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Diffstat (limited to 'vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/histogram.go')
-rw-r--r--vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/histogram.go98
1 files changed, 41 insertions, 57 deletions
diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/histogram.go b/vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/histogram.go
index a9a4706bf..ade0941f5 100644
--- a/vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/histogram.go
+++ b/vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/histogram.go
@@ -1,21 +1,11 @@
// Copyright The OpenTelemetry Authors
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-// http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
+// SPDX-License-Identifier: Apache-2.0
package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate"
import (
"context"
+ "slices"
"sort"
"sync"
"time"
@@ -26,7 +16,8 @@ import (
)
type buckets[N int64 | float64] struct {
- res exemplar.Reservoir[N]
+ attrs attribute.Set
+ res exemplar.FilteredReservoir[N]
counts []uint64
count uint64
@@ -35,8 +26,8 @@ type buckets[N int64 | float64] struct {
}
// newBuckets returns buckets with n bins.
-func newBuckets[N int64 | float64](n int) *buckets[N] {
- return &buckets[N]{counts: make([]uint64, n)}
+func newBuckets[N int64 | float64](attrs attribute.Set, n int) *buckets[N] {
+ return &buckets[N]{attrs: attrs, counts: make([]uint64, n)}
}
func (b *buckets[N]) sum(value N) { b.total += value }
@@ -57,26 +48,25 @@ type histValues[N int64 | float64] struct {
noSum bool
bounds []float64
- newRes func() exemplar.Reservoir[N]
+ newRes func() exemplar.FilteredReservoir[N]
limit limiter[*buckets[N]]
- values map[attribute.Set]*buckets[N]
+ values map[attribute.Distinct]*buckets[N]
valuesMu sync.Mutex
}
-func newHistValues[N int64 | float64](bounds []float64, noSum bool, limit int, r func() exemplar.Reservoir[N]) *histValues[N] {
+func newHistValues[N int64 | float64](bounds []float64, noSum bool, limit int, r func() exemplar.FilteredReservoir[N]) *histValues[N] {
// The responsibility of keeping all buckets correctly associated with the
// passed boundaries is ultimately this type's responsibility. Make a copy
// here so we can always guarantee this. Or, in the case of failure, have
// complete control over the fix.
- b := make([]float64, len(bounds))
- copy(b, bounds)
- sort.Float64s(b)
+ b := slices.Clone(bounds)
+ slices.Sort(b)
return &histValues[N]{
noSum: noSum,
bounds: b,
newRes: r,
limit: newLimiter[*buckets[N]](limit),
- values: make(map[attribute.Set]*buckets[N]),
+ values: make(map[attribute.Distinct]*buckets[N]),
}
}
@@ -90,13 +80,11 @@ func (s *histValues[N]) measure(ctx context.Context, value N, fltrAttr attribute
// (s.bounds[len(s.bounds)-1], +∞).
idx := sort.SearchFloat64s(s.bounds, float64(value))
- t := now()
-
s.valuesMu.Lock()
defer s.valuesMu.Unlock()
attr := s.limit.Attributes(fltrAttr, s.values)
- b, ok := s.values[attr]
+ b, ok := s.values[attr.Equivalent()]
if !ok {
// N+1 buckets. For example:
//
@@ -105,23 +93,23 @@ func (s *histValues[N]) measure(ctx context.Context, value N, fltrAttr attribute
// Then,
//
// buckets = (-∞, 0], (0, 5.0], (5.0, 10.0], (10.0, +∞)
- b = newBuckets[N](len(s.bounds) + 1)
+ b = newBuckets[N](attr, len(s.bounds)+1)
b.res = s.newRes()
// Ensure min and max are recorded values (not zero), for new buckets.
b.min, b.max = value, value
- s.values[attr] = b
+ s.values[attr.Equivalent()] = b
}
b.bin(idx, value)
if !s.noSum {
b.sum(value)
}
- b.res.Offer(ctx, t, value, droppedAttr)
+ b.res.Offer(ctx, value, droppedAttr)
}
// newHistogram returns an Aggregator that summarizes a set of measurements as
// an histogram.
-func newHistogram[N int64 | float64](boundaries []float64, noMinMax, noSum bool, limit int, r func() exemplar.Reservoir[N]) *histogram[N] {
+func newHistogram[N int64 | float64](boundaries []float64, noMinMax, noSum bool, limit int, r func() exemplar.FilteredReservoir[N]) *histogram[N] {
return &histogram[N]{
histValues: newHistValues[N](boundaries, noSum, limit, r),
noMinMax: noMinMax,
@@ -150,36 +138,35 @@ func (s *histogram[N]) delta(dest *metricdata.Aggregation) int {
defer s.valuesMu.Unlock()
// Do not allow modification of our copy of bounds.
- bounds := make([]float64, len(s.bounds))
- copy(bounds, s.bounds)
+ bounds := slices.Clone(s.bounds)
n := len(s.values)
hDPts := reset(h.DataPoints, n, n)
var i int
- for a, b := range s.values {
- hDPts[i].Attributes = a
+ for _, val := range s.values {
+ hDPts[i].Attributes = val.attrs
hDPts[i].StartTime = s.start
hDPts[i].Time = t
- hDPts[i].Count = b.count
+ hDPts[i].Count = val.count
hDPts[i].Bounds = bounds
- hDPts[i].BucketCounts = b.counts
+ hDPts[i].BucketCounts = val.counts
if !s.noSum {
- hDPts[i].Sum = b.total
+ hDPts[i].Sum = val.total
}
if !s.noMinMax {
- hDPts[i].Min = metricdata.NewExtrema(b.min)
- hDPts[i].Max = metricdata.NewExtrema(b.max)
+ hDPts[i].Min = metricdata.NewExtrema(val.min)
+ hDPts[i].Max = metricdata.NewExtrema(val.max)
}
- b.res.Collect(&hDPts[i].Exemplars)
+ collectExemplars(&hDPts[i].Exemplars, val.res.Collect)
- // Unused attribute sets do not report.
- delete(s.values, a)
i++
}
+ // Unused attribute sets do not report.
+ clear(s.values)
// The delta collection cycle resets.
s.start = t
@@ -201,39 +188,36 @@ func (s *histogram[N]) cumulative(dest *metricdata.Aggregation) int {
defer s.valuesMu.Unlock()
// Do not allow modification of our copy of bounds.
- bounds := make([]float64, len(s.bounds))
- copy(bounds, s.bounds)
+ bounds := slices.Clone(s.bounds)
n := len(s.values)
hDPts := reset(h.DataPoints, n, n)
var i int
- for a, b := range s.values {
+ for _, val := range s.values {
+ hDPts[i].Attributes = val.attrs
+ hDPts[i].StartTime = s.start
+ hDPts[i].Time = t
+ hDPts[i].Count = val.count
+ hDPts[i].Bounds = bounds
+
// The HistogramDataPoint field values returned need to be copies of
// the buckets value as we will keep updating them.
//
// TODO (#3047): Making copies for bounds and counts incurs a large
// memory allocation footprint. Alternatives should be explored.
- counts := make([]uint64, len(b.counts))
- copy(counts, b.counts)
-
- hDPts[i].Attributes = a
- hDPts[i].StartTime = s.start
- hDPts[i].Time = t
- hDPts[i].Count = b.count
- hDPts[i].Bounds = bounds
- hDPts[i].BucketCounts = counts
+ hDPts[i].BucketCounts = slices.Clone(val.counts)
if !s.noSum {
- hDPts[i].Sum = b.total
+ hDPts[i].Sum = val.total
}
if !s.noMinMax {
- hDPts[i].Min = metricdata.NewExtrema(b.min)
- hDPts[i].Max = metricdata.NewExtrema(b.max)
+ hDPts[i].Min = metricdata.NewExtrema(val.min)
+ hDPts[i].Max = metricdata.NewExtrema(val.max)
}
- b.res.Collect(&hDPts[i].Exemplars)
+ collectExemplars(&hDPts[i].Exemplars, val.res.Collect)
i++
// TODO (#3006): This will use an unbounded amount of memory if there