Merge pull request #15220 from prometheus/nhcb-scrape-optimize
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perf(nhcb): scrape optimize
This commit is contained in:
Bartlomiej Plotka 2024-11-08 19:02:48 +01:00 committed by GitHub
commit 76432aaf4e
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
5 changed files with 461 additions and 151 deletions

View file

@ -283,18 +283,18 @@ func (p *NHCBParser) handleClassicHistogramSeries(lset labels.Labels) bool {
le, err := strconv.ParseFloat(lset.Get(labels.BucketLabel), 64)
if err == nil && !math.IsNaN(le) {
p.processClassicHistogramSeries(lset, "_bucket", func(hist *convertnhcb.TempHistogram) {
hist.BucketCounts[le] = p.value
_ = hist.SetBucketCount(le, p.value)
})
return true
}
case strings.HasSuffix(mName, "_count"):
p.processClassicHistogramSeries(lset, "_count", func(hist *convertnhcb.TempHistogram) {
hist.Count = p.value
_ = hist.SetCount(p.value)
})
return true
case strings.HasSuffix(mName, "_sum"):
p.processClassicHistogramSeries(lset, "_sum", func(hist *convertnhcb.TempHistogram) {
hist.Sum = p.value
_ = hist.SetSum(p.value)
})
return true
}
@ -306,8 +306,8 @@ func (p *NHCBParser) processClassicHistogramSeries(lset labels.Labels, suffix st
p.storeClassicLabels()
p.tempCT = p.parser.CreatedTimestamp()
p.state = stateCollecting
p.tempLsetNHCB = convertnhcb.GetHistogramMetricBase(lset, suffix)
}
p.tempLsetNHCB = convertnhcb.GetHistogramMetricBase(lset, suffix)
p.storeExemplars()
updateHist(&p.tempNHCB)
}
@ -335,7 +335,6 @@ func (p *NHCBParser) nextExemplarPtr() *exemplar.Exemplar {
func (p *NHCBParser) swapExemplars() {
p.exemplars = p.tempExemplars[:p.tempExemplarCount]
p.tempExemplars = p.tempExemplars[:0]
p.tempExemplarCount = 0
}
// processNHCB converts the collated classic histogram series to NHCB and caches the info
@ -344,33 +343,32 @@ func (p *NHCBParser) processNHCB() bool {
if p.state != stateCollecting {
return false
}
ub := make([]float64, 0, len(p.tempNHCB.BucketCounts))
for b := range p.tempNHCB.BucketCounts {
ub = append(ub, b)
}
upperBounds, hBase := convertnhcb.ProcessUpperBoundsAndCreateBaseHistogram(ub, false)
fhBase := hBase.ToFloat(nil)
h, fh := convertnhcb.NewHistogram(p.tempNHCB, upperBounds, hBase, fhBase)
if h != nil {
if err := h.Validate(); err != nil {
return false
h, fh, err := p.tempNHCB.Convert()
if err == nil {
if h != nil {
if err := h.Validate(); err != nil {
return false
}
p.hNHCB = h
p.fhNHCB = nil
} else if fh != nil {
if err := fh.Validate(); err != nil {
return false
}
p.hNHCB = nil
p.fhNHCB = fh
}
p.hNHCB = h
p.fhNHCB = nil
} else if fh != nil {
if err := fh.Validate(); err != nil {
return false
}
p.hNHCB = nil
p.fhNHCB = fh
p.metricStringNHCB = p.tempLsetNHCB.Get(labels.MetricName) + strings.ReplaceAll(p.tempLsetNHCB.DropMetricName().String(), ", ", ",")
p.bytesNHCB = []byte(p.metricStringNHCB)
p.lsetNHCB = p.tempLsetNHCB
p.swapExemplars()
p.ctNHCB = p.tempCT
p.state = stateEmitting
} else {
p.state = stateStart
}
p.metricStringNHCB = p.tempLsetNHCB.Get(labels.MetricName) + strings.ReplaceAll(p.tempLsetNHCB.DropMetricName().String(), ", ", ",")
p.bytesNHCB = []byte(p.metricStringNHCB)
p.lsetNHCB = p.tempLsetNHCB
p.swapExemplars()
p.ctNHCB = p.tempCT
p.tempNHCB = convertnhcb.NewTempHistogram()
p.state = stateEmitting
p.tempNHCB.Reset()
p.tempExemplarCount = 0
p.tempCT = nil
return true
return err == nil
}

View file

@ -500,8 +500,8 @@ something_bucket{a="b",le="+Inf"} 9 # {id="something-test"} 2e100 123.000
Schema: histogram.CustomBucketsSchema,
Count: 9,
Sum: 42123.0,
PositiveSpans: []histogram.Span{{Offset: 0, Length: 1}, {Offset: 1, Length: 1}},
PositiveBuckets: []int64{8, -7},
PositiveSpans: []histogram.Span{{Offset: 0, Length: 3}},
PositiveBuckets: []int64{8, -8, 1},
CustomValues: []float64{0.0, 1.0}, // We do not store the +Inf boundary.
},
lset: labels.FromStrings("__name__", "something", "a", "b"),
@ -937,3 +937,48 @@ test_histogram1_bucket{le="-0.0003899999999999998"} 4 1234568
test_histogram1_bucket{le="-0.0002899999999999998"} 16 1234568
test_histogram1_bucket{le="+Inf"} 175 1234568`
}
func TestNHCBParserErrorHandling(t *testing.T) {
input := `# HELP something Histogram with non cumulative buckets
# TYPE something histogram
something_count 18
something_sum 324789.4
something_created 1520430001
something_bucket{le="0.0"} 18
something_bucket{le="+Inf"} 1
something_count{a="b"} 9
something_sum{a="b"} 42123
something_created{a="b"} 1520430002
something_bucket{a="b",le="0.0"} 1
something_bucket{a="b",le="+Inf"} 9
# EOF`
exp := []parsedEntry{
{
m: "something",
help: "Histogram with non cumulative buckets",
},
{
m: "something",
typ: model.MetricTypeHistogram,
},
// The parser should skip the series with non-cumulative buckets.
{
m: `something{a="b"}`,
shs: &histogram.Histogram{
Schema: histogram.CustomBucketsSchema,
Count: 9,
Sum: 42123.0,
PositiveSpans: []histogram.Span{{Offset: 0, Length: 2}},
PositiveBuckets: []int64{1, 7},
CustomValues: []float64{0.0}, // We do not store the +Inf boundary.
},
lset: labels.FromStrings("__name__", "something", "a", "b"),
ct: int64p(1520430002000),
},
}
p := NewOpenMetricsParser([]byte(input), labels.NewSymbolTable(), WithOMParserCTSeriesSkipped())
p = NewNHCBParser(p, labels.NewSymbolTable(), false)
got := testParse(t, p)
requireEntries(t, exp, got)
}

View file

@ -482,18 +482,16 @@ func (cmd *loadCmd) append(a storage.Appender) error {
type tempHistogramWrapper struct {
metric labels.Labels
upperBounds []float64
histogramByTs map[int64]convertnhcb.TempHistogram
}
func newTempHistogramWrapper() tempHistogramWrapper {
return tempHistogramWrapper{
upperBounds: []float64{},
histogramByTs: map[int64]convertnhcb.TempHistogram{},
}
}
func processClassicHistogramSeries(m labels.Labels, suffix string, histogramMap map[uint64]tempHistogramWrapper, smpls []promql.Sample, updateHistogramWrapper func(*tempHistogramWrapper), updateHistogram func(*convertnhcb.TempHistogram, float64)) {
func processClassicHistogramSeries(m labels.Labels, suffix string, histogramMap map[uint64]tempHistogramWrapper, smpls []promql.Sample, updateHistogram func(*convertnhcb.TempHistogram, float64)) {
m2 := convertnhcb.GetHistogramMetricBase(m, suffix)
m2hash := m2.Hash()
histogramWrapper, exists := histogramMap[m2hash]
@ -501,9 +499,6 @@ func processClassicHistogramSeries(m labels.Labels, suffix string, histogramMap
histogramWrapper = newTempHistogramWrapper()
}
histogramWrapper.metric = m2
if updateHistogramWrapper != nil {
updateHistogramWrapper(&histogramWrapper)
}
for _, s := range smpls {
if s.H != nil {
continue
@ -534,18 +529,16 @@ func (cmd *loadCmd) appendCustomHistogram(a storage.Appender) error {
if err != nil || math.IsNaN(le) {
continue
}
processClassicHistogramSeries(m, "_bucket", histogramMap, smpls, func(histogramWrapper *tempHistogramWrapper) {
histogramWrapper.upperBounds = append(histogramWrapper.upperBounds, le)
}, func(histogram *convertnhcb.TempHistogram, f float64) {
histogram.BucketCounts[le] = f
processClassicHistogramSeries(m, "_bucket", histogramMap, smpls, func(histogram *convertnhcb.TempHistogram, f float64) {
_ = histogram.SetBucketCount(le, f)
})
case strings.HasSuffix(mName, "_count"):
processClassicHistogramSeries(m, "_count", histogramMap, smpls, nil, func(histogram *convertnhcb.TempHistogram, f float64) {
histogram.Count = f
processClassicHistogramSeries(m, "_count", histogramMap, smpls, func(histogram *convertnhcb.TempHistogram, f float64) {
_ = histogram.SetCount(f)
})
case strings.HasSuffix(mName, "_sum"):
processClassicHistogramSeries(m, "_sum", histogramMap, smpls, nil, func(histogram *convertnhcb.TempHistogram, f float64) {
histogram.Sum = f
processClassicHistogramSeries(m, "_sum", histogramMap, smpls, func(histogram *convertnhcb.TempHistogram, f float64) {
_ = histogram.SetSum(f)
})
}
}
@ -553,11 +546,12 @@ func (cmd *loadCmd) appendCustomHistogram(a storage.Appender) error {
// Convert the collated classic histogram data into native histograms
// with custom bounds and append them to the storage.
for _, histogramWrapper := range histogramMap {
upperBounds, hBase := convertnhcb.ProcessUpperBoundsAndCreateBaseHistogram(histogramWrapper.upperBounds, true)
fhBase := hBase.ToFloat(nil)
samples := make([]promql.Sample, 0, len(histogramWrapper.histogramByTs))
for t, histogram := range histogramWrapper.histogramByTs {
h, fh := convertnhcb.NewHistogram(histogram, upperBounds, hBase, fhBase)
h, fh, err := histogram.Convert()
if err != nil {
return err
}
if fh == nil {
if err := h.Validate(); err != nil {
return err

View file

@ -14,6 +14,7 @@
package convertnhcb
import (
"errors"
"fmt"
"math"
"sort"
@ -23,129 +24,212 @@ import (
"github.com/prometheus/prometheus/model/labels"
)
var (
errNegativeBucketCount = errors.New("bucket count must be non-negative")
errNegativeCount = errors.New("count must be non-negative")
errCountMismatch = errors.New("count mismatch")
errCountNotCumulative = errors.New("count is not cumulative")
)
type tempHistogramBucket struct {
le float64
count float64
}
// TempHistogram is used to collect information about classic histogram
// samples incrementally before creating a histogram.Histogram or
// histogram.FloatHistogram based on the values collected.
type TempHistogram struct {
BucketCounts map[float64]float64
Count float64
Sum float64
HasFloat bool
buckets []tempHistogramBucket
count float64
sum float64
err error
hasCount bool
}
// NewTempHistogram creates a new TempHistogram to
// collect information about classic histogram samples.
func NewTempHistogram() TempHistogram {
return TempHistogram{
BucketCounts: map[float64]float64{},
buckets: make([]tempHistogramBucket, 0, 10),
}
}
func (h TempHistogram) getIntBucketCounts() (map[float64]int64, error) {
bucketCounts := map[float64]int64{}
for le, count := range h.BucketCounts {
intCount := int64(math.Round(count))
if float64(intCount) != count {
return nil, fmt.Errorf("bucket count %f for le %g is not an integer", count, le)
func (h TempHistogram) Err() error {
return h.err
}
func (h *TempHistogram) Reset() {
h.buckets = h.buckets[:0]
h.count = 0
h.sum = 0
h.err = nil
h.hasCount = false
}
func (h *TempHistogram) SetBucketCount(boundary, count float64) error {
if h.err != nil {
return h.err
}
if count < 0 {
h.err = fmt.Errorf("%w: le=%g, count=%g", errNegativeBucketCount, boundary, count)
return h.err
}
// Assume that the elements are added in order.
switch {
case len(h.buckets) == 0:
h.buckets = append(h.buckets, tempHistogramBucket{le: boundary, count: count})
case h.buckets[len(h.buckets)-1].le < boundary:
// Happy case is "<".
if count < h.buckets[len(h.buckets)-1].count {
h.err = fmt.Errorf("%w: %g < %g", errCountNotCumulative, count, h.buckets[len(h.buckets)-1].count)
return h.err
}
bucketCounts[le] = intCount
}
return bucketCounts, nil
}
// ProcessUpperBoundsAndCreateBaseHistogram prepares an integer native
// histogram with custom buckets based on the provided upper bounds.
// Everything is set except the bucket counts.
// The sorted upper bounds are also returned.
func ProcessUpperBoundsAndCreateBaseHistogram(upperBounds0 []float64, needsDedup bool) ([]float64, *histogram.Histogram) {
sort.Float64s(upperBounds0)
var upperBounds []float64
if needsDedup {
upperBounds = make([]float64, 0, len(upperBounds0))
prevLE := math.Inf(-1)
for _, le := range upperBounds0 {
if le != prevLE {
upperBounds = append(upperBounds, le)
prevLE = le
}
h.buckets = append(h.buckets, tempHistogramBucket{le: boundary, count: count})
case h.buckets[len(h.buckets)-1].le == boundary:
// Ignore this, as it is a duplicate sample.
default:
// Find the correct position to insert.
i := sort.Search(len(h.buckets), func(i int) bool {
return h.buckets[i].le >= boundary
})
if h.buckets[i].le == boundary {
// Ignore this, as it is a duplicate sample.
return nil
}
} else {
upperBounds = upperBounds0
}
var customBounds []float64
if upperBounds[len(upperBounds)-1] == math.Inf(1) {
customBounds = upperBounds[:len(upperBounds)-1]
} else {
customBounds = upperBounds
}
return upperBounds, &histogram.Histogram{
Count: 0,
Sum: 0,
Schema: histogram.CustomBucketsSchema,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: uint32(len(upperBounds))},
},
PositiveBuckets: make([]int64, len(upperBounds)),
CustomValues: customBounds,
}
}
// NewHistogram fills the bucket counts in the provided histogram.Histogram
// or histogram.FloatHistogram based on the provided temporary histogram and
// upper bounds.
func NewHistogram(histogram TempHistogram, upperBounds []float64, hBase *histogram.Histogram, fhBase *histogram.FloatHistogram) (*histogram.Histogram, *histogram.FloatHistogram) {
intBucketCounts, err := histogram.getIntBucketCounts()
if err != nil {
return nil, newFloatHistogram(histogram, upperBounds, histogram.BucketCounts, fhBase)
}
return newIntegerHistogram(histogram, upperBounds, intBucketCounts, hBase), nil
}
func newIntegerHistogram(histogram TempHistogram, upperBounds []float64, bucketCounts map[float64]int64, hBase *histogram.Histogram) *histogram.Histogram {
h := hBase.Copy()
absBucketCounts := make([]int64, len(h.PositiveBuckets))
var prevCount, total int64
for i, le := range upperBounds {
currCount, exists := bucketCounts[le]
if !exists {
currCount = 0
if i > 0 && count < h.buckets[i-1].count {
h.err = fmt.Errorf("%w: %g < %g", errCountNotCumulative, count, h.buckets[i-1].count)
return h.err
}
count := currCount - prevCount
absBucketCounts[i] = count
total += count
prevCount = currCount
if count > h.buckets[i].count {
h.err = fmt.Errorf("%w: %g > %g", errCountNotCumulative, count, h.buckets[i].count)
return h.err
}
// Insert at the correct position unless duplicate.
h.buckets = append(h.buckets, tempHistogramBucket{})
copy(h.buckets[i+1:], h.buckets[i:])
h.buckets[i] = tempHistogramBucket{le: boundary, count: count}
}
h.PositiveBuckets[0] = absBucketCounts[0]
for i := 1; i < len(h.PositiveBuckets); i++ {
h.PositiveBuckets[i] = absBucketCounts[i] - absBucketCounts[i-1]
}
h.Sum = histogram.Sum
if histogram.Count != 0 {
total = int64(histogram.Count)
}
h.Count = uint64(total)
return h.Compact(0)
return nil
}
func newFloatHistogram(histogram TempHistogram, upperBounds []float64, bucketCounts map[float64]float64, fhBase *histogram.FloatHistogram) *histogram.FloatHistogram {
fh := fhBase.Copy()
var prevCount, total float64
for i, le := range upperBounds {
currCount, exists := bucketCounts[le]
if !exists {
currCount = 0
func (h *TempHistogram) SetCount(count float64) error {
if h.err != nil {
return h.err
}
if count < 0 {
h.err = fmt.Errorf("%w: count=%g", errNegativeCount, count)
return h.err
}
h.count = count
h.hasCount = true
return nil
}
func (h *TempHistogram) SetSum(sum float64) error {
if h.err != nil {
return h.err
}
h.sum = sum
return nil
}
func (h TempHistogram) Convert() (*histogram.Histogram, *histogram.FloatHistogram, error) {
if h.err != nil {
return nil, nil, h.err
}
if len(h.buckets) == 0 || h.buckets[len(h.buckets)-1].le != math.Inf(1) {
// No +Inf bucket.
if !h.hasCount && len(h.buckets) > 0 {
// No count either, so set count to the last known bucket's count.
h.count = h.buckets[len(h.buckets)-1].count
}
count := currCount - prevCount
fh.PositiveBuckets[i] = count
total += count
prevCount = currCount
// Let the last bucket be +Inf with the overall count.
h.buckets = append(h.buckets, tempHistogramBucket{le: math.Inf(1), count: h.count})
}
fh.Sum = histogram.Sum
if histogram.Count != 0 {
total = histogram.Count
if !h.hasCount {
h.count = h.buckets[len(h.buckets)-1].count
h.hasCount = true
}
fh.Count = total
return fh.Compact(0)
for _, b := range h.buckets {
intCount := int64(math.Round(b.count))
if b.count != float64(intCount) {
return h.convertToFloatHistogram()
}
}
intCount := uint64(math.Round(h.count))
if h.count != float64(intCount) {
return h.convertToFloatHistogram()
}
return h.convertToIntegerHistogram(intCount)
}
func (h TempHistogram) convertToIntegerHistogram(count uint64) (*histogram.Histogram, *histogram.FloatHistogram, error) {
rh := &histogram.Histogram{
Schema: histogram.CustomBucketsSchema,
Count: count,
Sum: h.sum,
PositiveSpans: []histogram.Span{{Length: uint32(len(h.buckets))}},
PositiveBuckets: make([]int64, len(h.buckets)),
}
if len(h.buckets) > 1 {
rh.CustomValues = make([]float64, len(h.buckets)-1) // Not storing the last +Inf bucket.
}
prevCount := int64(0)
prevDelta := int64(0)
for i, b := range h.buckets {
// delta is the actual bucket count as the input is cumulative.
delta := int64(b.count) - prevCount
rh.PositiveBuckets[i] = delta - prevDelta
prevCount = int64(b.count)
prevDelta = delta
if b.le != math.Inf(1) {
rh.CustomValues[i] = b.le
}
}
if count != uint64(h.buckets[len(h.buckets)-1].count) {
h.err = fmt.Errorf("%w: count=%d != le=%g count=%g", errCountMismatch, count, h.buckets[len(h.buckets)-1].le, h.buckets[len(h.buckets)-1].count)
return nil, nil, h.err
}
return rh.Compact(2), nil, nil
}
func (h TempHistogram) convertToFloatHistogram() (*histogram.Histogram, *histogram.FloatHistogram, error) {
rh := &histogram.FloatHistogram{
Schema: histogram.CustomBucketsSchema,
Count: h.count,
Sum: h.sum,
PositiveSpans: []histogram.Span{{Length: uint32(len(h.buckets))}},
PositiveBuckets: make([]float64, len(h.buckets)),
}
if len(h.buckets) > 1 {
rh.CustomValues = make([]float64, len(h.buckets)-1) // Not storing the last +Inf bucket.
}
prevCount := 0.0
for i, b := range h.buckets {
rh.PositiveBuckets[i] = b.count - prevCount
prevCount = b.count
if b.le != math.Inf(1) {
rh.CustomValues[i] = b.le
}
}
if h.count != h.buckets[len(h.buckets)-1].count {
h.err = fmt.Errorf("%w: count=%g != le=%g count=%g", errCountMismatch, h.count, h.buckets[len(h.buckets)-1].le, h.buckets[len(h.buckets)-1].count)
return nil, nil, h.err
}
return nil, rh.Compact(0), nil
}
func GetHistogramMetricBase(m labels.Labels, suffix string) labels.Labels {

View file

@ -0,0 +1,189 @@
// Copyright 2024 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 convertnhcb
import (
"math"
"testing"
"github.com/stretchr/testify/require"
"github.com/prometheus/prometheus/model/histogram"
)
func TestNHCBConvert(t *testing.T) {
tests := map[string]struct {
setup func() *TempHistogram
expectedErr error
expectedH *histogram.Histogram
expectedFH *histogram.FloatHistogram
}{
"empty": {
setup: func() *TempHistogram {
h := NewTempHistogram()
return &h
},
expectedH: &histogram.Histogram{
Schema: histogram.CustomBucketsSchema,
PositiveSpans: []histogram.Span{},
PositiveBuckets: []int64{},
},
},
"sum only": {
setup: func() *TempHistogram {
h := NewTempHistogram()
h.SetSum(1000.25)
return &h
},
expectedH: &histogram.Histogram{
Schema: histogram.CustomBucketsSchema,
Sum: 1000.25,
PositiveSpans: []histogram.Span{},
PositiveBuckets: []int64{},
},
},
"single integer bucket": {
setup: func() *TempHistogram {
h := NewTempHistogram()
h.SetSum(1000.25)
h.SetBucketCount(0.5, 1000)
return &h
},
expectedH: &histogram.Histogram{
Schema: histogram.CustomBucketsSchema,
Count: 1000,
Sum: 1000.25,
PositiveSpans: []histogram.Span{{Length: 1}},
PositiveBuckets: []int64{1000},
CustomValues: []float64{0.5},
},
},
"single float bucket": {
setup: func() *TempHistogram {
h := NewTempHistogram()
h.SetSum(1000.25)
h.SetBucketCount(0.5, 1337.42)
return &h
},
expectedFH: &histogram.FloatHistogram{
Schema: histogram.CustomBucketsSchema,
Count: 1337.42,
Sum: 1000.25,
PositiveSpans: []histogram.Span{{Length: 1}},
PositiveBuckets: []float64{1337.42},
CustomValues: []float64{0.5},
},
},
"happy case integer bucket": {
setup: func() *TempHistogram {
h := NewTempHistogram()
h.SetCount(1000)
h.SetSum(1000.25)
h.SetBucketCount(0.5, 50)
h.SetBucketCount(1.0, 950)
h.SetBucketCount(math.Inf(1), 1000)
return &h
},
expectedH: &histogram.Histogram{
Schema: histogram.CustomBucketsSchema,
Count: 1000,
Sum: 1000.25,
PositiveSpans: []histogram.Span{{Length: 3}},
PositiveBuckets: []int64{50, 850, -850},
CustomValues: []float64{0.5, 1.0},
},
},
"happy case float bucket": {
setup: func() *TempHistogram {
h := NewTempHistogram()
h.SetCount(1000)
h.SetSum(1000.25)
h.SetBucketCount(0.5, 50)
h.SetBucketCount(1.0, 950.5)
h.SetBucketCount(math.Inf(1), 1000)
return &h
},
expectedFH: &histogram.FloatHistogram{
Schema: histogram.CustomBucketsSchema,
Count: 1000,
Sum: 1000.25,
PositiveSpans: []histogram.Span{{Length: 3}},
PositiveBuckets: []float64{50, 900.5, 49.5},
CustomValues: []float64{0.5, 1.0},
},
},
"non cumulative bucket": {
setup: func() *TempHistogram {
h := NewTempHistogram()
h.SetCount(1000)
h.SetSum(1000.25)
h.SetBucketCount(0.5, 50)
h.SetBucketCount(1.0, 950)
h.SetBucketCount(math.Inf(1), 900)
return &h
},
expectedErr: errCountNotCumulative,
},
"negative count": {
setup: func() *TempHistogram {
h := NewTempHistogram()
h.SetCount(-1000)
h.SetSum(1000.25)
h.SetBucketCount(0.5, 50)
h.SetBucketCount(1.0, 950)
h.SetBucketCount(math.Inf(1), 900)
return &h
},
expectedErr: errNegativeCount,
},
"mixed order": {
setup: func() *TempHistogram {
h := NewTempHistogram()
h.SetBucketCount(0.5, 50)
h.SetBucketCount(math.Inf(1), 1000)
h.SetBucketCount(1.0, 950)
h.SetCount(1000)
h.SetSum(1000.25)
return &h
},
expectedH: &histogram.Histogram{
Schema: histogram.CustomBucketsSchema,
Count: 1000,
Sum: 1000.25,
PositiveSpans: []histogram.Span{{Length: 3}},
PositiveBuckets: []int64{50, 850, -850},
CustomValues: []float64{0.5, 1.0},
},
},
}
for name, test := range tests {
t.Run(name, func(t *testing.T) {
th := test.setup()
h, fh, err := th.Convert()
if test.expectedErr != nil {
require.ErrorIs(t, err, test.expectedErr)
return
}
require.Equal(t, test.expectedH, h)
if h != nil {
require.NoError(t, h.Validate())
}
require.Equal(t, test.expectedFH, fh)
if fh != nil {
require.NoError(t, fh.Validate())
}
})
}
}