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PromQL: Add histogram_quantiles variadic function
Signed-off-by: Linas Medziunas <linas.medziunas@gmail.com>
This commit is contained in:
Linas Medziunas
parent
f4b8840f51
commit
dd4783e6c2
5 changed files with 226 additions and 4 deletions
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@ -1159,6 +1159,9 @@ type EvalNodeHelper struct {
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// funcHistogramQuantile and funcHistogramFraction for classic histograms.
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signatureToMetricWithBuckets map[string]*metricWithBuckets
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nativeHistogramSamples []Sample
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// funcHistogramQuantiles for histograms.
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quantileStrs map[float64]string
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signatureToLabelsWithQuantile map[string]map[float64]labels.Labels
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lb *labels.Builder
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lblBuf []byte
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@ -1246,6 +1249,35 @@ func (enh *EvalNodeHelper) resetHistograms(inVec Vector, arg parser.Expr) annota
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return annos
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}
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func (enh *EvalNodeHelper) getOrCreateLblsWithQuantile(lbls labels.Labels, quantileLabel string, q float64) labels.Labels {
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if enh.signatureToLabelsWithQuantile == nil {
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enh.signatureToLabelsWithQuantile = make(map[string]map[float64]labels.Labels)
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}
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enh.lblBuf = lbls.Bytes(enh.lblBuf)
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cachedLbls, ok := enh.signatureToLabelsWithQuantile[string(enh.lblBuf)]
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if !ok {
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cachedLbls = make(map[float64]labels.Labels, len(enh.quantileStrs))
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enh.signatureToLabelsWithQuantile[string(enh.lblBuf)] = cachedLbls
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}
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cachedLblsWithQuantile, ok := cachedLbls[q]
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if !ok {
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quantileStr := "NaN"
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if !math.IsNaN(q) {
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// Cannot do map lookup by NaN key.
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quantileStr = enh.quantileStrs[q]
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}
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cachedLblsWithQuantile = labels.NewBuilder(lbls).
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Set(quantileLabel, quantileStr).
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Labels()
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cachedLbls[q] = cachedLblsWithQuantile
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}
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return cachedLblsWithQuantile
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}
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// rangeEval evaluates the given expressions, and then for each step calls
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// the given funcCall with the values computed for each expression at that
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// step. The return value is the combination into time series of all the
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@ -4072,7 +4104,7 @@ func detectHistogramStatsDecoding(expr parser.Expr) {
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// further up (the latter wouldn't make sense,
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// but no harm in detecting it).
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n.SkipHistogramBuckets = true
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case "histogram_quantile", "histogram_fraction":
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case "histogram_quantile", "histogram_quantiles", "histogram_fraction":
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// If we ever see a function that needs the
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// whole histogram, we will not skip the
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// buckets.
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@ -1612,8 +1612,8 @@ func funcHistogramQuantile(vectorVals []Vector, _ Matrix, args parser.Expression
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inVec := vectorVals[1]
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var annos annotations.Annotations
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if math.IsNaN(q) || q < 0 || q > 1 {
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annos.Add(annotations.NewInvalidQuantileWarning(q, args[0].PositionRange()))
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if err := validateQuantile(q, args[0]); err != nil {
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annos.Add(err)
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}
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annos.Merge(enh.resetHistograms(inVec, args[1]))
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@ -1662,6 +1662,89 @@ func funcHistogramQuantile(vectorVals []Vector, _ Matrix, args parser.Expression
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return enh.Out, annos
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}
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func validateQuantile(q float64, arg parser.Expr) error {
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if math.IsNaN(q) || q < 0 || q > 1 {
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return annotations.NewInvalidQuantileWarning(q, arg.PositionRange())
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}
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return nil
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}
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// === histogram_quantiles(Vector parser.ValueTypeVector, label parser.ValueTypeString, q0 parser.ValueTypeScalar, qs parser.ValueTypeScalar...) (Vector, Annotations) ===
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func funcHistogramQuantiles(vectorVals []Vector, _ Matrix, args parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
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var (
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inVec = vectorVals[0]
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quantileLabel = args[1].(*parser.StringLiteral).Val
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numQuantiles = len(vectorVals[2:])
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qs = make([]float64, 0, numQuantiles)
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annos annotations.Annotations
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)
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if enh.quantileStrs == nil {
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enh.quantileStrs = make(map[float64]string, numQuantiles)
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}
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for i := 2; i < len(vectorVals); i++ {
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q := vectorVals[i][0].F
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if err := validateQuantile(q, args[i]); err != nil {
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annos.Add(err)
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}
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if _, ok := enh.quantileStrs[q]; !ok {
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enh.quantileStrs[q] = fmt.Sprintf("%g", q)
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}
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qs = append(qs, q)
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}
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annos.Merge(enh.resetHistograms(inVec, args[0]))
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for _, q := range qs {
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// Deal with the native histograms.
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for _, sample := range enh.nativeHistogramSamples {
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if sample.H == nil {
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// Native histogram conflicts with classic histogram at the same timestamp, ignore.
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continue
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}
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if !enh.enableDelayedNameRemoval {
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sample.Metric = sample.Metric.DropReserved(schema.IsMetadataLabel)
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}
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hq, hqAnnos := HistogramQuantile(q, sample.H, sample.Metric.Get(model.MetricNameLabel), args[0].PositionRange())
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annos.Merge(hqAnnos)
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enh.Out = append(enh.Out, Sample{
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Metric: enh.getOrCreateLblsWithQuantile(sample.Metric, quantileLabel, q),
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F: hq,
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DropName: true,
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})
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}
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// Deal with classic histograms that have already been filtered for conflicting native histograms.
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for _, mb := range enh.signatureToMetricWithBuckets {
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if len(mb.buckets) > 0 {
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hq, forcedMonotonicity, _ := BucketQuantile(q, mb.buckets)
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if forcedMonotonicity {
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if enh.enableDelayedNameRemoval {
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annos.Add(annotations.NewHistogramQuantileForcedMonotonicityInfo(mb.metric.Get(labels.MetricName), args[0].PositionRange()))
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} else {
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annos.Add(annotations.NewHistogramQuantileForcedMonotonicityInfo("", args[0].PositionRange()))
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}
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}
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if !enh.enableDelayedNameRemoval {
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mb.metric = mb.metric.DropReserved(schema.IsMetadataLabel)
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}
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enh.Out = append(enh.Out, Sample{
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Metric: enh.getOrCreateLblsWithQuantile(mb.metric, quantileLabel, q),
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F: hq,
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DropName: true,
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})
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}
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}
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}
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return enh.Out, annos
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}
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// pickFirstSampleIndex returns the index of the last sample before
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// or at the range start, or 0 if none exist before the range start.
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// If the vector selector is not anchored, it always returns 0.
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@ -1982,6 +2065,7 @@ var FunctionCalls = map[string]FunctionCall{
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"histogram_count": funcHistogramCount,
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"histogram_fraction": funcHistogramFraction,
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"histogram_quantile": funcHistogramQuantile,
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"histogram_quantiles": funcHistogramQuantiles,
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"histogram_sum": funcHistogramSum,
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"histogram_stddev": funcHistogramStdDev,
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"histogram_stdvar": funcHistogramStdVar,
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@ -208,6 +208,13 @@ var Functions = map[string]*Function{
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ArgTypes: []ValueType{ValueTypeScalar, ValueTypeVector},
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ReturnType: ValueTypeVector,
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},
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"histogram_quantiles": {
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Name: "histogram_quantiles",
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ArgTypes: []ValueType{ValueTypeVector, ValueTypeString, ValueTypeScalar, ValueTypeScalar},
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Variadic: 10,
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ReturnType: ValueTypeVector,
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Experimental: true,
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},
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"double_exponential_smoothing": {
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Name: "double_exponential_smoothing",
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ArgTypes: []ValueType{ValueTypeMatrix, ValueTypeScalar, ValueTypeScalar},
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86
promql/promqltest/testdata/histograms.test
vendored
86
promql/promqltest/testdata/histograms.test
vendored
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@ -221,6 +221,40 @@ eval instant at 50m histogram_quantile(1, testhistogram3_bucket)
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{start="positive"} 1
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{start="negative"} -0.1
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eval instant at 50m histogram_quantiles(testhistogram3, "q", 0, 0.25, 0.5, 0.75, 1)
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expect no_warn
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{q="0", start="positive"} 0
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{q="0", start="negative"} -0.25
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{q="0.25", start="positive"} 0.055
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{q="0.25", start="negative"} -0.225
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{q="0.5", start="positive"} 0.125
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{q="0.5", start="negative"} -0.2
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{q="0.75", start="positive"} 0.45
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{q="0.75", start="negative"} -0.15
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{q="1", start="positive"} 1
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{q="1", start="negative"} -0.1
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eval instant at 50m histogram_quantiles(testhistogram3_bucket, "q", 0, 0.25, 0.5, 0.75, 1)
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expect no_warn
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{q="0", start="positive"} 0
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{q="0", start="negative"} -0.25
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{q="0.25", start="positive"} 0.055
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{q="0.25", start="negative"} -0.225
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{q="0.5", start="positive"} 0.125
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{q="0.5", start="negative"} -0.2
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{q="0.75", start="positive"} 0.45
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{q="0.75", start="negative"} -0.15
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{q="1", start="positive"} 1
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{q="1", start="negative"} -0.1
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# Break label set uniqueness.
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eval instant at 50m histogram_quantiles(testhistogram3, "start", 0, 0.25, 0.5, 0.75, 1)
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expect fail
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eval instant at 50m histogram_quantiles(testhistogram3_bucket, "start", 0, 0.25, 0.5, 0.75, 1)
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expect fail
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# Quantile too low.
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eval instant at 50m histogram_quantile(-0.1, testhistogram)
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@ -233,6 +267,16 @@ eval instant at 50m histogram_quantile(-0.1, testhistogram_bucket)
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{start="positive"} -Inf
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{start="negative"} -Inf
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eval instant at 50m histogram_quantiles(testhistogram, "q", -0.1)
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expect warn
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{q="-0.1", start="positive"} -Inf
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{q="-0.1", start="negative"} -Inf
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eval instant at 50m histogram_quantiles(testhistogram_bucket, "q", -0.1)
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expect warn
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{q="-0.1", start="positive"} -Inf
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{q="-0.1", start="negative"} -Inf
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# Quantile too high.
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eval instant at 50m histogram_quantile(1.01, testhistogram)
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@ -245,6 +289,16 @@ eval instant at 50m histogram_quantile(1.01, testhistogram_bucket)
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{start="positive"} +Inf
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{start="negative"} +Inf
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eval instant at 50m histogram_quantiles(testhistogram, "q", 1.01)
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expect warn
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{q="1.01", start="positive"} +Inf
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{q="1.01", start="negative"} +Inf
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eval instant at 50m histogram_quantiles(testhistogram_bucket, "q", 1.01)
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expect warn
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{q="1.01", start="positive"} +Inf
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{q="1.01", start="negative"} +Inf
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# Quantile invalid.
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eval instant at 50m histogram_quantile(NaN, testhistogram)
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@ -257,9 +311,22 @@ eval instant at 50m histogram_quantile(NaN, testhistogram_bucket)
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{start="positive"} NaN
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{start="negative"} NaN
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eval instant at 50m histogram_quantiles(testhistogram, "q", NaN)
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expect warn
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{q="NaN", start="positive"} NaN
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{q="NaN", start="negative"} NaN
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eval instant at 50m histogram_quantiles(testhistogram_bucket, "q", NaN)
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expect warn
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{q="NaN", start="positive"} NaN
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{q="NaN", start="negative"} NaN
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eval instant at 50m histogram_quantile(NaN, non_existent)
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expect warn msg: PromQL warning: quantile value should be between 0 and 1, got NaN
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eval instant at 50m histogram_quantiles(non_existent, "q", NaN)
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expect warn msg: PromQL warning: quantile value should be between 0 and 1, got NaN
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# Quantile value in lowest bucket.
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eval instant at 50m histogram_quantile(0, testhistogram)
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@ -590,6 +657,12 @@ eval instant at 50m histogram_quantile(0.99, nonmonotonic_bucket)
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expect info
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{} 979.75
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eval instant at 50m histogram_quantiles(nonmonotonic_bucket, "q", 0.01, 0.5, 0.99)
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expect info
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{q="0.01"} 0.0045
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{q="0.5"} 8.5
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{q="0.99"} 979.75
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# Buckets with different representations of the same upper bound.
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eval instant at 50m histogram_quantile(0.5, rate(mixed_bucket[10m]))
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{instance="ins1", job="job1"} 0.15
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@ -625,9 +698,15 @@ load_with_nhcb 5m
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eval instant at 50m histogram_quantile(0.99, {__name__=~"request_duration_seconds\\d*_bucket"})
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expect fail
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eval instant at 50m histogram_quantiles({__name__=~"request_duration_seconds\\d*_bucket"}, "q", 0.99)
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expect fail
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eval instant at 50m histogram_quantile(0.99, {__name__=~"request_duration_seconds\\d*"})
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expect fail
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eval instant at 50m histogram_quantiles({__name__=~"request_duration_seconds\\d*"}, "q", 0.99)
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expect fail
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# Histogram with constant buckets.
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load_with_nhcb 1m
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const_histogram_bucket{le="0.0"} 1 1 1 1 1
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@ -689,7 +768,7 @@ eval instant at 10m histogram_sum(increase(histogram_with_reset[15m]))
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clear
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# Test histogram_quantile and histogram_fraction with conflicting classic and native histograms.
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# Test histogram_quantile(s) and histogram_fraction with conflicting classic and native histograms.
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load 1m
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series{host="a"} {{schema:0 sum:5 count:4 buckets:[9 2 1]}}
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series{host="a", le="0.1"} 2
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@ -704,6 +783,11 @@ eval instant at 0 histogram_quantile(0.8, series)
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expect warn msg: PromQL warning: vector contains a mix of classic and native histograms for metric name "series"
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# Should return no results.
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eval instant at 0 histogram_quantiles(series, "q", 0.1, 0.2)
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expect no_info
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expect warn msg: PromQL warning: vector contains a mix of classic and native histograms for metric name "series"
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# Should return no results.
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eval instant at 0 histogram_fraction(-Inf, 1, series)
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expect no_info
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expect warn msg: PromQL warning: vector contains a mix of classic and native histograms for metric name "series"
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@ -55,6 +55,10 @@ eval instant at 1m histogram_quantile(0.5, single_histogram)
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expect no_info
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{} 1.414213562373095
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eval instant at 1m histogram_quantiles(single_histogram, "q", 0.5)
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expect no_info
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{q="0.5"} 1.414213562373095
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clear
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# Repeat the same histogram 10 times.
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@ -1463,6 +1467,11 @@ eval instant at 1m histogram_quantile(0.81, histogram_nan)
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{case="100% NaNs"} NaN
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{case="20% NaNs"} NaN
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eval instant at 1m histogram_quantiles(histogram_nan, "q", 0.81)
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expect info msg: PromQL info: input to histogram_quantile has NaN observations, result is NaN for metric name "histogram_nan"
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{case="100% NaNs", q="0.81"} NaN
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{case="20% NaNs", q="0.81"} NaN
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eval instant at 1m histogram_quantile(0.8, histogram_nan{case="100% NaNs"})
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expect info msg: PromQL info: input to histogram_quantile has NaN observations, result is NaN for metric name "histogram_nan"
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{case="100% NaNs"} NaN
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@ -1608,6 +1617,9 @@ eval instant at 1m histogram_quantile(0.5, myHistogram2)
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eval instant at 1m histogram_quantile(0.5, mixedHistogram)
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expect warn msg: PromQL warning: vector contains a mix of classic and native histograms for metric name "mixedHistogram"
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eval instant at 1m histogram_quantiles(mixedHistogram, "q", 0.5)
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expect warn msg: PromQL warning: vector contains a mix of classic and native histograms for metric name "mixedHistogram"
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clear
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# A counter reset only in a bucket. Sub-queries still need to detect
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@ -1677,6 +1689,9 @@ eval instant at 1m histogram_count(histogram unless histogram_quantile(0.5, hist
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eval instant at 1m histogram_quantile(0.5, histogram unless histogram_count(histogram) == 0)
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{} 3.1748021039363987
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eval instant at 1m histogram_quantiles(histogram unless histogram_count(histogram) == 0, "q", 0.5)
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{q="0.5"} 3.1748021039363987
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clear
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# Regression test for:
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