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In general aim for the happy case when the exposer lists the buckets
in ascending order.
Use Compact(2) to compact the result of nhcb convert.
This is more in line with how client_golang optimizes spans vs
buckets.
aef8aedb4b/prometheus/histogram.go (L1485)
Signed-off-by: György Krajcsovits <gyorgy.krajcsovits@grafana.com>
190 lines
5 KiB
Go
190 lines
5 KiB
Go
// Copyright 2024 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 convertnhcb
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import (
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"math"
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"testing"
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"github.com/stretchr/testify/require"
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"github.com/prometheus/prometheus/model/histogram"
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)
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func TestNHCBConvert(t *testing.T) {
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tests := map[string]struct {
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setup func() *TempHistogram
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expectedErr error
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expectedH *histogram.Histogram
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expectedFH *histogram.FloatHistogram
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}{
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"empty": {
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setup: func() *TempHistogram {
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h := NewTempHistogram()
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return &h
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},
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expectedH: &histogram.Histogram{
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Schema: histogram.CustomBucketsSchema,
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PositiveSpans: []histogram.Span{},
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PositiveBuckets: []int64{},
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},
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},
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"sum only": {
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setup: func() *TempHistogram {
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h := NewTempHistogram()
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h.SetSum(1000.25)
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return &h
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},
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expectedH: &histogram.Histogram{
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Schema: histogram.CustomBucketsSchema,
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Sum: 1000.25,
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PositiveSpans: []histogram.Span{},
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PositiveBuckets: []int64{},
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},
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},
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"single integer bucket": {
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setup: func() *TempHistogram {
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h := NewTempHistogram()
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h.SetSum(1000.25)
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h.SetBucketCount(0.5, 1000)
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return &h
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},
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expectedH: &histogram.Histogram{
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Schema: histogram.CustomBucketsSchema,
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Count: 1000,
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Sum: 1000.25,
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PositiveSpans: []histogram.Span{{Length: 1}},
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PositiveBuckets: []int64{1000},
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CustomValues: []float64{0.5},
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},
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},
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"single float bucket": {
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setup: func() *TempHistogram {
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h := NewTempHistogram()
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h.SetSum(1000.25)
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h.SetBucketCount(0.5, 1337.42)
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return &h
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},
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expectedFH: &histogram.FloatHistogram{
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Schema: histogram.CustomBucketsSchema,
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Count: 1337.42,
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Sum: 1000.25,
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PositiveSpans: []histogram.Span{{Length: 1}},
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PositiveBuckets: []float64{1337.42},
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CustomValues: []float64{0.5},
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},
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},
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"happy case integer bucket": {
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setup: func() *TempHistogram {
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h := NewTempHistogram()
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h.SetCount(1000)
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h.SetSum(1000.25)
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h.SetBucketCount(0.5, 50)
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h.SetBucketCount(1.0, 950)
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h.SetBucketCount(math.Inf(1), 1000)
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return &h
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},
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expectedH: &histogram.Histogram{
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Schema: histogram.CustomBucketsSchema,
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Count: 1000,
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Sum: 1000.25,
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PositiveSpans: []histogram.Span{{Length: 3}},
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PositiveBuckets: []int64{50, 850, -850},
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CustomValues: []float64{0.5, 1.0},
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},
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},
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"happy case float bucket": {
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setup: func() *TempHistogram {
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h := NewTempHistogram()
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h.SetCount(1000)
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h.SetSum(1000.25)
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h.SetBucketCount(0.5, 50)
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h.SetBucketCount(1.0, 950.5)
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h.SetBucketCount(math.Inf(1), 1000)
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return &h
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},
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expectedFH: &histogram.FloatHistogram{
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Schema: histogram.CustomBucketsSchema,
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Count: 1000,
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Sum: 1000.25,
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PositiveSpans: []histogram.Span{{Length: 3}},
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PositiveBuckets: []float64{50, 900.5, 49.5},
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CustomValues: []float64{0.5, 1.0},
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},
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},
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"non cumulative bucket": {
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setup: func() *TempHistogram {
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h := NewTempHistogram()
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h.SetCount(1000)
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h.SetSum(1000.25)
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h.SetBucketCount(0.5, 50)
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h.SetBucketCount(1.0, 950)
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h.SetBucketCount(math.Inf(1), 900)
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return &h
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},
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expectedErr: errCountNotCumulative,
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},
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"negative count": {
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setup: func() *TempHistogram {
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h := NewTempHistogram()
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h.SetCount(-1000)
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h.SetSum(1000.25)
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h.SetBucketCount(0.5, 50)
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h.SetBucketCount(1.0, 950)
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h.SetBucketCount(math.Inf(1), 900)
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return &h
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},
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expectedErr: errNegativeCount,
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},
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"mixed order": {
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setup: func() *TempHistogram {
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h := NewTempHistogram()
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h.SetBucketCount(0.5, 50)
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h.SetBucketCount(math.Inf(1), 1000)
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h.SetBucketCount(1.0, 950)
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h.SetCount(1000)
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h.SetSum(1000.25)
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return &h
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},
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expectedH: &histogram.Histogram{
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Schema: histogram.CustomBucketsSchema,
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Count: 1000,
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Sum: 1000.25,
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PositiveSpans: []histogram.Span{{Length: 3}},
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PositiveBuckets: []int64{50, 850, -850},
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CustomValues: []float64{0.5, 1.0},
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},
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},
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}
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for name, test := range tests {
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t.Run(name, func(t *testing.T) {
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th := test.setup()
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h, fh, err := th.Convert()
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if test.expectedErr != nil {
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require.ErrorIs(t, err, test.expectedErr)
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return
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}
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require.Equal(t, test.expectedH, h)
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if h != nil {
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require.NoError(t, h.Validate())
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}
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require.Equal(t, test.expectedFH, fh)
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if fh != nil {
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require.NoError(t, fh.Validate())
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}
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})
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}
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}
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