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Merge pull request #1144 from prometheus/beorn7/histogram2 

sparse buckets: Fix handling of +Inf/-Inf/NaN observations
This commit is contained in:
Björn Rabenstein 2022-10-11 12:57:40 +02:00 committed by GitHub
parent 95cf173f19 6942f9e454
commit 25bc1886c0
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 162 additions and 18 deletions
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71
prometheus/histogram.go
View File

@ -577,21 +577,27 @@ func (hc *histogramCounts) observe(v float64, bucket int, doSparse bool) {
atomic.AddUint64(&hc.buckets[bucket], 1)
}
atomicAddFloat(&hc.sumBits, v)
if doSparse {
if doSparse && !math.IsNaN(v) {
var (
sparseKey int
sparseSchema = atomic.LoadInt32(&hc.sparseSchema)
sparseZeroThreshold = math.Float64frombits(atomic.LoadUint64(&hc.sparseZeroThresholdBits))
frac, exp = math.Frexp(math.Abs(v))
bucketCreated bool
bucketCreated, isInf bool
)
switch {
case math.IsInf(v, 0):
sparseKey = math.MaxInt32 // Largest possible sparseKey.
case sparseSchema > 0:
if math.IsInf(v, 0) {
// Pretend v is MaxFloat64 but later increment sparseKey by one.
if math.IsInf(v, +1) {
v = math.MaxFloat64
} else {
v = -math.MaxFloat64
}
isInf = true
}
frac, exp := math.Frexp(math.Abs(v))
if sparseSchema > 0 {
bounds := sparseBounds[sparseSchema]
sparseKey = sort.SearchFloat64s(bounds, frac) + (exp-1)*len(bounds)
default:
} else {
sparseKey = exp
if frac == 0.5 {
sparseKey--
@ -599,6 +605,9 @@ func (hc *histogramCounts) observe(v float64, bucket int, doSparse bool) {
div := 1 << -sparseSchema
sparseKey = (sparseKey + div - 1) / div
}
if isInf {
sparseKey++
}
switch {
case v > sparseZeroThreshold:
bucketCreated = addToSparseBucket(&hc.sparseBucketsPositive, sparseKey, 1)
@ -1062,6 +1071,7 @@ func (v *HistogramVec) GetMetricWith(labels Labels) (Observer, error) {
// WithLabelValues works as GetMetricWithLabelValues, but panics where
// GetMetricWithLabelValues would have returned an error. Not returning an
// error allows shortcuts like
//
// myVec.WithLabelValues("404", "GET").Observe(42.21)
func (v *HistogramVec) WithLabelValues(lvs ...string) Observer {
h, err := v.GetMetricWithLabelValues(lvs...)
@ -1073,6 +1083,7 @@ func (v *HistogramVec) WithLabelValues(lvs ...string) Observer {
// With works as GetMetricWith but panics where GetMetricWithLabels would have
// returned an error. Not returning an error allows shortcuts like
//
// myVec.With(prometheus.Labels{"code": "404", "method": "GET"}).Observe(42.21)
func (v *HistogramVec) With(labels Labels) Observer {
h, err := v.GetMetricWith(labels)
@ -1346,13 +1357,55 @@ func findSmallestKey(m *sync.Map) int {
}
func getLe(key int, schema int32) float64 {
// Here a bit of context about the behavior for the last bucket counting
// regular numbers (called simply "last bucket" below) and the bucket
// counting observations of ±Inf (called "inf bucket" below, with a key
// one higher than that of the "last bucket"):
//
// If we apply the usual formula to the last bucket, its upper bound
// would be calculated as +Inf. The reason is that the max possible
// regular float64 number (math.MaxFloat64) doesn't coincide with one of
// the calculated bucket boundaries. So the calculated boundary has to
// be larger than math.MaxFloat64, and the only float64 larger than
// math.MaxFloat64 is +Inf. However, we want to count actual
// observations of ±Inf in the inf bucket. Therefore, we have to treat
// the upper bound of the last bucket specially and set it to
// math.MaxFloat64. (The upper bound of the inf bucket, with its key
// being one higher than that of the last bucket, naturally comes out as
// +Inf by the usual formula. So that's fine.)
//
// math.MaxFloat64 has a frac of 0.9999999999999999 and an exp of
// 1024. If there were a float64 number following math.MaxFloat64, it
// would have a frac of 1.0 and an exp of 1024, or equivalently a frac
// of 0.5 and an exp of 1025. However, since frac must be smaller than
// 1, and exp must be smaller than 1025, either representation overflows
// a float64. (Which, in turn, is the reason that math.MaxFloat64 is the
// largest possible float64. Q.E.D.) However, the formula for
// calculating the upper bound from the idx and schema of the last
// bucket results in precisely that. It is either frac=1.0 & exp=1024
// (for schema < 0) or frac=0.5 & exp=1025 (for schema >=0). (This is,
// by the way, a power of two where the exponent itself is a power of
// two, 2¹⁰ in fact, which coinicides with a bucket boundary in all
// schemas.) So these are the special cases we have to catch below.
if schema < 0 {
return math.Ldexp(1, key<<(-schema))
exp := key << -schema
if exp == 1024 {
// This is the last bucket before the overflow bucket
// (for ±Inf observations). Return math.MaxFloat64 as
// explained above.
return math.MaxFloat64
}
return math.Ldexp(1, exp)
}
fracIdx := key & ((1 << schema) - 1)
frac := sparseBounds[schema][fracIdx]
exp := (key >> schema) + 1
if frac == 0.5 && exp == 1025 {
// This is the last bucket before the overflow bucket (for ±Inf
// observations). Return math.MaxFloat64 as explained above.
return math.MaxFloat64
}
return math.Ldexp(frac, exp)
}

95
prometheus/histogram_test.go
View File

@ -548,13 +548,13 @@ func TestSparseHistogram(t *testing.T) {
name: "+Inf observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(+1)},
factor: 1.2,
want: `sample_count:7 sample_sum:inf schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 positive_span:<offset:0 length:5 > positive_span:<offset:2147483642 length:1 > positive_delta:1 positive_delta:-1 positive_delta:2 positive_delta:-2 positive_delta:2 positive_delta:-1 `,
want: `sample_count:7 sample_sum:inf schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 positive_span:<offset:0 length:5 > positive_span:<offset:4092 length:1 > positive_delta:1 positive_delta:-1 positive_delta:2 positive_delta:-2 positive_delta:2 positive_delta:-1 `,
},
{
name: "-Inf observation",
observations: []float64{0, 1, 1.2, 1.4, 1.8, 2, math.Inf(-1)},
factor: 1.2,
want: `sample_count:7 sample_sum:-inf schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 negative_span:<offset:2147483647 length:1 > negative_delta:1 positive_span:<offset:0 length:5 > positive_delta:1 positive_delta:-1 positive_delta:2 positive_delta:-2 positive_delta:2 `,
want: `sample_count:7 sample_sum:-inf schema:2 zero_threshold:2.938735877055719e-39 zero_count:1 negative_span:<offset:4097 length:1 > negative_delta:1 positive_span:<offset:0 length:5 > positive_delta:1 positive_delta:-1 positive_delta:2 positive_delta:-2 positive_delta:2 `,
},
{
name: "limited buckets but nothing triggered",
@ -782,3 +782,94 @@ func TestSparseHistogramConcurrency(t *testing.T) {
t.Error(err)
}
}
func TestGetLe(t *testing.T) {
scenarios := []struct {
key int
schema int32
want float64
}{
{
key: -1,
schema: -1,
want: 0.25,
},
{
key: 0,
schema: -1,
want: 1,
},
{
key: 1,
schema: -1,
want: 4,
},
{
key: 512,
schema: -1,
want: math.MaxFloat64,
},
{
key: 513,
schema: -1,
want: math.Inf(+1),
},
{
key: -1,
schema: 0,
want: 0.5,
},
{
key: 0,
schema: 0,
want: 1,
},
{
key: 1,
schema: 0,
want: 2,
},
{
key: 1024,
schema: 0,
want: math.MaxFloat64,
},
{
key: 1025,
schema: 0,
want: math.Inf(+1),
},
{
key: -1,
schema: 2,
want: 0.8408964152537144,
},
{
key: 0,
schema: 2,
want: 1,
},
{
key: 1,
schema: 2,
want: 1.189207115002721,
},
{
key: 4096,
schema: 2,
want: math.MaxFloat64,
},
{
key: 4097,
schema: 2,
want: math.Inf(+1),
},
}
for i, s := range scenarios {
got := getLe(s.key, s.schema)
if s.want != got {
t.Errorf("%d. key %d, schema %d, want upper bound of %g, got %g", i, s.key, s.schema, s.want, got)
}
}
}