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8 Commits

Author SHA1 Message Date
Shivanth MP 45b69a2c78
Merge ae8497940d into 13851e9287 2024-11-13 14:20:00 +01:00
Shivanth ae8497940d Add native histograms
Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Apply suggestions from code review

Co-authored-by: Arthur Silva Sens <arthursens2005@gmail.com>
Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Fix references and existing tests

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Review comments

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

fmt

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

validation

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Count validation

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Validation

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Review comments

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Space formatting

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Review comments

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Rename SyncMaptoMap -> SyncMapToMap

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Remove exemplars from parameters for constNativeHistogram function

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Update prometheus/histogram.go

Co-authored-by: George Krajcsovits <krajorama@users.noreply.github.com>
Signed-off-by: Shivanth MP <shivanth.metchem@deliveryhero.com>

Update prometheus/histogram.go

Co-authored-by: George Krajcsovits <krajorama@users.noreply.github.com>
Signed-off-by: Shivanth MP <shivanth.metchem@deliveryhero.com>

Update prometheus/histogram.go

Co-authored-by: George Krajcsovits <krajorama@users.noreply.github.com>
Signed-off-by: Shivanth MP <shivanth.metchem@deliveryhero.com>

Update prometheus/histogram.go

Co-authored-by: Björn Rabenstein <github@rabenste.in>
Signed-off-by: Shivanth MP <shivanth.metchem@deliveryhero.com>

Review comments

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>

Lint fix

Signed-off-by: Shivanth <shivanth.metchem@deliveryhero.com>
2024-11-13 14:19:40 +01:00
PrometheusBot 13851e9287
Update common Prometheus files (#1683)
Signed-off-by: prombot <prometheus-team@googlegroups.com>
2024-11-12 20:02:43 +00:00
Ivan Goncharov a934c35951
Add: exponential backoff for CAS operations on floats (#1661)
* add: exponential backoff for CAS operations of floats

Signed-off-by: Ivan Goncharov <i.morph@gmail.com>

* add: some more benchmark use cases (higher contention)

Signed-off-by: Ivan Goncharov <i.morph@gmail.com>

* fmt: fumpted some files

Signed-off-by: Ivan Goncharov <i.morph@gmail.com>

* add: license header

Signed-off-by: Ivan Goncharov <i.morph@gmail.com>

* add: comment explaining origin of backoff constants

Signed-off-by: Ivan Goncharov <i.morph@gmail.com>

---------

Signed-off-by: Ivan Goncharov <i.morph@gmail.com>
2024-11-11 16:26:17 +00:00
Matthieu MOREL bab92a7743
chore: enable usestdlibvars linter (#1680)
Signed-off-by: Matthieu MOREL <matthieu.morel35@gmail.com>
2024-11-11 15:19:33 +01:00
PrometheusBot 400ee29a10
Update common Prometheus files (#1679)
Signed-off-by: prombot <prometheus-team@googlegroups.com>
2024-11-11 15:09:29 +01:00
Arthur Silva Sens 2b11a4ba39
Merge pull request #1673 from imorph/faster_find_bucket
PERF: faster algorithm to discover bucket of an histogram observation
2024-11-08 07:22:56 -03:00
Ivan Goncharov 78d7a94e46 add: linear search implementation (+ benchmarks)
Signed-off-by: Ivan Goncharov <i.morph@gmail.com>
2024-11-04 20:26:59 +01:00
14 changed files with 1112 additions and 63 deletions

View File

@ -36,4 +36,4 @@ jobs:
uses: golangci/golangci-lint-action@971e284b6050e8a5849b72094c50ab08da042db8 # v6.1.1
with:
args: --verbose
version: v1.60.2
version: v1.61.0

View File

@ -31,6 +31,7 @@ linters:
- staticcheck
- unconvert
- unused
- usestdlibvars
- wastedassign
issues:

View File

@ -61,7 +61,7 @@ PROMU_URL := https://github.com/prometheus/promu/releases/download/v$(PROMU_
SKIP_GOLANGCI_LINT :=
GOLANGCI_LINT :=
GOLANGCI_LINT_OPTS ?=
GOLANGCI_LINT_VERSION ?= v1.60.2
GOLANGCI_LINT_VERSION ?= v1.61.0
# golangci-lint only supports linux, darwin and windows platforms on i386/amd64/arm64.
# windows isn't included here because of the path separator being different.
ifeq ($(GOHOSTOS),$(filter $(GOHOSTOS),linux darwin))

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@ -0,0 +1,50 @@
// Copyright 2014 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"
"sync/atomic"
"time"
)
// atomicUpdateFloat atomically updates the float64 value pointed to by bits
// using the provided updateFunc, with an exponential backoff on contention.
func atomicUpdateFloat(bits *uint64, updateFunc func(float64) float64) {
const (
// both numbers are derived from empirical observations
// documented in this PR: https://github.com/prometheus/client_golang/pull/1661
maxBackoff = 320 * time.Millisecond
initialBackoff = 10 * time.Millisecond
)
backoff := initialBackoff
for {
loadedBits := atomic.LoadUint64(bits)
oldFloat := math.Float64frombits(loadedBits)
newFloat := updateFunc(oldFloat)
newBits := math.Float64bits(newFloat)
if atomic.CompareAndSwapUint64(bits, loadedBits, newBits) {
break
} else {
// Exponential backoff with sleep and cap to avoid infinite wait
time.Sleep(backoff)
backoff *= 2
if backoff > maxBackoff {
backoff = maxBackoff
}
}
}
}

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@ -0,0 +1,167 @@
// Copyright 2014 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"
"sync"
"sync/atomic"
"testing"
"unsafe"
)
var output float64
func TestAtomicUpdateFloat(t *testing.T) {
var val float64 = 0.0
bits := (*uint64)(unsafe.Pointer(&val))
var wg sync.WaitGroup
numGoroutines := 100000
increment := 1.0
for i := 0; i < numGoroutines; i++ {
wg.Add(1)
go func() {
defer wg.Done()
atomicUpdateFloat(bits, func(f float64) float64 {
return f + increment
})
}()
}
wg.Wait()
expected := float64(numGoroutines) * increment
if val != expected {
t.Errorf("Expected %f, got %f", expected, val)
}
}
// Benchmark for atomicUpdateFloat with single goroutine (no contention).
func BenchmarkAtomicUpdateFloat_SingleGoroutine(b *testing.B) {
var val float64 = 0.0
bits := (*uint64)(unsafe.Pointer(&val))
for i := 0; i < b.N; i++ {
atomicUpdateFloat(bits, func(f float64) float64 {
return f + 1.0
})
}
output = val
}
// Benchmark for old implementation with single goroutine (no contention) -> to check overhead of backoff
func BenchmarkAtomicNoBackoff_SingleGoroutine(b *testing.B) {
var val float64 = 0.0
bits := (*uint64)(unsafe.Pointer(&val))
for i := 0; i < b.N; i++ {
for {
loadedBits := atomic.LoadUint64(bits)
newBits := math.Float64bits(math.Float64frombits(loadedBits) + 1.0)
if atomic.CompareAndSwapUint64(bits, loadedBits, newBits) {
break
}
}
}
output = val
}
// Benchmark varying the number of goroutines.
func benchmarkAtomicUpdateFloatConcurrency(b *testing.B, numGoroutines int) {
var val float64 = 0.0
bits := (*uint64)(unsafe.Pointer(&val))
b.SetParallelism(numGoroutines)
b.ResetTimer()
b.RunParallel(func(pb *testing.PB) {
for pb.Next() {
atomicUpdateFloat(bits, func(f float64) float64 {
return f + 1.0
})
}
})
output = val
}
func benchmarkAtomicNoBackoffFloatConcurrency(b *testing.B, numGoroutines int) {
var val float64 = 0.0
bits := (*uint64)(unsafe.Pointer(&val))
b.SetParallelism(numGoroutines)
b.ResetTimer()
b.RunParallel(func(pb *testing.PB) {
for pb.Next() {
for {
loadedBits := atomic.LoadUint64(bits)
newBits := math.Float64bits(math.Float64frombits(loadedBits) + 1.0)
if atomic.CompareAndSwapUint64(bits, loadedBits, newBits) {
break
}
}
}
})
output = val
}
func BenchmarkAtomicUpdateFloat_1Goroutine(b *testing.B) {
benchmarkAtomicUpdateFloatConcurrency(b, 1)
}
func BenchmarkAtomicNoBackoff_1Goroutine(b *testing.B) {
benchmarkAtomicNoBackoffFloatConcurrency(b, 1)
}
func BenchmarkAtomicUpdateFloat_2Goroutines(b *testing.B) {
benchmarkAtomicUpdateFloatConcurrency(b, 2)
}
func BenchmarkAtomicNoBackoff_2Goroutines(b *testing.B) {
benchmarkAtomicNoBackoffFloatConcurrency(b, 2)
}
func BenchmarkAtomicUpdateFloat_4Goroutines(b *testing.B) {
benchmarkAtomicUpdateFloatConcurrency(b, 4)
}
func BenchmarkAtomicNoBackoff_4Goroutines(b *testing.B) {
benchmarkAtomicNoBackoffFloatConcurrency(b, 4)
}
func BenchmarkAtomicUpdateFloat_8Goroutines(b *testing.B) {
benchmarkAtomicUpdateFloatConcurrency(b, 8)
}
func BenchmarkAtomicNoBackoff_8Goroutines(b *testing.B) {
benchmarkAtomicNoBackoffFloatConcurrency(b, 8)
}
func BenchmarkAtomicUpdateFloat_16Goroutines(b *testing.B) {
benchmarkAtomicUpdateFloatConcurrency(b, 16)
}
func BenchmarkAtomicNoBackoff_16Goroutines(b *testing.B) {
benchmarkAtomicNoBackoffFloatConcurrency(b, 16)
}
func BenchmarkAtomicUpdateFloat_32Goroutines(b *testing.B) {
benchmarkAtomicUpdateFloatConcurrency(b, 32)
}
func BenchmarkAtomicNoBackoff_32Goroutines(b *testing.B) {
benchmarkAtomicNoBackoffFloatConcurrency(b, 32)
}

View File

@ -134,13 +134,9 @@ func (c *counter) Add(v float64) {
return
}
for {
oldBits := atomic.LoadUint64(&c.valBits)
newBits := math.Float64bits(math.Float64frombits(oldBits) + v)
if atomic.CompareAndSwapUint64(&c.valBits, oldBits, newBits) {
return
}
}
atomicUpdateFloat(&c.valBits, func(oldVal float64) float64 {
return oldVal + v
})
}
func (c *counter) AddWithExemplar(v float64, e Labels) {

View File

@ -120,13 +120,9 @@ func (g *gauge) Dec() {
}
func (g *gauge) Add(val float64) {
for {
oldBits := atomic.LoadUint64(&g.valBits)
newBits := math.Float64bits(math.Float64frombits(oldBits) + val)
if atomic.CompareAndSwapUint64(&g.valBits, oldBits, newBits) {
return
}
}
atomicUpdateFloat(&g.valBits, func(oldVal float64) float64 {
return oldVal + val
})
}
func (g *gauge) Sub(val float64) {

View File

@ -14,6 +14,7 @@
package prometheus
import (
"errors"
"fmt"
"math"
"runtime"
@ -28,6 +29,11 @@ import (
"google.golang.org/protobuf/types/known/timestamppb"
)
const (
nativeHistogramSchemaMaximum = 8
nativeHistogramSchemaMinimum = -4
)
// nativeHistogramBounds for the frac of observed values. Only relevant for
// schema > 0. The position in the slice is the schema. (0 is never used, just
// here for convenience of using the schema directly as the index.)
@ -858,15 +864,35 @@ func (h *histogram) Write(out *dto.Metric) error {
// findBucket returns the index of the bucket for the provided value, or
// len(h.upperBounds) for the +Inf bucket.
func (h *histogram) findBucket(v float64) int {
// TODO(beorn7): For small numbers of buckets (<30), a linear search is
// slightly faster than the binary search. If we really care, we could
// switch from one search strategy to the other depending on the number
// of buckets.
//
// Microbenchmarks (BenchmarkHistogramNoLabels):
// 11 buckets: 38.3 ns/op linear - binary 48.7 ns/op
// 100 buckets: 78.1 ns/op linear - binary 54.9 ns/op
// 300 buckets: 154 ns/op linear - binary 61.6 ns/op
n := len(h.upperBounds)
if n == 0 {
return 0
}
// Early exit: if v is less than or equal to the first upper bound, return 0
if v <= h.upperBounds[0] {
return 0
}
// Early exit: if v is greater than the last upper bound, return len(h.upperBounds)
if v > h.upperBounds[n-1] {
return n
}
// For small arrays, use simple linear search
// "magic number" 35 is result of tests on couple different (AWS and baremetal) servers
// see more details here: https://github.com/prometheus/client_golang/pull/1662
if n < 35 {
for i, bound := range h.upperBounds {
if v <= bound {
return i
}
}
// If v is greater than all upper bounds, return len(h.upperBounds)
return n
}
// For larger arrays, use stdlib's binary search
return sort.SearchFloat64s(h.upperBounds, v)
}
@ -1440,9 +1466,9 @@ func pickSchema(bucketFactor float64) int32 {
floor := math.Floor(math.Log2(math.Log2(bucketFactor)))
switch {
case floor <= -8:
return 8
return nativeHistogramSchemaMaximum
case floor >= 4:
return -4
return nativeHistogramSchemaMinimum
default:
return -int32(floor)
}
@ -1621,13 +1647,9 @@ func waitForCooldown(count uint64, counts *histogramCounts) {
// atomicAddFloat adds the provided float atomically to another float
// represented by the bit pattern the bits pointer is pointing to.
func atomicAddFloat(bits *uint64, v float64) {
for {
loadedBits := atomic.LoadUint64(bits)
newBits := math.Float64bits(math.Float64frombits(loadedBits) + v)
if atomic.CompareAndSwapUint64(bits, loadedBits, newBits) {
break
}
}
atomicUpdateFloat(bits, func(oldVal float64) float64 {
return oldVal + v
})
}
// atomicDecUint32 atomically decrements the uint32 p points to. See
@ -1835,3 +1857,196 @@ func (n *nativeExemplars) addExemplar(e *dto.Exemplar) {
n.exemplars = append(n.exemplars[:nIdx], append([]*dto.Exemplar{e}, append(n.exemplars[nIdx:rIdx], n.exemplars[rIdx+1:]...)...)...)
}
}
type constNativeHistogram struct {
desc *Desc
dto.Histogram
labelPairs []*dto.LabelPair
}
func validateCount(sum float64, count uint64, negativeBuckets, positiveBuckets map[int]int64, zeroBucket uint64) error {
var bucketPopulationSum int64
for _, v := range positiveBuckets {
bucketPopulationSum += v
}
for _, v := range negativeBuckets {
bucketPopulationSum += v
}
bucketPopulationSum += int64(zeroBucket)
// If the sum of observations is NaN, the number of observations must be greater or equal to the sum of all bucket counts.
// Otherwise, the number of observations must be equal to the sum of all bucket counts .
if math.IsNaN(sum) && bucketPopulationSum > int64(count) ||
!math.IsNaN(sum) && bucketPopulationSum != int64(count) {
return errors.New("the sum of all bucket populations exceeds the count of observations")
}
return nil
}
// NewConstNativeHistogram returns a metric representing a Prometheus native histogram with
// fixed values for the count, sum, and positive/negative/zero bucket counts. As those parameters
// cannot be changed, the returned value does not implement the Histogram
// interface (but only the Metric interface). Users of this package will not
// have much use for it in regular operations. However, when implementing custom
// OpenTelemetry Collectors, it is useful as a throw-away metric that is generated on the fly
// to send it to Prometheus in the Collect method.
//
// zeroBucket counts all (positive and negative)
// observations in the zero bucket (with an absolute value less or equal
// the current threshold).
// positiveBuckets and negativeBuckets are separate maps for negative and positive
// observations. The map's value is an int64, counting observations in
// that bucket. The map's key is the
// index of the bucket according to the used
// Schema. Index 0 is for an upper bound of 1 in positive buckets and for a lower bound of -1 in negative buckets.
// NewConstNativeHistogram returns an error if
// - the length of labelValues is not consistent with the variable labels in Desc or if Desc is invalid.
// - the schema passed is not between 8 and -4
// - the sum of counts in all buckets including the zero bucket does not equal the count if sum is not NaN (or exceeds the count if sum is NaN)
//
// See https://opentelemetry.io/docs/specs/otel/compatibility/prometheus_and_openmetrics/#exponential-histograms for more details about the conversion from OTel to Prometheus.
func NewConstNativeHistogram(
desc *Desc,
count uint64,
sum float64,
positiveBuckets, negativeBuckets map[int]int64,
zeroBucket uint64,
schema int32,
zeroThreshold float64,
createdTimestamp time.Time,
labelValues ...string,
) (Metric, error) {
if desc.err != nil {
return nil, desc.err
}
if err := validateLabelValues(labelValues, len(desc.variableLabels.names)); err != nil {
return nil, err
}
if schema > nativeHistogramSchemaMaximum || schema < nativeHistogramSchemaMinimum {
return nil, errors.New("invalid native histogram schema")
}
if err := validateCount(sum, count, negativeBuckets, positiveBuckets, zeroBucket); err != nil {
return nil, err
}
NegativeSpan, NegativeDelta := makeBucketsFromMap(negativeBuckets)
PositiveSpan, PositiveDelta := makeBucketsFromMap(positiveBuckets)
ret := &constNativeHistogram{
desc: desc,
Histogram: dto.Histogram{
CreatedTimestamp: timestamppb.New(createdTimestamp),
Schema: &schema,
ZeroThreshold: &zeroThreshold,
SampleCount: &count,
SampleSum: &sum,
NegativeSpan: NegativeSpan,
NegativeDelta: NegativeDelta,
PositiveSpan: PositiveSpan,
PositiveDelta: PositiveDelta,
ZeroCount: proto.Uint64(zeroBucket),
},
labelPairs: MakeLabelPairs(desc, labelValues),
}
if *ret.ZeroThreshold == 0 && *ret.ZeroCount == 0 && len(ret.PositiveSpan) == 0 && len(ret.NegativeSpan) == 0 {
ret.PositiveSpan = []*dto.BucketSpan{{
Offset: proto.Int32(0),
Length: proto.Uint32(0),
}}
}
return ret, nil
}
// MustNewConstNativeHistogram is a version of NewConstNativeHistogram that panics where
// NewConstNativeHistogram would have returned an error.
func MustNewConstNativeHistogram(
desc *Desc,
count uint64,
sum float64,
positiveBuckets, negativeBuckets map[int]int64,
zeroBucket uint64,
nativeHistogramSchema int32,
nativeHistogramZeroThreshold float64,
createdTimestamp time.Time,
labelValues ...string,
) Metric {
nativehistogram, err := NewConstNativeHistogram(desc,
count,
sum,
positiveBuckets,
negativeBuckets,
zeroBucket,
nativeHistogramSchema,
nativeHistogramZeroThreshold,
createdTimestamp,
labelValues...)
if err != nil {
panic(err)
}
return nativehistogram
}
func (h *constNativeHistogram) Desc() *Desc {
return h.desc
}
func (h *constNativeHistogram) Write(out *dto.Metric) error {
out.Histogram = &h.Histogram
out.Label = h.labelPairs
return nil
}
func makeBucketsFromMap(buckets map[int]int64) ([]*dto.BucketSpan, []int64) {
if len(buckets) == 0 {
return nil, nil
}
var ii []int
for k := range buckets {
ii = append(ii, k)
}
sort.Ints(ii)
var (
spans []*dto.BucketSpan
deltas []int64
prevCount int64
nextI int
)
appendDelta := func(count int64) {
*spans[len(spans)-1].Length++
deltas = append(deltas, count-prevCount)
prevCount = count
}
for n, i := range ii {
count := buckets[i]
// Multiple spans with only small gaps in between are probably
// encoded more efficiently as one larger span with a few empty
// buckets. Needs some research to find the sweet spot. For now,
// we assume that gaps of one or two buckets should not create
// a new span.
iDelta := int32(i - nextI)
if n == 0 || iDelta > 2 {
// We have to create a new span, either because we are
// at the very beginning, or because we have found a gap
// of more than two buckets.
spans = append(spans, &dto.BucketSpan{
Offset: proto.Int32(iDelta),
Length: proto.Uint32(0),
})
} else {
// We have found a small gap (or no gap at all).
// Insert empty buckets as needed.
for j := int32(0); j < iDelta; j++ {
appendDelta(0)
}
}
appendDelta(count)
nextI = i + 1
}
return spans, deltas
}

View File

@ -25,11 +25,11 @@ import (
"testing/quick"
"time"
"github.com/prometheus/client_golang/prometheus/internal"
dto "github.com/prometheus/client_model/go"
"google.golang.org/protobuf/proto"
"google.golang.org/protobuf/types/known/timestamppb"
"github.com/prometheus/client_golang/prometheus/internal"
)
func benchmarkHistogramObserve(w int, b *testing.B) {
@ -1455,3 +1455,632 @@ func compareNativeExemplarValues(t *testing.T, exps []*dto.Exemplar, values []fl
}
}
}
var resultFindBucket int
func benchmarkFindBucket(b *testing.B, l int) {
h := &histogram{upperBounds: make([]float64, l)}
for i := range h.upperBounds {
h.upperBounds[i] = float64(i)
}
v := float64(l / 2)
b.ResetTimer()
for i := 0; i < b.N; i++ {
resultFindBucket = h.findBucket(v)
}
}
func BenchmarkFindBucketShort(b *testing.B) {
benchmarkFindBucket(b, 20)
}
func BenchmarkFindBucketMid(b *testing.B) {
benchmarkFindBucket(b, 40)
}
func BenchmarkFindBucketLarge(b *testing.B) {
benchmarkFindBucket(b, 100)
}
func BenchmarkFindBucketHuge(b *testing.B) {
benchmarkFindBucket(b, 500)
}
func BenchmarkFindBucketInf(b *testing.B) {
h := &histogram{upperBounds: make([]float64, 500)}
for i := range h.upperBounds {
h.upperBounds[i] = float64(i)
}
v := 1000.5
b.ResetTimer()
for i := 0; i < b.N; i++ {
resultFindBucket = h.findBucket(v)
}
}
func BenchmarkFindBucketLow(b *testing.B) {
h := &histogram{upperBounds: make([]float64, 500)}
for i := range h.upperBounds {
h.upperBounds[i] = float64(i)
}
v := -1.1
b.ResetTimer()
for i := 0; i < b.N; i++ {
resultFindBucket = h.findBucket(v)
}
}
func TestFindBucket(t *testing.T) {
smallHistogram := &histogram{upperBounds: []float64{1, 2, 3, 4, 5}}
largeHistogram := &histogram{upperBounds: make([]float64, 50)}
for i := range largeHistogram.upperBounds {
largeHistogram.upperBounds[i] = float64(i)
}
tests := []struct {
h *histogram
v float64
expected int
}{
{smallHistogram, -1, 0},
{smallHistogram, 0.5, 0},
{smallHistogram, 2.5, 2},
{smallHistogram, 5.5, 5},
{largeHistogram, -1, 0},
{largeHistogram, 25.5, 26},
{largeHistogram, 49.5, 50},
{largeHistogram, 50.5, 50},
{largeHistogram, 5000.5, 50},
}
for _, tt := range tests {
result := tt.h.findBucket(tt.v)
if result != tt.expected {
t.Errorf("findBucket(%v) = %d; expected %d", tt.v, result, tt.expected)
}
}
}
func syncMapToMap(syncmap *sync.Map) (m map[int]int64) {
m = map[int]int64{}
syncmap.Range(func(key, value any) bool {
m[key.(int)] = *value.(*int64)
return true
})
return m
}
func TestConstNativeHistogram(t *testing.T) {
now := time.Now()
scenarios := []struct {
name string
observations []float64 // With simulated interval of 1m.
factor float64
zeroThreshold float64
maxBuckets uint32
minResetDuration time.Duration
maxZeroThreshold float64
want *dto.Histogram
}{
{
name: "no observations",
factor: 1.1,
want: &dto.Histogram{
SampleCount: proto.Uint64(0),
SampleSum: proto.Float64(0),
Schema: proto.Int32(3),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(0),
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "no observations and zero threshold of zero resulting in no-op span",
factor: 1.1,
zeroThreshold: NativeHistogramZeroThresholdZero,
want: &dto.Histogram{
SampleCount: proto.Uint64(0),
SampleSum: proto.Float64(0),
Schema: proto.Int32(3),
ZeroThreshold: proto.Float64(0),
ZeroCount: proto.Uint64(0),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(0)},
},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "factor 1.1 results in schema 3",
observations: []float64{0, 1, 2, 3},
factor: 1.1,
want: &dto.Histogram{
SampleCount: proto.Uint64(4),
SampleSum: proto.Float64(6),
Schema: proto.Int32(3),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(1)},
{Offset: proto.Int32(7), Length: proto.Uint32(1)},
{Offset: proto.Int32(4), Length: proto.Uint32(1)},
},
PositiveDelta: []int64{1, 0, 0},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "factor 1.2 results in schema 2",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2},
factor: 1.2,
want: &dto.Histogram{
SampleCount: proto.Uint64(6),
SampleSum: proto.Float64(7.4),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
},
PositiveDelta: []int64{1, -1, 2, -2, 2},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "factor 4 results in schema -1",
observations: []float64{
0.0156251, 0.0625, // Bucket -2: (0.015625, 0.0625)
0.1, 0.25, // Bucket -1: (0.0625, 0.25]
0.5, 1, // Bucket 0: (0.25, 1]
1.5, 2, 3, 3.5, // Bucket 1: (1, 4]
5, 6, 7, // Bucket 2: (4, 16]
33.33, // Bucket 3: (16, 64]
},
factor: 4,
want: &dto.Histogram{
SampleCount: proto.Uint64(14),
SampleSum: proto.Float64(63.2581251),
Schema: proto.Int32(-1),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(0),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(-2), Length: proto.Uint32(6)},
},
PositiveDelta: []int64{2, 0, 0, 2, -1, -2},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "factor 17 results in schema -2",
observations: []float64{
0.0156251, 0.0625, // Bucket -1: (0.015625, 0.0625]
0.1, 0.25, 0.5, 1, // Bucket 0: (0.0625, 1]
1.5, 2, 3, 3.5, 5, 6, 7, // Bucket 1: (1, 16]
33.33, // Bucket 2: (16, 256]
},
factor: 17,
want: &dto.Histogram{
SampleCount: proto.Uint64(14),
SampleSum: proto.Float64(63.2581251),
Schema: proto.Int32(-2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(0),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(-1), Length: proto.Uint32(4)},
},
PositiveDelta: []int64{2, 2, 3, -6},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "negative buckets",
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2},
factor: 1.2,
want: &dto.Histogram{
SampleCount: proto.Uint64(6),
SampleSum: proto.Float64(-7.4),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
NegativeSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
},
NegativeDelta: []int64{1, -1, 2, -2, 2},
CreatedTimestamp: timestamppb.New(now),
},
},
{
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: &dto.Histogram{
SampleCount: proto.Uint64(11),
SampleSum: proto.Float64(0),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
NegativeSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
},
NegativeDelta: []int64{1, -1, 2, -2, 2},
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
},
PositiveDelta: []int64{1, -1, 2, -2, 2},
CreatedTimestamp: timestamppb.New(now),
},
},
{
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: &dto.Histogram{
SampleCount: proto.Uint64(11),
SampleSum: proto.Float64(0),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(1.4),
ZeroCount: proto.Uint64(7),
NegativeSpan: []*dto.BucketSpan{
{Offset: proto.Int32(4), Length: proto.Uint32(1)},
},
NegativeDelta: []int64{2},
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(4), Length: proto.Uint32(1)},
},
PositiveDelta: []int64{2},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "NaN observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.NaN()},
factor: 1.2,
want: &dto.Histogram{
SampleCount: proto.Uint64(7),
SampleSum: proto.Float64(math.NaN()),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
},
PositiveDelta: []int64{1, -1, 2, -2, 2},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "+Inf observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(+1)},
factor: 1.2,
want: &dto.Histogram{
SampleCount: proto.Uint64(7),
SampleSum: proto.Float64(math.Inf(+1)),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
{Offset: proto.Int32(4092), Length: proto.Uint32(1)},
},
PositiveDelta: []int64{1, -1, 2, -2, 2, -1},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "-Inf observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(-1)},
factor: 1.2,
want: &dto.Histogram{
SampleCount: proto.Uint64(7),
SampleSum: proto.Float64(math.Inf(-1)),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
NegativeSpan: []*dto.BucketSpan{
{Offset: proto.Int32(4097), Length: proto.Uint32(1)},
},
NegativeDelta: []int64{1},
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
},
PositiveDelta: []int64{1, -1, 2, -2, 2},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "limited buckets but nothing triggered",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2},
factor: 1.2,
maxBuckets: 4,
want: &dto.Histogram{
SampleCount: proto.Uint64(6),
SampleSum: proto.Float64(7.4),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
},
PositiveDelta: []int64{1, -1, 2, -2, 2},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "buckets limited by halving resolution",
observations: []float64{0, 1, 1.1, 1.2, 1.4, 1.8, 2, 3},
factor: 1.2,
maxBuckets: 4,
want: &dto.Histogram{
SampleCount: proto.Uint64(8),
SampleSum: proto.Float64(11.5),
Schema: proto.Int32(1),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
},
PositiveDelta: []int64{1, 2, -1, -2, 1},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "buckets limited by widening the zero bucket",
observations: []float64{0, 1, 1.1, 1.2, 1.4, 1.8, 2, 3},
factor: 1.2,
maxBuckets: 4,
maxZeroThreshold: 1.2,
want: &dto.Histogram{
SampleCount: proto.Uint64(8),
SampleSum: proto.Float64(11.5),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(1),
ZeroCount: proto.Uint64(2),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(1), Length: proto.Uint32(7)},
},
PositiveDelta: []int64{1, 1, -2, 2, -2, 0, 1},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "buckets limited by widening the zero bucket twice",
observations: []float64{0, 1, 1.1, 1.2, 1.4, 1.8, 2, 3, 4},
factor: 1.2,
maxBuckets: 4,
maxZeroThreshold: 1.2,
want: &dto.Histogram{
SampleCount: proto.Uint64(9),
SampleSum: proto.Float64(15.5),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(1.189207115002721),
ZeroCount: proto.Uint64(3),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(2), Length: proto.Uint32(7)},
},
PositiveDelta: []int64{2, -2, 2, -2, 0, 1, 0},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "buckets limited by reset",
observations: []float64{0, 1, 1.1, 1.2, 1.4, 1.8, 2, 3, 4},
factor: 1.2,
maxBuckets: 4,
maxZeroThreshold: 1.2,
minResetDuration: 5 * time.Minute,
want: &dto.Histogram{
SampleCount: proto.Uint64(2),
SampleSum: proto.Float64(7),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(0),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(7), Length: proto.Uint32(2)},
},
PositiveDelta: []int64{1, 0},
CreatedTimestamp: timestamppb.New(now.Add(8 * time.Minute)), // We expect reset to happen after 8 observations.
},
},
{
name: "limited buckets but nothing triggered, negative observations",
observations: []float64{0, -1, -1.2, -1.4, -1.8, -2},
factor: 1.2,
maxBuckets: 4,
want: &dto.Histogram{
SampleCount: proto.Uint64(6),
SampleSum: proto.Float64(-7.4),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
NegativeSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
},
NegativeDelta: []int64{1, -1, 2, -2, 2},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "buckets limited by halving resolution, negative observations",
observations: []float64{0, -1, -1.1, -1.2, -1.4, -1.8, -2, -3},
factor: 1.2,
maxBuckets: 4,
want: &dto.Histogram{
SampleCount: proto.Uint64(8),
SampleSum: proto.Float64(-11.5),
Schema: proto.Int32(1),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(1),
NegativeSpan: []*dto.BucketSpan{
{Offset: proto.Int32(0), Length: proto.Uint32(5)},
},
NegativeDelta: []int64{1, 2, -1, -2, 1},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "buckets limited by widening the zero bucket, negative observations",
observations: []float64{0, -1, -1.1, -1.2, -1.4, -1.8, -2, -3},
factor: 1.2,
maxBuckets: 4,
maxZeroThreshold: 1.2,
want: &dto.Histogram{
SampleCount: proto.Uint64(8),
SampleSum: proto.Float64(-11.5),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(1),
ZeroCount: proto.Uint64(2),
NegativeSpan: []*dto.BucketSpan{
{Offset: proto.Int32(1), Length: proto.Uint32(7)},
},
NegativeDelta: []int64{1, 1, -2, 2, -2, 0, 1},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "buckets limited by widening the zero bucket twice, negative observations",
observations: []float64{0, -1, -1.1, -1.2, -1.4, -1.8, -2, -3, -4},
factor: 1.2,
maxBuckets: 4,
maxZeroThreshold: 1.2,
want: &dto.Histogram{
SampleCount: proto.Uint64(9),
SampleSum: proto.Float64(-15.5),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(1.189207115002721),
ZeroCount: proto.Uint64(3),
NegativeSpan: []*dto.BucketSpan{
{Offset: proto.Int32(2), Length: proto.Uint32(7)},
},
NegativeDelta: []int64{2, -2, 2, -2, 0, 1, 0},
CreatedTimestamp: timestamppb.New(now),
},
},
{
name: "buckets limited by reset, negative observations",
observations: []float64{0, -1, -1.1, -1.2, -1.4, -1.8, -2, -3, -4},
factor: 1.2,
maxBuckets: 4,
maxZeroThreshold: 1.2,
minResetDuration: 5 * time.Minute,
want: &dto.Histogram{
SampleCount: proto.Uint64(2),
SampleSum: proto.Float64(-7),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(0),
NegativeSpan: []*dto.BucketSpan{
{Offset: proto.Int32(7), Length: proto.Uint32(2)},
},
NegativeDelta: []int64{1, 0},
CreatedTimestamp: timestamppb.New(now.Add(8 * time.Minute)), // We expect reset to happen after 8 observations.
},
},
{
name: "buckets limited by halving resolution, then reset",
observations: []float64{0, 1, 1.1, 1.2, 1.4, 1.8, 2, 5, 5.1, 3, 4},
factor: 1.2,
maxBuckets: 4,
minResetDuration: 9 * time.Minute,
want: &dto.Histogram{
SampleCount: proto.Uint64(3),
SampleSum: proto.Float64(12.1),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(0),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(7), Length: proto.Uint32(4)},
},
PositiveDelta: []int64{1, 0, -1, 1},
CreatedTimestamp: timestamppb.New(now.Add(9 * time.Minute)), // We expect reset to happen after 8 minutes.
},
},
{
name: "buckets limited by widening the zero bucket, then reset",
observations: []float64{0, 1, 1.1, 1.2, 1.4, 1.8, 2, 5, 5.1, 3, 4},
factor: 1.2,
maxBuckets: 4,
maxZeroThreshold: 1.2,
minResetDuration: 9 * time.Minute,
want: &dto.Histogram{
SampleCount: proto.Uint64(3),
SampleSum: proto.Float64(12.1),
Schema: proto.Int32(2),
ZeroThreshold: proto.Float64(2.938735877055719e-39),
ZeroCount: proto.Uint64(0),
PositiveSpan: []*dto.BucketSpan{
{Offset: proto.Int32(7), Length: proto.Uint32(4)},
},
PositiveDelta: []int64{1, 0, -1, 1},
CreatedTimestamp: timestamppb.New(now.Add(9 * time.Minute)), // We expect reset to happen after 8 minutes.
},
},
}
for _, s := range scenarios {
t.Run(s.name, func(t *testing.T) {
var (
ts = now
funcToCall func()
whenToCall time.Duration
)
his := NewHistogram(HistogramOpts{
Name: "name",
Help: "help",
NativeHistogramBucketFactor: s.factor,
NativeHistogramZeroThreshold: s.zeroThreshold,
NativeHistogramMaxBucketNumber: s.maxBuckets,
NativeHistogramMinResetDuration: s.minResetDuration,
NativeHistogramMaxZeroThreshold: s.maxZeroThreshold,
now: func() time.Time { return ts },
afterFunc: func(d time.Duration, f func()) *time.Timer {
funcToCall = f
whenToCall = d
return nil
},
})
ts = ts.Add(time.Minute)
for _, o := range s.observations {
his.Observe(o)
ts = ts.Add(time.Minute)
whenToCall -= time.Minute
if funcToCall != nil && whenToCall <= 0 {
funcToCall()
funcToCall = nil
}
}
_his := his.(*histogram)
n := atomic.LoadUint64(&_his.countAndHotIdx)
hotIdx := n >> 63
cold := _his.counts[hotIdx]
consthist, err := NewConstNativeHistogram(_his.Desc(),
cold.count,
math.Float64frombits(cold.sumBits),
syncMapToMap(&cold.nativeHistogramBucketsPositive),
syncMapToMap(&cold.nativeHistogramBucketsNegative),
cold.nativeHistogramZeroBucket,
cold.nativeHistogramSchema,
math.Float64frombits(cold.nativeHistogramZeroThresholdBits),
_his.lastResetTime,
)
if err != nil {
t.Fatal("unexpected error writing metric", err)
}
m2 := &dto.Metric{}
if err := consthist.Write(m2); err != nil {
t.Fatal("unexpected error writing metric", err)
}
got := m2.Histogram
if !proto.Equal(s.want, got) {
t.Errorf("want histogram %q, got %q", s.want, got)
}
})
}
}

View File

@ -131,7 +131,7 @@ func TestHandlerErrorHandling(t *testing.T) {
logger := log.New(logBuf, "", 0)
writer := httptest.NewRecorder()
request, _ := http.NewRequest("GET", "/", nil)
request, _ := http.NewRequest(http.MethodGet, "/", nil)
request.Header.Add("Accept", "test/plain")
mReg := &mockTransactionGatherer{g: reg}
@ -252,7 +252,7 @@ func TestInstrumentMetricHandler(t *testing.T) {
// Do it again to test idempotency.
InstrumentMetricHandler(reg, HandlerForTransactional(mReg, HandlerOpts{}))
writer := httptest.NewRecorder()
request, _ := http.NewRequest("GET", "/", nil)
request, _ := http.NewRequest(http.MethodGet, "/", nil)
request.Header.Add(acceptHeader, acceptTextPlain)
handler.ServeHTTP(writer, request)
@ -311,7 +311,7 @@ func TestHandlerMaxRequestsInFlight(t *testing.T) {
w1 := httptest.NewRecorder()
w2 := httptest.NewRecorder()
w3 := httptest.NewRecorder()
request, _ := http.NewRequest("GET", "/", nil)
request, _ := http.NewRequest(http.MethodGet, "/", nil)
request.Header.Add(acceptHeader, acceptTextPlain)
c := blockingCollector{Block: make(chan struct{}), CollectStarted: make(chan struct{}, 1)}
@ -348,7 +348,7 @@ func TestHandlerTimeout(t *testing.T) {
handler := HandlerFor(reg, HandlerOpts{Timeout: time.Millisecond})
w := httptest.NewRecorder()
request, _ := http.NewRequest("GET", "/", nil)
request, _ := http.NewRequest(http.MethodGet, "/", nil)
request.Header.Add("Accept", "test/plain")
c := blockingCollector{Block: make(chan struct{}), CollectStarted: make(chan struct{}, 1)}
@ -372,7 +372,7 @@ func TestInstrumentMetricHandlerWithCompression(t *testing.T) {
handler := InstrumentMetricHandler(reg, HandlerForTransactional(mReg, HandlerOpts{DisableCompression: false}))
compression := Zstd
writer := httptest.NewRecorder()
request, _ := http.NewRequest("GET", "/", nil)
request, _ := http.NewRequest(http.MethodGet, "/", nil)
request.Header.Add(acceptHeader, acceptTextPlain)
request.Header.Add(acceptEncodingHeader, string(compression))
@ -533,7 +533,7 @@ func TestNegotiateEncodingWriter(t *testing.T) {
}
for _, test := range testCases {
request, _ := http.NewRequest("GET", "/", nil)
request, _ := http.NewRequest(http.MethodGet, "/", nil)
request.Header.Add(acceptEncodingHeader, test.acceptEncoding)
rr := httptest.NewRecorder()
_, encodingHeader, _, err := negotiateEncodingWriter(request, rr, test.offeredCompressions)
@ -631,7 +631,7 @@ func BenchmarkCompression(b *testing.B) {
b.Run(benchmark.name+"_"+size.name, func(b *testing.B) {
for i := 0; i < b.N; i++ {
writer := httptest.NewRecorder()
request, _ := http.NewRequest("GET", "/", nil)
request, _ := http.NewRequest(http.MethodGet, "/", nil)
request.Header.Add(acceptEncodingHeader, benchmark.compressionType)
handler.ServeHTTP(writer, request)
}

View File

@ -223,7 +223,7 @@ func TestClientMiddlewareAPI_WithRequestContext(t *testing.T) {
}))
defer backend.Close()
req, err := http.NewRequest("GET", backend.URL, nil)
req, err := http.NewRequest(http.MethodGet, backend.URL, nil)
if err != nil {
t.Fatalf("%v", err)
}
@ -276,7 +276,7 @@ func TestClientMiddlewareAPIWithRequestContextTimeout(t *testing.T) {
}))
defer backend.Close()
req, err := http.NewRequest("GET", backend.URL, nil)
req, err := http.NewRequest(http.MethodGet, backend.URL, nil)
if err != nil {
t.Fatalf("%v", err)
}

View File

@ -418,7 +418,7 @@ func TestMiddlewareAPI(t *testing.T) {
_, _ = w.Write([]byte("OK"))
})
r, _ := http.NewRequest("GET", "www.example.com", nil)
r, _ := http.NewRequest(http.MethodGet, "www.example.com", nil)
w := httptest.NewRecorder()
chain.ServeHTTP(w, r)
@ -432,7 +432,7 @@ func TestMiddlewareAPI_WithExemplars(t *testing.T) {
_, _ = w.Write([]byte("OK"))
}, WithExemplarFromContext(func(_ context.Context) prometheus.Labels { return exemplar }))
r, _ := http.NewRequest("GET", "www.example.com", nil)
r, _ := http.NewRequest(http.MethodGet, "www.example.com", nil)
w := httptest.NewRecorder()
chain.ServeHTTP(w, r)

View File

@ -714,7 +714,7 @@ collected metric "broken_metric" { label:<name:"foo" value:"bar" > label:<name:"
}
writer := httptest.NewRecorder()
handler := promhttp.HandlerFor(gatherer, promhttp.HandlerOpts{})
request, _ := http.NewRequest("GET", "/", nil)
request, _ := http.NewRequest(http.MethodGet, "/", nil)
for key, value := range scenario.headers {
request.Header.Add(key, value)
}

View File

@ -471,13 +471,9 @@ func (s *noObjectivesSummary) Observe(v float64) {
n := atomic.AddUint64(&s.countAndHotIdx, 1)
hotCounts := s.counts[n>>63]
for {
oldBits := atomic.LoadUint64(&hotCounts.sumBits)
newBits := math.Float64bits(math.Float64frombits(oldBits) + v)
if atomic.CompareAndSwapUint64(&hotCounts.sumBits, oldBits, newBits) {
break
}
}
atomicUpdateFloat(&hotCounts.sumBits, func(oldVal float64) float64 {
return oldVal + v
})
// Increment count last as we take it as a signal that the observation
// is complete.
atomic.AddUint64(&hotCounts.count, 1)
@ -519,14 +515,13 @@ func (s *noObjectivesSummary) Write(out *dto.Metric) error {
// Finally add all the cold counts to the new hot counts and reset the cold counts.
atomic.AddUint64(&hotCounts.count, count)
atomic.StoreUint64(&coldCounts.count, 0)
for {
oldBits := atomic.LoadUint64(&hotCounts.sumBits)
newBits := math.Float64bits(math.Float64frombits(oldBits) + sum.GetSampleSum())
if atomic.CompareAndSwapUint64(&hotCounts.sumBits, oldBits, newBits) {
atomic.StoreUint64(&coldCounts.sumBits, 0)
break
}
}
// Use atomicUpdateFloat to update hotCounts.sumBits atomically.
atomicUpdateFloat(&hotCounts.sumBits, func(oldVal float64) float64 {
return oldVal + sum.GetSampleSum()
})
atomic.StoreUint64(&coldCounts.sumBits, 0)
return nil
}