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[REFACTOR] PromQL: DRY `stddev` and `stdvar` functions (#16451) 

* DRY stddev and stdvar

---------

Signed-off-by: Neeraj Gartia <neerajgartia211002@gmail.com>
This commit is contained in:
Neeraj Gartia 2025-04-20 14:47:03 +05:30 committed by GitHub
parent 5afa652a83
commit a511164615
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GPG Key ID: B5690EEEBB952194
1 changed files with 27 additions and 71 deletions
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98
promql/functions.go
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@ -932,8 +932,7 @@ func funcQuantileOverTime(vals []parser.Value, args parser.Expressions, enh *Eva
return append(enh.Out, Sample{F: quantile(q, values)}), annos
}
// === stddev_over_time(Matrix parser.ValueTypeMatrix) (Vector, Annotations) ===
func funcStddevOverTime(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
func varianceOverTime(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper, varianceToResult func(float64) float64) (Vector, annotations.Annotations) {
samples := vals[0].(Matrix)[0]
var annos annotations.Annotations
if len(samples.Floats) == 0 {
@ -953,33 +952,22 @@ func funcStddevOverTime(vals []parser.Value, args parser.Expressions, enh *EvalN
mean, cMean = kahanSumInc(delta/count, mean, cMean)
aux, cAux = kahanSumInc(delta*(f.F-(mean+cMean)), aux, cAux)
}
return math.Sqrt((aux + cAux) / count)
variance := (aux + cAux) / count
if varianceToResult == nil {
return variance
}
return varianceToResult(variance)
}), annos
}
// === stddev_over_time(Matrix parser.ValueTypeMatrix) (Vector, Annotations) ===
func funcStddevOverTime(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
return varianceOverTime(vals, args, enh, math.Sqrt)
}
// === stdvar_over_time(Matrix parser.ValueTypeMatrix) (Vector, Annotations) ===
func funcStdvarOverTime(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
samples := vals[0].(Matrix)[0]
var annos annotations.Annotations
if len(samples.Floats) == 0 {
return enh.Out, nil
}
if len(samples.Histograms) > 0 {
metricName := samples.Metric.Get(labels.MetricName)
annos.Add(annotations.NewHistogramIgnoredInMixedRangeInfo(metricName, args[0].PositionRange()))
}
return aggrOverTime(vals, enh, func(s Series) float64 {
var count float64
var mean, cMean float64
var aux, cAux float64
for _, f := range s.Floats {
count++
delta := f.F - (mean + cMean)
mean, cMean = kahanSumInc(delta/count, mean, cMean)
aux, cAux = kahanSumInc(delta*(f.F-(mean+cMean)), aux, cAux)
}
return (aux + cAux) / count
}), annos
return varianceOverTime(vals, args, enh, nil)
}
// === absent(Vector parser.ValueTypeVector) (Vector, Annotations) ===
@ -1347,11 +1335,9 @@ func funcHistogramAvg(vals []parser.Value, _ parser.Expressions, enh *EvalNodeHe
return enh.Out, nil
}
// === histogram_stddev(Vector parser.ValueTypeVector) (Vector, Annotations) ===
func funcHistogramStdDev(vals []parser.Value, _ parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
inVec := vals[0].(Vector)
for _, sample := range inVec {
func histogramVariance(vals []parser.Value, enh *EvalNodeHelper, varianceToResult func(float64) float64) (Vector, annotations.Annotations) {
vec := vals[0].(Vector)
for _, sample := range vec {
// Skip non-histogram samples.
if sample.H == nil {
continue
@ -1381,48 +1367,8 @@ func funcHistogramStdDev(vals []parser.Value, _ parser.Expressions, enh *EvalNod
if !enh.enableDelayedNameRemoval {
sample.Metric = sample.Metric.DropMetricName()
}
enh.Out = append(enh.Out, Sample{
Metric: sample.Metric,
F: math.Sqrt(variance),
DropName: true,
})
}
return enh.Out, nil
}
// === histogram_stdvar(Vector parser.ValueTypeVector) (Vector, Annotations) ===
func funcHistogramStdVar(vals []parser.Value, _ parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
inVec := vals[0].(Vector)
for _, sample := range inVec {
// Skip non-histogram samples.
if sample.H == nil {
continue
}
mean := sample.H.Sum / sample.H.Count
var variance, cVariance float64
it := sample.H.AllBucketIterator()
for it.Next() {
bucket := it.At()
if bucket.Count == 0 {
continue
}
var val float64
if bucket.Lower <= 0 && 0 <= bucket.Upper {
val = 0
} else {
val = math.Sqrt(bucket.Upper * bucket.Lower)
if bucket.Upper < 0 {
val = -val
}
}
delta := val - mean
variance, cVariance = kahanSumInc(bucket.Count*delta*delta, variance, cVariance)
}
variance += cVariance
variance /= sample.H.Count
if !enh.enableDelayedNameRemoval {
sample.Metric = sample.Metric.DropMetricName()
if varianceToResult != nil {
variance = varianceToResult(variance)
}
enh.Out = append(enh.Out, Sample{
Metric: sample.Metric,
@ -1433,6 +1379,16 @@ func funcHistogramStdVar(vals []parser.Value, _ parser.Expressions, enh *EvalNod
return enh.Out, nil
}
// === histogram_stddev(Vector parser.ValueTypeVector) (Vector, Annotations) ===
func funcHistogramStdDev(vals []parser.Value, _ parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
return histogramVariance(vals, enh, math.Sqrt)
}
// === histogram_stdvar(Vector parser.ValueTypeVector) (Vector, Annotations) ===
func funcHistogramStdVar(vals []parser.Value, _ parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
return histogramVariance(vals, enh, nil)
}
// === histogram_fraction(lower, upper parser.ValueTypeScalar, Vector parser.ValueTypeVector) (Vector, Annotations) ===
func funcHistogramFraction(vals []parser.Value, _ parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
lower := vals[0].(Vector)[0].F