
|
if h.GetSampleCount() != uint64(h.GetSampleSum()) ||
|
|
h.GetSampleCount() != h.GetBucket()[1].GetCumulativeCount() ||
|
|
h.GetSampleCount() != h.GetBucket()[2].GetCumulativeCount() {
|
|
t.Fatalf(
|
|
"inconsistent counts in histogram: count=%d sum=%f buckets=[%d, %d]",
|
|
h.GetSampleCount(), h.GetSampleSum(),
|
|
h.GetBucket()[1].GetCumulativeCount(), h.GetBucket()[2].GetCumulativeCount(),
|
|
)
|
|
}
|
|
runtime.Gosched()
|
|
}
|
|
}
|
|
|
|
func TestHistogramExemplar(t *testing.T) {
|
|
now := time.Now()
|
|
|
|
histogram := NewHistogram(HistogramOpts{
|
|
Name: "test",
|
|
Help: "test help",
|
|
Buckets: []float64{1, 2, 3, 4},
|
|
}).(*histogram)
|
|
histogram.now = func() time.Time { return now }
|
|
|
|
ts, err := ptypes.TimestampProto(now)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
expectedExemplars := []*dto.Exemplar{
|
|
nil,
|
|
&dto.Exemplar{
|
|
Label: []*dto.LabelPair{
|
|
&dto.LabelPair{Name: proto.String("id"), Value: proto.String("2")},
|
|
},
|
|
Value: proto.Float64(1.6),
|
|
Timestamp: ts,
|
|
},
|
|
nil,
|
|
&dto.Exemplar{
|
|
Label: []*dto.LabelPair{
|
|
&dto.LabelPair{Name: proto.String("id"), Value: proto.String("3")},
|
|
},
|
|
Value: proto.Float64(4),
|
|
Timestamp: ts,
|
|
},
|
|
&dto.Exemplar{
|
|
Label: []*dto.LabelPair{
|
|
&dto.LabelPair{Name: proto.String("id"), Value: proto.String("4")},
|
|
},
|
|
Value: proto.Float64(4.5),
|
|
Timestamp: ts,
|
|
},
|
|
}
|
|
|
|
histogram.ObserveWithExemplar(1.5, Labels{"id": "1"})
|
|
histogram.ObserveWithExemplar(1.6, Labels{"id": "2"}) // To replace exemplar in bucket 0.
|
|
histogram.ObserveWithExemplar(4, Labels{"id": "3"})
|
|
histogram.ObserveWithExemplar(4.5, Labels{"id": "4"}) // Should go to +Inf bucket.
|
|
|
|
for i, ex := range histogram.exemplars {
|
|
var got, expected string
|
|
if val := ex.Load(); val != nil {
|
|
got = val.(*dto.Exemplar).String()
|
|
}
|
|
if expectedExemplars[i] != nil {
|
|
expected = expectedExemplars[i].String()
|
|
}
|
|
if got != expected {
|
|
t.Errorf("expected exemplar %s, got %s.", expected, got)
|
|
}
|
|
}
|
|
}
|
|
|
|
func TestSparseHistogram(t *testing.T) {
|
|
|
|
scenarios := []struct {
|
|
name string
|
|
observations []float64
|
|
factor float64
|
|
zeroThreshold float64
|
|
want string // String representation of protobuf.
|
|
}{
|
|
{
|
|
name: "no sparse buckets",
|
|
observations: []float64{1, 2, 3},
|
|
factor: 1,
|
|
want: `sample_count:3 sample_sum:6 bucket:<cumulative_count:0 upper_bound:0.005 > bucket:<cumulative_count:0 upper_bound:0.01 > bucket:<cumulative_count:0 upper_bound:0.025 > bucket:<cumulative_count:0 upper_bound:0.05 > bucket:<cumulative_count:0 upper_bound:0.1 > bucket:<cumulative_count:0 upper_bound:0.25 > bucket:<cumulative_count:0 upper_bound:0.5 > bucket:<cumulative_count:1 upper_bound:1 > bucket:<cumulative_count:2 upper_bound:2.5 > bucket:<cumulative_count:3 upper_bound:5 > bucket:<cumulative_count:3 upper_bound:10 > sb_schema:0 sb_zero_threshold:0 `, // Has conventional buckets because there are no sparse buckets.
|
|
},
|
|
{
|
|
name: "factor 1.1 results in schema 3",
|
|
observations: []float64{0, 1, 2, 3},
|
|
factor: 1.1,
|
|
want: `sample_count:4 sample_sum:6 sb_schema:3 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_positive:<span:<offset:0 length:1 > span:<offset:7 length:1 > span:<offset:4 length:1 > delta:1 delta:0 delta:0 > `,
|
|
},
|
|
{
|
|
name: "factor 1.2 results in schema 2",
|
|
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2},
|
|
factor: 1.2,
|
|
want: `sample_count:6 sample_sum:7.4 sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_positive:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > `,
|
|
},
|
|
{
|
|
name: "negative buckets",
|
|
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2},
|
|
factor: 1.2,
|
|
want: `sample_count:6 sample_sum:-7.4 sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_negative:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > `,
|
|
},
|
|
{
|
|
name: "negative and positive buckets",
|
|
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2, 1, 1.2, 1.4, 1.8, 2},
|
|
factor: 1.2,
|
|
want: `sample_count:11 sample_sum:0 sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_negative:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > sb_positive:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > `,
|
|
},
|
|
{
|
|
name: "wide zero bucket",
|
|
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2, 1, 1.2, 1.4, 1.8, 2},
|
|
factor: 1.2,
|
|
zeroThreshold: 1.4,
|
|
want: `sample_count:11 sample_sum:0 sb_schema:2 sb_zero_threshold:1.4 sb_zero_count:7 sb_negative:<span:<offset:4 length:1 > delta:2 > sb_positive:<span:<offset:4 length:1 > delta:2 > `,
|
|
},
|
|
{
|
|
name: "NaN observation",
|
|
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.NaN()},
|
|
factor: 1.2,
|
|
want: `sample_count:7 sample_sum:nan sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_positive:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > `,
|
|
},
|
|
{
|
|
name: "+Inf observation",
|
|
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(+1)},
|
|
factor: 1.2,
|
|
want: `sample_count:7 sample_sum:inf sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_positive:<span:<offset:0 length:5 > span:<offset:2147483642 length:1 > delta:1 delta:-1 delta:2 delta:-2 delta:2 delta:-1 > `,
|
|
},
|
|
{
|
|
name: "-Inf observation",
|
|
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(-1)},
|
|
factor: 1.2,
|
|
want: `sample_count:7 sample_sum:-inf sb_schema:2 sb_zero_threshold:2.938735877055719e-39 sb_zero_count:1 sb_negative:<span:<offset:2147483647 length:1 > delta:1 > sb_positive:<span:<offset:0 length:5 > delta:1 delta:-1 delta:2 delta:-2 delta:2 > `,
|
|
},
|
|
}
|
|
|
|
for _, s := range scenarios {
|
|
t.Run(s.name, func(t *testing.T) {
|
|
his := NewHistogram(HistogramOpts{
|
|
Name: "name",
|
|
Help: "help",
|
|
SparseBucketsFactor: s.factor,
|
|
SparseBucketsZeroThreshold: s.zeroThreshold,
|
|
})
|
|
for _, o := range s.observations {
|
|
his.Observe(o)
|
|
}
|
|
m := &dto.Metric{}
|
|
if err := his.Write(m); err != nil {
|
|
t.Fatal("unexpected error writing metric", err)
|
|
}
|
|
got := m.Histogram.String()
|
|
if s.want != got {
|
|
t.Errorf("want histogram %q, got %q", s.want, got)
|
|
}
|
|
})
|
|
}
|
|
|
|
}
|