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[FIX] PromQL: Ignore histograms in scalar, sort and sort_desc functions (#15964)

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PromQL: Ignore histograms in scalar, sort and sort_desc functions

---------

Signed-off-by: Neeraj Gartia <neerajgartia211002@gmail.com>
This commit is contained in:
Neeraj Gartia 2025-02-06 20:32:03 +05:30 committed by GitHub
parent cb096a8ea8
commit 20371118b6
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GPG key ID: B5690EEEBB952194
2 changed files with 52 additions and 23 deletions
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55
promql/functions.go
View file

@ -486,11 +486,22 @@ func funcDoubleExponentialSmoothing(vals []parser.Value, args parser.Expressions
return append(enh.Out, Sample{F: s1}), nil
}
// filterFloats filters out histogram samples from the vector in-place.
func filterFloats(v Vector) Vector {
floats := v[:0]
for _, s := range v {
if s.H == nil {
floats = append(floats, s)
}
}
return floats
}
// === sort(node parser.ValueTypeVector) (Vector, Annotations) ===
func funcSort(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
// NaN should sort to the bottom, so take descending sort with NaN first and
// reverse it.
byValueSorter := vectorByReverseValueHeap(vals[0].(Vector))
byValueSorter := vectorByReverseValueHeap(filterFloats(vals[0].(Vector)))
sort.Sort(sort.Reverse(byValueSorter))
return Vector(byValueSorter), nil
}
@ -499,7 +510,7 @@ func funcSort(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper)
func funcSortDesc(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
// NaN should sort to the bottom, so take ascending sort with NaN first and
// reverse it.
byValueSorter := vectorByValueHeap(vals[0].(Vector))
byValueSorter := vectorByValueHeap(filterFloats(vals[0].(Vector)))
sort.Sort(sort.Reverse(byValueSorter))
return Vector(byValueSorter), nil
}
@ -631,11 +642,27 @@ func funcRound(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper
// === Scalar(node parser.ValueTypeVector) Scalar ===
func funcScalar(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
v := vals[0].(Vector)
if len(v) != 1 {
var (
v = vals[0].(Vector)
value float64
found bool
)
for _, s := range v {
if s.H == nil {
if found {
// More than one float found, return NaN.
return append(enh.Out, Sample{F: math.NaN()}), nil
}
found = true
value = s.F
}
}
// Return the single float if found, otherwise return NaN.
if !found {
return append(enh.Out, Sample{F: math.NaN()}), nil
}
return append(enh.Out, Sample{F: v[0].F}), nil
return append(enh.Out, Sample{F: value}), nil
}
func aggrOverTime(vals []parser.Value, enh *EvalNodeHelper, aggrFn func(Series) float64) Vector {
@ -1896,16 +1923,7 @@ func (s vectorByValueHeap) Len() int {
}
func (s vectorByValueHeap) Less(i, j int) bool {
// We compare histograms based on their sum of observations.
// TODO(beorn7): Is that what we want?
vi, vj := s[i].F, s[j].F
if s[i].H != nil {
vi = s[i].H.Sum
}
if s[j].H != nil {
vj = s[j].H.Sum
}
if math.IsNaN(vi) {
return true
}
@ -1935,16 +1953,7 @@ func (s vectorByReverseValueHeap) Len() int {
}
func (s vectorByReverseValueHeap) Less(i, j int) bool {
// We compare histograms based on their sum of observations.
// TODO(beorn7): Is that what we want?
vi, vj := s[i].F, s[j].F
if s[i].H != nil {
vi = s[i].H.Sum
}
if s[j].H != nil {
vj = s[j].H.Sum
}
if math.IsNaN(vi) {
return true
}

20
promql/promqltest/testdata/functions.test vendored
View file

@ -642,6 +642,7 @@ load 5m
http_requests{job="app-server", instance="1", group="production"} 0+60x10
http_requests{job="app-server", instance="0", group="canary"} 0+70x10
http_requests{job="app-server", instance="1", group="canary"} 0+80x10
http_requests{job="app-server", instance="2", group="canary"} {{schema:0 sum:1 count:1}}x15
eval_ordered instant at 50m sort(http_requests)
http_requests{group="production", instance="0", job="api-server"} 100
@ -1652,3 +1653,22 @@ load 1m
eval range from 0 to 5m step 1m round(mixed_metric)
{} _ 1 2 3
# Test scalar() with histograms.
load 1m
metric{type="float", l="x"} 1
metric{type="float", l="y"} 2
metric{type="histogram", l="x"} {{schema:0 sum:1 count:1}}
metric{type="histogram", l="x"} {{schema:0 sum:1 count:1}}
# Two floats in the vector.
eval instant at 0m scalar(metric)
NaN
# No floats in the vector.
eval instant at 0m scalar({type="histogram"})
NaN
# One float in the vector.
eval instant at 0m scalar({l="x"})
1