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Export quantile functions (#15190)
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Export quantile functions For use in Mimir's query engine, it would be helpful if these functions were exported. Co-authored-by: Björn Rabenstein <github@rabenste.in> Signed-off-by: Joshua Hesketh <josh@hesketh.net.au> --------- Signed-off-by: Joshua Hesketh <josh@nitrotech.org> Signed-off-by: Joshua Hesketh <josh@hesketh.net.au> Co-authored-by: Björn Rabenstein <github@rabenste.in>
This commit is contained in:
Joshua Hesketh
GitHub
parent
9ad93ba8df
commit
8e3301eb44
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@ -1300,7 +1300,7 @@ func funcHistogramFraction(vals []parser.Value, args parser.Expressions, enh *Ev
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}
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enh.Out = append(enh.Out, Sample{
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Metric: sample.Metric,
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F: histogramFraction(lower, upper, sample.H),
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F: HistogramFraction(lower, upper, sample.H),
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DropName: true,
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})
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}
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@ -1352,7 +1352,7 @@ func funcHistogramQuantile(vals []parser.Value, args parser.Expressions, enh *Ev
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mb = &metricWithBuckets{sample.Metric, nil}
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enh.signatureToMetricWithBuckets[string(enh.lblBuf)] = mb
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}
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mb.buckets = append(mb.buckets, bucket{upperBound, sample.F})
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mb.buckets = append(mb.buckets, Bucket{upperBound, sample.F})
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}
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// Now deal with the histograms.
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@ -1374,14 +1374,14 @@ func funcHistogramQuantile(vals []parser.Value, args parser.Expressions, enh *Ev
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}
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enh.Out = append(enh.Out, Sample{
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Metric: sample.Metric,
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F: histogramQuantile(q, sample.H),
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F: HistogramQuantile(q, sample.H),
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DropName: true,
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})
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}
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for _, mb := range enh.signatureToMetricWithBuckets {
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if len(mb.buckets) > 0 {
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res, forcedMonotonicity, _ := bucketQuantile(q, mb.buckets)
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res, forcedMonotonicity, _ := BucketQuantile(q, mb.buckets)
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enh.Out = append(enh.Out, Sample{
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Metric: mb.metric,
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F: res,
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@ -51,20 +51,22 @@ var excludedLabels = []string{
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labels.BucketLabel,
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}
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type bucket struct {
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upperBound float64
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count float64
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// Bucket represents a bucket of a classic histogram. It is used internally by the promql
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// package, but it is nevertheless exported for potential use in other PromQL engines.
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type Bucket struct {
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UpperBound float64
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Count float64
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}
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// buckets implements sort.Interface.
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type buckets []bucket
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// Buckets implements sort.Interface.
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type Buckets []Bucket
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type metricWithBuckets struct {
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metric labels.Labels
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buckets buckets
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buckets Buckets
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}
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// bucketQuantile calculates the quantile 'q' based on the given buckets. The
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// BucketQuantile calculates the quantile 'q' based on the given buckets. The
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// buckets will be sorted by upperBound by this function (i.e. no sorting
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// needed before calling this function). The quantile value is interpolated
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// assuming a linear distribution within a bucket. However, if the quantile
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@ -95,7 +97,14 @@ type metricWithBuckets struct {
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// and another bool to indicate if small differences between buckets (that
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// are likely artifacts of floating point precision issues) have been
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// ignored.
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func bucketQuantile(q float64, buckets buckets) (float64, bool, bool) {
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//
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// Generically speaking, BucketQuantile is for calculating the
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// histogram_quantile() of classic histograms. See also: HistogramQuantile
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// for native histograms.
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//
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// BucketQuantile is exported as a useful quantile function over a set of
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// given buckets. It may be used by other PromQL engine implementations.
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func BucketQuantile(q float64, buckets Buckets) (float64, bool, bool) {
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if math.IsNaN(q) {
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return math.NaN(), false, false
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}
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@ -105,17 +114,17 @@ func bucketQuantile(q float64, buckets buckets) (float64, bool, bool) {
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if q > 1 {
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return math.Inf(+1), false, false
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}
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slices.SortFunc(buckets, func(a, b bucket) int {
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slices.SortFunc(buckets, func(a, b Bucket) int {
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// We don't expect the bucket boundary to be a NaN.
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if a.upperBound < b.upperBound {
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if a.UpperBound < b.UpperBound {
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return -1
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}
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if a.upperBound > b.upperBound {
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if a.UpperBound > b.UpperBound {
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return +1
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}
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return 0
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})
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if !math.IsInf(buckets[len(buckets)-1].upperBound, +1) {
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if !math.IsInf(buckets[len(buckets)-1].UpperBound, +1) {
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return math.NaN(), false, false
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}
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@ -125,33 +134,33 @@ func bucketQuantile(q float64, buckets buckets) (float64, bool, bool) {
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if len(buckets) < 2 {
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return math.NaN(), false, false
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}
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observations := buckets[len(buckets)-1].count
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observations := buckets[len(buckets)-1].Count
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if observations == 0 {
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return math.NaN(), false, false
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}
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rank := q * observations
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b := sort.Search(len(buckets)-1, func(i int) bool { return buckets[i].count >= rank })
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b := sort.Search(len(buckets)-1, func(i int) bool { return buckets[i].Count >= rank })
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if b == len(buckets)-1 {
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return buckets[len(buckets)-2].upperBound, forcedMonotonic, fixedPrecision
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return buckets[len(buckets)-2].UpperBound, forcedMonotonic, fixedPrecision
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}
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if b == 0 && buckets[0].upperBound <= 0 {
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return buckets[0].upperBound, forcedMonotonic, fixedPrecision
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if b == 0 && buckets[0].UpperBound <= 0 {
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return buckets[0].UpperBound, forcedMonotonic, fixedPrecision
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}
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var (
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bucketStart float64
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bucketEnd = buckets[b].upperBound
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count = buckets[b].count
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bucketEnd = buckets[b].UpperBound
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count = buckets[b].Count
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)
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if b > 0 {
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bucketStart = buckets[b-1].upperBound
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count -= buckets[b-1].count
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rank -= buckets[b-1].count
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bucketStart = buckets[b-1].UpperBound
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count -= buckets[b-1].Count
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rank -= buckets[b-1].Count
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}
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return bucketStart + (bucketEnd-bucketStart)*(rank/count), forcedMonotonic, fixedPrecision
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}
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// histogramQuantile calculates the quantile 'q' based on the given histogram.
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// HistogramQuantile calculates the quantile 'q' based on the given histogram.
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//
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// For custom buckets, the result is interpolated linearly, i.e. it is assumed
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// the observations are uniformly distributed within each bucket. (This is a
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@ -186,7 +195,13 @@ func bucketQuantile(q float64, buckets buckets) (float64, bool, bool) {
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// If q>1, +Inf is returned.
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//
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// If q is NaN, NaN is returned.
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func histogramQuantile(q float64, h *histogram.FloatHistogram) float64 {
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//
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// HistogramQuantile is for calculating the histogram_quantile() of native
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// histograms. See also: BucketQuantile for classic histograms.
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//
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// HistogramQuantile is exported as it may be used by other PromQL engine
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// implementations.
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func HistogramQuantile(q float64, h *histogram.FloatHistogram) float64 {
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if q < 0 {
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return math.Inf(-1)
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}
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@ -297,11 +312,11 @@ func histogramQuantile(q float64, h *histogram.FloatHistogram) float64 {
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return -math.Exp2(logUpper + (logLower-logUpper)*(1-fraction))
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}
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// histogramFraction calculates the fraction of observations between the
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// HistogramFraction calculates the fraction of observations between the
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// provided lower and upper bounds, based on the provided histogram.
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//
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// histogramFraction is in a certain way the inverse of histogramQuantile. If
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// histogramQuantile(0.9, h) returns 123.4, then histogramFraction(-Inf, 123.4, h)
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// HistogramFraction is in a certain way the inverse of histogramQuantile. If
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// HistogramQuantile(0.9, h) returns 123.4, then HistogramFraction(-Inf, 123.4, h)
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// returns 0.9.
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//
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// The same notes with regard to interpolation and assumptions about the zero
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@ -328,7 +343,10 @@ func histogramQuantile(q float64, h *histogram.FloatHistogram) float64 {
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// If lower or upper is NaN, NaN is returned.
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//
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// If lower >= upper and the histogram has at least 1 observation, zero is returned.
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func histogramFraction(lower, upper float64, h *histogram.FloatHistogram) float64 {
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//
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// HistogramFraction is exported as it may be used by other PromQL engine
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// implementations.
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func HistogramFraction(lower, upper float64, h *histogram.FloatHistogram) float64 {
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if h.Count == 0 || math.IsNaN(lower) || math.IsNaN(upper) {
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return math.NaN()
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}
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@ -434,12 +452,12 @@ func histogramFraction(lower, upper float64, h *histogram.FloatHistogram) float6
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// coalesceBuckets merges buckets with the same upper bound.
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//
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// The input buckets must be sorted.
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func coalesceBuckets(buckets buckets) buckets {
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func coalesceBuckets(buckets Buckets) Buckets {
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last := buckets[0]
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i := 0
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for _, b := range buckets[1:] {
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if b.upperBound == last.upperBound {
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last.count += b.count
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if b.UpperBound == last.UpperBound {
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last.Count += b.Count
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} else {
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buckets[i] = last
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last = b
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@ -476,11 +494,11 @@ func coalesceBuckets(buckets buckets) buckets {
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//
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// We return a bool to indicate if this monotonicity was forced or not, and
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// another bool to indicate if small deltas were ignored or not.
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func ensureMonotonicAndIgnoreSmallDeltas(buckets buckets, tolerance float64) (bool, bool) {
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func ensureMonotonicAndIgnoreSmallDeltas(buckets Buckets, tolerance float64) (bool, bool) {
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var forcedMonotonic, fixedPrecision bool
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prev := buckets[0].count
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prev := buckets[0].Count
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for i := 1; i < len(buckets); i++ {
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curr := buckets[i].count // Assumed always positive.
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curr := buckets[i].Count // Assumed always positive.
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if curr == prev {
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// No correction needed if the counts are identical between buckets.
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continue
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@ -489,14 +507,14 @@ func ensureMonotonicAndIgnoreSmallDeltas(buckets buckets, tolerance float64) (bo
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// Silently correct numerically insignificant differences from floating
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// point precision errors, regardless of direction.
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// Do not update the 'prev' value as we are ignoring the difference.
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buckets[i].count = prev
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buckets[i].Count = prev
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fixedPrecision = true
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continue
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}
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if curr < prev {
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// Force monotonicity by removing any decreases regardless of magnitude.
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// Do not update the 'prev' value as we are ignoring the decrease.
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buckets[i].count = prev
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buckets[i].Count = prev
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forcedMonotonic = true
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continue
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}
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@ -24,29 +24,29 @@ func TestBucketQuantile_ForcedMonotonicity(t *testing.T) {
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eps := 1e-12
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for name, tc := range map[string]struct {
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getInput func() buckets // The buckets can be modified in-place so return a new one each time.
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getInput func() Buckets // The buckets can be modified in-place so return a new one each time.
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expectedForced bool
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expectedFixed bool
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expectedValues map[float64]float64
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}{
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"simple - monotonic": {
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getInput: func() buckets {
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return buckets{
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getInput: func() Buckets {
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return Buckets{
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{
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upperBound: 10,
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count: 10,
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UpperBound: 10,
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Count: 10,
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}, {
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upperBound: 15,
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count: 15,
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UpperBound: 15,
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Count: 15,
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}, {
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upperBound: 20,
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count: 15,
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UpperBound: 20,
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Count: 15,
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}, {
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upperBound: 30,
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count: 15,
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UpperBound: 30,
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Count: 15,
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}, {
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upperBound: math.Inf(1),
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count: 15,
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UpperBound: math.Inf(1),
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Count: 15,
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},
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}
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},
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@ -60,23 +60,23 @@ func TestBucketQuantile_ForcedMonotonicity(t *testing.T) {
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},
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},
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"simple - non-monotonic middle": {
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getInput: func() buckets {
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return buckets{
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getInput: func() Buckets {
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return Buckets{
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{
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upperBound: 10,
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count: 10,
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UpperBound: 10,
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Count: 10,
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}, {
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upperBound: 15,
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count: 15,
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UpperBound: 15,
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Count: 15,
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}, {
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upperBound: 20,
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count: 15.00000000001, // Simulate the case there's a small imprecision in float64.
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UpperBound: 20,
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Count: 15.00000000001, // Simulate the case there's a small imprecision in float64.
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}, {
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upperBound: 30,
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count: 15,
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UpperBound: 30,
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Count: 15,
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}, {
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upperBound: math.Inf(1),
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count: 15,
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UpperBound: math.Inf(1),
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Count: 15,
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},
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}
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},
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@ -90,41 +90,41 @@ func TestBucketQuantile_ForcedMonotonicity(t *testing.T) {
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},
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},
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"real example - monotonic": {
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getInput: func() buckets {
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return buckets{
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getInput: func() Buckets {
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return Buckets{
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{
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upperBound: 1,
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count: 6454661.3014166197,
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UpperBound: 1,
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Count: 6454661.3014166197,
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}, {
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upperBound: 5,
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count: 8339611.2001912938,
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UpperBound: 5,
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Count: 8339611.2001912938,
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}, {
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upperBound: 10,
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count: 14118319.2444762159,
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UpperBound: 10,
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Count: 14118319.2444762159,
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}, {
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upperBound: 25,
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count: 14130031.5272856522,
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UpperBound: 25,
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Count: 14130031.5272856522,
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}, {
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upperBound: 50,
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count: 46001270.3030008152,
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UpperBound: 50,
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Count: 46001270.3030008152,
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}, {
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upperBound: 64,
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count: 46008473.8585563600,
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UpperBound: 64,
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Count: 46008473.8585563600,
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}, {
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upperBound: 80,
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count: 46008473.8585563600,
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UpperBound: 80,
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Count: 46008473.8585563600,
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}, {
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upperBound: 100,
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count: 46008473.8585563600,
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UpperBound: 100,
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Count: 46008473.8585563600,
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}, {
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upperBound: 250,
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count: 46008473.8585563600,
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UpperBound: 250,
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Count: 46008473.8585563600,
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}, {
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upperBound: 1000,
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count: 46008473.8585563600,
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UpperBound: 1000,
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Count: 46008473.8585563600,
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}, {
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upperBound: math.Inf(1),
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||||
count: 46008473.8585563600,
|
||||
UpperBound: math.Inf(1),
|
||||
Count: 46008473.8585563600,
|
||||
},
|
||||
}
|
||||
},
|
||||
|
|
@ -138,41 +138,41 @@ func TestBucketQuantile_ForcedMonotonicity(t *testing.T) {
|
|||
},
|
||||
},
|
||||
"real example - non-monotonic": {
|
||||
getInput: func() buckets {
|
||||
return buckets{
|
||||
getInput: func() Buckets {
|
||||
return Buckets{
|
||||
{
|
||||
upperBound: 1,
|
||||
count: 6454661.3014166225,
|
||||
UpperBound: 1,
|
||||
Count: 6454661.3014166225,
|
||||
}, {
|
||||
upperBound: 5,
|
||||
count: 8339611.2001912957,
|
||||
UpperBound: 5,
|
||||
Count: 8339611.2001912957,
|
||||
}, {
|
||||
upperBound: 10,
|
||||
count: 14118319.2444762159,
|
||||
UpperBound: 10,
|
||||
Count: 14118319.2444762159,
|
||||
}, {
|
||||
upperBound: 25,
|
||||
count: 14130031.5272856504,
|
||||
UpperBound: 25,
|
||||
Count: 14130031.5272856504,
|
||||
}, {
|
||||
upperBound: 50,
|
||||
count: 46001270.3030008227,
|
||||
UpperBound: 50,
|
||||
Count: 46001270.3030008227,
|
||||
}, {
|
||||
upperBound: 64,
|
||||
count: 46008473.8585563824,
|
||||
UpperBound: 64,
|
||||
Count: 46008473.8585563824,
|
||||
}, {
|
||||
upperBound: 80,
|
||||
count: 46008473.8585563898,
|
||||
UpperBound: 80,
|
||||
Count: 46008473.8585563898,
|
||||
}, {
|
||||
upperBound: 100,
|
||||
count: 46008473.8585563824,
|
||||
UpperBound: 100,
|
||||
Count: 46008473.8585563824,
|
||||
}, {
|
||||
upperBound: 250,
|
||||
count: 46008473.8585563824,
|
||||
UpperBound: 250,
|
||||
Count: 46008473.8585563824,
|
||||
}, {
|
||||
upperBound: 1000,
|
||||
count: 46008473.8585563898,
|
||||
UpperBound: 1000,
|
||||
Count: 46008473.8585563898,
|
||||
}, {
|
||||
upperBound: math.Inf(1),
|
||||
count: 46008473.8585563824,
|
||||
UpperBound: math.Inf(1),
|
||||
Count: 46008473.8585563824,
|
||||
},
|
||||
}
|
||||
},
|
||||
|
|
@ -186,53 +186,53 @@ func TestBucketQuantile_ForcedMonotonicity(t *testing.T) {
|
|||
},
|
||||
},
|
||||
"real example 2 - monotonic": {
|
||||
getInput: func() buckets {
|
||||
return buckets{
|
||||
getInput: func() Buckets {
|
||||
return Buckets{
|
||||
{
|
||||
upperBound: 0.005,
|
||||
count: 9.6,
|
||||
UpperBound: 0.005,
|
||||
Count: 9.6,
|
||||
}, {
|
||||
upperBound: 0.01,
|
||||
count: 9.688888889,
|
||||
UpperBound: 0.01,
|
||||
Count: 9.688888889,
|
||||
}, {
|
||||
upperBound: 0.025,
|
||||
count: 9.755555556,
|
||||
UpperBound: 0.025,
|
||||
Count: 9.755555556,
|
||||
}, {
|
||||
upperBound: 0.05,
|
||||
count: 9.844444444,
|
||||
UpperBound: 0.05,
|
||||
Count: 9.844444444,
|
||||
}, {
|
||||
upperBound: 0.1,
|
||||
count: 9.888888889,
|
||||
UpperBound: 0.1,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 0.25,
|
||||
count: 9.888888889,
|
||||
UpperBound: 0.25,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 0.5,
|
||||
count: 9.888888889,
|
||||
UpperBound: 0.5,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 1,
|
||||
count: 9.888888889,
|
||||
UpperBound: 1,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 2.5,
|
||||
count: 9.888888889,
|
||||
UpperBound: 2.5,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 5,
|
||||
count: 9.888888889,
|
||||
UpperBound: 5,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 10,
|
||||
count: 9.888888889,
|
||||
UpperBound: 10,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 25,
|
||||
count: 9.888888889,
|
||||
UpperBound: 25,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 50,
|
||||
count: 9.888888889,
|
||||
UpperBound: 50,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 100,
|
||||
count: 9.888888889,
|
||||
UpperBound: 100,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: math.Inf(1),
|
||||
count: 9.888888889,
|
||||
UpperBound: math.Inf(1),
|
||||
Count: 9.888888889,
|
||||
},
|
||||
}
|
||||
},
|
||||
|
|
@ -246,53 +246,53 @@ func TestBucketQuantile_ForcedMonotonicity(t *testing.T) {
|
|||
},
|
||||
},
|
||||
"real example 2 - non-monotonic": {
|
||||
getInput: func() buckets {
|
||||
return buckets{
|
||||
getInput: func() Buckets {
|
||||
return Buckets{
|
||||
{
|
||||
upperBound: 0.005,
|
||||
count: 9.6,
|
||||
UpperBound: 0.005,
|
||||
Count: 9.6,
|
||||
}, {
|
||||
upperBound: 0.01,
|
||||
count: 9.688888889,
|
||||
UpperBound: 0.01,
|
||||
Count: 9.688888889,
|
||||
}, {
|
||||
upperBound: 0.025,
|
||||
count: 9.755555556,
|
||||
UpperBound: 0.025,
|
||||
Count: 9.755555556,
|
||||
}, {
|
||||
upperBound: 0.05,
|
||||
count: 9.844444444,
|
||||
UpperBound: 0.05,
|
||||
Count: 9.844444444,
|
||||
}, {
|
||||
upperBound: 0.1,
|
||||
count: 9.888888889,
|
||||
UpperBound: 0.1,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 0.25,
|
||||
count: 9.888888889,
|
||||
UpperBound: 0.25,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 0.5,
|
||||
count: 9.888888889,
|
||||
UpperBound: 0.5,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 1,
|
||||
count: 9.888888889,
|
||||
UpperBound: 1,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 2.5,
|
||||
count: 9.888888889,
|
||||
UpperBound: 2.5,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 5,
|
||||
count: 9.888888889,
|
||||
UpperBound: 5,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 10,
|
||||
count: 9.888888889001, // Simulate the case there's a small imprecision in float64.
|
||||
UpperBound: 10,
|
||||
Count: 9.888888889001, // Simulate the case there's a small imprecision in float64.
|
||||
}, {
|
||||
upperBound: 25,
|
||||
count: 9.888888889,
|
||||
UpperBound: 25,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: 50,
|
||||
count: 9.888888888999, // Simulate the case there's a small imprecision in float64.
|
||||
UpperBound: 50,
|
||||
Count: 9.888888888999, // Simulate the case there's a small imprecision in float64.
|
||||
}, {
|
||||
upperBound: 100,
|
||||
count: 9.888888889,
|
||||
UpperBound: 100,
|
||||
Count: 9.888888889,
|
||||
}, {
|
||||
upperBound: math.Inf(1),
|
||||
count: 9.888888889,
|
||||
UpperBound: math.Inf(1),
|
||||
Count: 9.888888889,
|
||||
},
|
||||
}
|
||||
},
|
||||
|
|
@ -308,7 +308,7 @@ func TestBucketQuantile_ForcedMonotonicity(t *testing.T) {
|
|||
} {
|
||||
t.Run(name, func(t *testing.T) {
|
||||
for q, v := range tc.expectedValues {
|
||||
res, forced, fixed := bucketQuantile(q, tc.getInput())
|
||||
res, forced, fixed := BucketQuantile(q, tc.getInput())
|
||||
require.Equal(t, tc.expectedForced, forced)
|
||||
require.Equal(t, tc.expectedFixed, fixed)
|
||||
require.InEpsilon(t, v, res, eps)
|
||||
|
|
|
|||
Loading…
Reference in a new issue