diff options
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.go | 98 |
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 |