mirror of
https://github.com/prometheus/prometheus.git
synced 2025-12-03 16:41:05 +01:00
fix: Added Unroll support to Sparse NHCBs
Signed-off-by: Naman-B-Parlecha <namanparlecha@gmail.com>
This commit is contained in:
Naman-B-Parlecha
parent
167cb350f1
commit
1df1f53ea0
@ -1,4 +1,4 @@
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// Copyright 2025 The Prometheus Authors
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// Copyright 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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@ -30,6 +30,9 @@ func ConvertNHCBToClassic(nhcb any, lset labels.Labels, lsetBuilder *labels.Buil
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return errors.New("metric name label '__name__' is missing")
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}
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// We preserve original labels and restore them after conversion.
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// This is to ensure that no modifications are made to the original labels
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// that the queue_manager relies on.
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oldLabels := lsetBuilder.Labels()
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defer lsetBuilder.Reset(oldLabels)
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@ -37,6 +40,8 @@ func ConvertNHCBToClassic(nhcb any, lset labels.Labels, lsetBuilder *labels.Buil
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customValues []float64
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positiveBuckets []float64
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count, sum float64
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idx int // This index is to track buckets in Classic Histogram
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currIdx int // This index is to track buckets in Native Histogram
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)
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switch h := nhcb.(type) {
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@ -44,13 +49,35 @@ func ConvertNHCBToClassic(nhcb any, lset labels.Labels, lsetBuilder *labels.Buil
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if !IsCustomBucketsSchema(h.Schema) {
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return errors.New("unsupported histogram schema, not a NHCB")
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}
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filledBuckets := 0
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totalBuckets := 0
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for _, span := range h.PositiveSpans {
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filledBuckets += int(span.Length)
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totalBuckets += int(span.Offset) + int(span.Length)
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}
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if filledBuckets != len(h.PositiveBuckets) {
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return errors.New("mismatched lengths of positive buckets and spans")
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}
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if totalBuckets > len(h.CustomValues) {
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return errors.New("mismatched lengths of custom values and buckets from span calculation")
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}
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customValues = h.CustomValues
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positiveBuckets = make([]float64, len(h.PositiveBuckets))
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for i, v := range h.PositiveBuckets {
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if i == 0 {
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positiveBuckets[i] = float64(v)
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} else {
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positiveBuckets[i] = float64(v) + positiveBuckets[i-1]
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positiveBuckets = make([]float64, len(customValues))
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// Histograms are in delta format so we first bring them to absolute format.
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acc := int64(0)
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for _, s := range h.PositiveSpans {
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for i := 0; i < int(s.Offset); i++ {
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positiveBuckets[idx] = float64(acc)
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idx++
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}
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for i := 0; i < int(s.Length); i++ {
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acc += h.PositiveBuckets[currIdx]
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positiveBuckets[idx] = float64(acc)
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idx++
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currIdx++
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}
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}
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count = float64(h.Count)
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@ -59,8 +86,34 @@ func ConvertNHCBToClassic(nhcb any, lset labels.Labels, lsetBuilder *labels.Buil
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if !IsCustomBucketsSchema(h.Schema) {
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return errors.New("unsupported histogram schema, not a NHCB")
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}
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filledBuckets := 0
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totalBuckets := 0
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for _, s := range h.PositiveSpans {
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filledBuckets += int(s.Length)
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totalBuckets += int(s.Offset) + int(s.Length)
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}
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if filledBuckets != len(h.PositiveBuckets) {
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return errors.New("mismatched lengths of positive buckets and spans")
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}
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if totalBuckets > len(h.CustomValues) {
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return errors.New("mismatched lengths of custom values and buckets from span calculation")
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}
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customValues = h.CustomValues
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positiveBuckets = h.PositiveBuckets
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positiveBuckets = make([]float64, len(customValues))
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for _, span := range h.PositiveSpans {
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// Since Float Histogram is already in absolute format we should
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// keep the sparse buckets empty so we jump and go to next filled
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// bucket index.
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idx += int(span.Offset)
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for i := 0; i < int(span.Length); i++ {
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positiveBuckets[idx] = h.PositiveBuckets[currIdx]
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idx++
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currIdx++
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}
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}
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count = h.Count
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sum = h.Sum
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default:
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@ -75,11 +128,11 @@ func ConvertNHCBToClassic(nhcb any, lset labels.Labels, lsetBuilder *labels.Buil
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}
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currCount := float64(0)
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for i := range customValues {
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currCount = positiveBuckets[i]
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for i, val := range customValues {
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currCount += positiveBuckets[i]
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lsetBuilder.Reset(lset)
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lsetBuilder.Set("__name__", baseName+"_bucket")
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lsetBuilder.Set("le", labels.FormatOpenMetricsFloat(customValues[i]))
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lsetBuilder.Set("le", labels.FormatOpenMetricsFloat(val))
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if err := emitSeriesFn(lsetBuilder.Labels(), currCount); err != nil {
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return err
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}
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@ -1,11 +1,11 @@
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// Copyright 2025 The Prometheus Authors
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// Copyright 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 filset elabels.FromStrings("__name__", "test_metric", "le",)xcept in compliance with 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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// Unlsetsslabels.FromStrings("__name__", "test_metric", "le",) required by applicablset llabels.FromStrings("__name__", "test_metric", "le",)aw or agreed to in writing, software
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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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@ -39,17 +39,20 @@ func TestConvertNHCBToClassicHistogram(t *testing.T) {
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nhcb: &Histogram{
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CustomValues: []float64{1, 2, 3},
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PositiveBuckets: []int64{10, 20, 30},
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Count: 60,
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Sum: 100.0,
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Schema: -53,
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PositiveSpans: []Span{
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{Offset: 0, Length: 3},
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},
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Count: 100,
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Sum: 100.0,
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Schema: CustomBucketsSchema,
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},
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labels: labels.FromStrings("__name__", "test_metric"),
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expected: []sample{
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "1.0"), val: 10},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "2.0"), val: 30},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "3.0"), val: 60},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "+Inf"), val: 60},
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{lset: labels.FromStrings("__name__", "test_metric_count"), val: 60},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "2.0"), val: 40},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "3.0"), val: 100},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "+Inf"), val: 100},
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{lset: labels.FromStrings("__name__", "test_metric_count"), val: 100},
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{lset: labels.FromStrings("__name__", "test_metric_sum"), val: 100},
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},
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},
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@ -57,18 +60,21 @@ func TestConvertNHCBToClassicHistogram(t *testing.T) {
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name: "valid floatHistogram",
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nhcb: &FloatHistogram{
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CustomValues: []float64{1, 2, 3},
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PositiveBuckets: []float64{20.0, 40.0, 60.0},
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Count: 60.0,
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Sum: 100.0,
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Schema: -53,
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PositiveBuckets: []float64{20.0, 40.0, 60.0}, // 20 -> 60 ->120
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PositiveSpans: []Span{
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{Offset: 0, Length: 3},
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},
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Count: 120.0,
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Sum: 100.0,
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Schema: CustomBucketsSchema,
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},
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labels: labels.FromStrings("__name__", "test_metric"),
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expected: []sample{
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "1.0"), val: 20},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "2.0"), val: 40},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "3.0"), val: 60},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "+Inf"), val: 60},
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{lset: labels.FromStrings("__name__", "test_metric_count"), val: 60},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "2.0"), val: 60},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "3.0"), val: 120},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "+Inf"), val: 120},
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{lset: labels.FromStrings("__name__", "test_metric_count"), val: 120},
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{lset: labels.FromStrings("__name__", "test_metric_sum"), val: 100},
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},
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},
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@ -77,9 +83,10 @@ func TestConvertNHCBToClassicHistogram(t *testing.T) {
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nhcb: &Histogram{
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CustomValues: []float64{},
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PositiveBuckets: []int64{},
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PositiveSpans: []Span{},
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Count: 0,
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Sum: 0.0,
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Schema: -53,
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Schema: CustomBucketsSchema,
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},
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labels: labels.FromStrings("__name__", "test_metric"),
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expected: []sample{
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@ -93,9 +100,9 @@ func TestConvertNHCBToClassicHistogram(t *testing.T) {
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nhcb: &Histogram{
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CustomValues: []float64{1, 2, 3},
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PositiveBuckets: []int64{10, 20, 30},
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Count: 60,
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Count: 100,
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Sum: 100.0,
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Schema: -53,
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Schema: CustomBucketsSchema,
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},
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labels: labels.FromStrings("job", "test_job"),
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expectErr: true,
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@ -111,28 +118,45 @@ func TestConvertNHCBToClassicHistogram(t *testing.T) {
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nhcb: &Histogram{
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CustomValues: []float64{1, 2, 3},
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PositiveBuckets: []int64{0, 10, 0},
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Count: 10,
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Sum: 50.0,
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Schema: -53,
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PositiveSpans: []Span{
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{Offset: 0, Length: 3},
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},
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Count: 20,
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Sum: 50.0,
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Schema: CustomBucketsSchema,
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},
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labels: labels.FromStrings("__name__", "test_metric"),
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expected: []sample{
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "1.0"), val: 0},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "2.0"), val: 10},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "3.0"), val: 10},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "+Inf"), val: 10},
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{lset: labels.FromStrings("__name__", "test_metric_count"), val: 10},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "3.0"), val: 20},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "+Inf"), val: 20},
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{lset: labels.FromStrings("__name__", "test_metric_count"), val: 20},
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{lset: labels.FromStrings("__name__", "test_metric_sum"), val: 50},
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},
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},
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{
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name: "mismatched bucket lengths",
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name: "mismatched bucket lengths with more filled bucket count",
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nhcb: &Histogram{
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CustomValues: []float64{1, 2},
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PositiveBuckets: []int64{10, 20, 30},
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Count: 60,
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PositiveSpans: []Span{{Offset: 0, Length: 3}},
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Count: 100,
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Sum: 100.0,
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Schema: -53,
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Schema: CustomBucketsSchema,
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},
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labels: labels.FromStrings("__name__", "test_metric_bucket"),
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expectErr: true,
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},
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{
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name: "mismatched bucket lengths with less filled bucket count",
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nhcb: &Histogram{
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CustomValues: []float64{1, 2},
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PositiveBuckets: []int64{10},
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PositiveSpans: []Span{{Offset: 0, Length: 2}},
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Count: 100,
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Sum: 100.0,
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Schema: CustomBucketsSchema,
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},
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labels: labels.FromStrings("__name__", "test_metric_bucket"),
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expectErr: true,
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@ -142,9 +166,12 @@ func TestConvertNHCBToClassicHistogram(t *testing.T) {
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nhcb: &Histogram{
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CustomValues: []float64{1},
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PositiveBuckets: []int64{10},
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Count: 10,
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Sum: 20.0,
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Schema: -53,
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PositiveSpans: []Span{
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{Offset: 0, Length: 1},
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},
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Count: 10,
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Sum: 20.0,
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Schema: CustomBucketsSchema,
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},
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labels: labels.FromStrings("__name__", "test_metric"),
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expected: []sample{
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@ -159,9 +186,12 @@ func TestConvertNHCBToClassicHistogram(t *testing.T) {
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nhcb: &Histogram{
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CustomValues: []float64{1},
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PositiveBuckets: []int64{10},
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Count: 10,
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Sum: 20.0,
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Schema: -53,
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PositiveSpans: []Span{
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{Offset: 0, Length: 1},
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},
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Count: 10,
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Sum: 20.0,
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Schema: CustomBucketsSchema,
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},
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labels: labels.FromStrings("__name__", "test_metric", "job", "test_job", "instance", "localhost:9090"),
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expected: []sample{
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@ -193,6 +223,68 @@ func TestConvertNHCBToClassicHistogram(t *testing.T) {
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labels: labels.FromStrings("__name__", "test_metric_bucket"),
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expectErr: true,
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},
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{
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name: "sparse histogram",
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nhcb: &Histogram{
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Schema: CustomBucketsSchema,
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CustomValues: []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10},
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PositiveSpans: []Span{
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{0, 2},
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{4, 1},
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{1, 2},
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},
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PositiveBuckets: []int64{1, 2, 3, 4, 5}, // 1 -> 3 -> 3 -> 3 -> 3 -> 3 -> 6 ->6 ->10 -> 15
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Count: 53, // 1 -> 4 -> 7 -> 10 -> 13 -> 16 -> 22 -> 28 -> 38 -> 53
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Sum: 123,
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},
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labels: labels.FromStrings("__name__", "test_metric"),
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expected: []sample{
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "1.0"), val: 1},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "2.0"), val: 4},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "3.0"), val: 7},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "4.0"), val: 10},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "5.0"), val: 13},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "6.0"), val: 16},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "7.0"), val: 22},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "8.0"), val: 28},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "9.0"), val: 38},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "10.0"), val: 53},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "+Inf"), val: 53},
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{lset: labels.FromStrings("__name__", "test_metric_count"), val: 53},
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{lset: labels.FromStrings("__name__", "test_metric_sum"), val: 123},
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},
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},
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{
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name: "sparse float histogram",
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nhcb: &FloatHistogram{
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Schema: CustomBucketsSchema,
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CustomValues: []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10},
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PositiveSpans: []Span{
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{0, 2},
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{4, 1},
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{1, 2},
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},
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PositiveBuckets: []float64{1, 2, 3, 4, 5}, // 1 -> 2 -> 0 -> 0 -> 0 -> 0 -> 3 -> 0 -> 4 -> 5
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Count: 15, // 1 -> 3 -> 3 -> 3 -> 3 -> 3 -> 6 -> 6 -> 10 -> 15
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Sum: 123,
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},
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labels: labels.FromStrings("__name__", "test_metric"),
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expected: []sample{
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "1.0"), val: 1},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "2.0"), val: 3},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "3.0"), val: 3},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "4.0"), val: 3},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "5.0"), val: 3},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "6.0"), val: 3},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "7.0"), val: 6},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "8.0"), val: 6},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "9.0"), val: 10},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "10.0"), val: 15},
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{lset: labels.FromStrings("__name__", "test_metric_bucket", "le", "+Inf"), val: 15},
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{lset: labels.FromStrings("__name__", "test_metric_count"), val: 15},
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{lset: labels.FromStrings("__name__", "test_metric_sum"), val: 123},
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},
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},
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}
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labelBuilder := labels.NewBuilder(labels.EmptyLabels())
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@ -1,4 +1,4 @@
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// Copyright 2025 The Prometheus Authors
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// Copyright 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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