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deps: update buildkit, vendor changes
Signed-off-by: Laura Brehm <laurabrehm@hey.com>
This commit is contained in:
133
vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/aggregate.go
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133
vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/aggregate.go
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// Copyright The OpenTelemetry Authors
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate"
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import (
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"context"
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"time"
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"go.opentelemetry.io/otel/attribute"
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"go.opentelemetry.io/otel/sdk/metric/metricdata"
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)
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// now is used to return the current local time while allowing tests to
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// override the default time.Now function.
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var now = time.Now
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// Measure receives measurements to be aggregated.
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type Measure[N int64 | float64] func(context.Context, N, attribute.Set)
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// ComputeAggregation stores the aggregate of measurements into dest and
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// returns the number of aggregate data-points output.
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type ComputeAggregation func(dest *metricdata.Aggregation) int
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// Builder builds an aggregate function.
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type Builder[N int64 | float64] struct {
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// Temporality is the temporality used for the returned aggregate function.
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//
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// If this is not provided a default of cumulative will be used (except for
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// the last-value aggregate function where delta is the only appropriate
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// temporality).
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Temporality metricdata.Temporality
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// Filter is the attribute filter the aggregate function will use on the
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// input of measurements.
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Filter attribute.Filter
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}
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func (b Builder[N]) filter(f Measure[N]) Measure[N] {
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if b.Filter != nil {
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fltr := b.Filter // Copy to make it immutable after assignment.
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return func(ctx context.Context, n N, a attribute.Set) {
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fAttr, _ := a.Filter(fltr)
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f(ctx, n, fAttr)
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}
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}
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return f
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}
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// LastValue returns a last-value aggregate function input and output.
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//
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// The Builder.Temporality is ignored and delta is use always.
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func (b Builder[N]) LastValue() (Measure[N], ComputeAggregation) {
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// Delta temporality is the only temporality that makes semantic sense for
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// a last-value aggregate.
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lv := newLastValue[N]()
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return b.filter(lv.measure), func(dest *metricdata.Aggregation) int {
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// Ignore if dest is not a metricdata.Gauge. The chance for memory
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// reuse of the DataPoints is missed (better luck next time).
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gData, _ := (*dest).(metricdata.Gauge[N])
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lv.computeAggregation(&gData.DataPoints)
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*dest = gData
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return len(gData.DataPoints)
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}
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}
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// PrecomputedSum returns a sum aggregate function input and output. The
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// arguments passed to the input are expected to be the precomputed sum values.
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func (b Builder[N]) PrecomputedSum(monotonic bool) (Measure[N], ComputeAggregation) {
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s := newPrecomputedSum[N](monotonic)
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switch b.Temporality {
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case metricdata.DeltaTemporality:
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return b.filter(s.measure), s.delta
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default:
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return b.filter(s.measure), s.cumulative
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}
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}
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// Sum returns a sum aggregate function input and output.
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func (b Builder[N]) Sum(monotonic bool) (Measure[N], ComputeAggregation) {
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s := newSum[N](monotonic)
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switch b.Temporality {
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case metricdata.DeltaTemporality:
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return b.filter(s.measure), s.delta
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default:
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return b.filter(s.measure), s.cumulative
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}
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}
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// ExplicitBucketHistogram returns a histogram aggregate function input and
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// output.
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func (b Builder[N]) ExplicitBucketHistogram(boundaries []float64, noMinMax, noSum bool) (Measure[N], ComputeAggregation) {
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h := newHistogram[N](boundaries, noMinMax, noSum)
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switch b.Temporality {
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case metricdata.DeltaTemporality:
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return b.filter(h.measure), h.delta
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default:
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return b.filter(h.measure), h.cumulative
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}
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}
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// ExponentialBucketHistogram returns a histogram aggregate function input and
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// output.
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func (b Builder[N]) ExponentialBucketHistogram(maxSize, maxScale int32, noMinMax, noSum bool) (Measure[N], ComputeAggregation) {
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h := newExponentialHistogram[N](maxSize, maxScale, noMinMax, noSum)
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switch b.Temporality {
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case metricdata.DeltaTemporality:
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return b.filter(h.measure), h.delta
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default:
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return b.filter(h.measure), h.cumulative
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}
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}
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// reset ensures s has capacity and sets it length. If the capacity of s too
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// small, a new slice is returned with the specified capacity and length.
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func reset[T any](s []T, length, capacity int) []T {
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if cap(s) < capacity {
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return make([]T, length, capacity)
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}
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return s[:length]
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}
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