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vendor: update buildkit to v0.18.0-rc1

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Signed-off-by: Tonis Tiigi <tonistiigi@gmail.com>
This commit is contained in:
Tonis Tiigi
2024-11-21 12:57:27 -08:00
parent 1a039115bc
commit 13a426fca6
448 changed files with 35377 additions and 5707 deletions
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87
vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/aggregate.go generated vendored
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@ -1,16 +1,5 @@
// 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"
@ -19,6 +8,7 @@ import (
"time"
"go.opentelemetry.io/otel/attribute"
"go.opentelemetry.io/otel/sdk/metric/internal/exemplar"
"go.opentelemetry.io/otel/sdk/metric/metricdata"
)
@ -44,42 +34,73 @@ type Builder[N int64 | float64] struct {
// Filter is the attribute filter the aggregate function will use on the
// input of measurements.
Filter attribute.Filter
// ReservoirFunc is the factory function used by aggregate functions to
// create new exemplar reservoirs for a new seen attribute set.
//
// If this is not provided a default factory function that returns an
// exemplar.Drop reservoir will be used.
ReservoirFunc func() exemplar.FilteredReservoir[N]
// AggregationLimit is the cardinality limit of measurement attributes. Any
// measurement for new attributes once the limit has been reached will be
// aggregated into a single aggregate for the "otel.metric.overflow"
// attribute.
//
// If AggregationLimit is less than or equal to zero there will not be an
// aggregation limit imposed (i.e. unlimited attribute sets).
AggregationLimit int
}
func (b Builder[N]) filter(f Measure[N]) Measure[N] {
func (b Builder[N]) resFunc() func() exemplar.FilteredReservoir[N] {
if b.ReservoirFunc != nil {
return b.ReservoirFunc
}
return exemplar.Drop
}
type fltrMeasure[N int64 | float64] func(ctx context.Context, value N, fltrAttr attribute.Set, droppedAttr []attribute.KeyValue)
func (b Builder[N]) filter(f fltrMeasure[N]) Measure[N] {
if b.Filter != nil {
fltr := b.Filter // Copy to make it immutable after assignment.
return func(ctx context.Context, n N, a attribute.Set) {
fAttr, _ := a.Filter(fltr)
f(ctx, n, fAttr)
fAttr, dropped := a.Filter(fltr)
f(ctx, n, fAttr, dropped)
}
}
return f
return func(ctx context.Context, n N, a attribute.Set) {
f(ctx, n, a, nil)
}
}
// LastValue returns a last-value aggregate function input and output.
//
// The Builder.Temporality is ignored and delta is use always.
func (b Builder[N]) LastValue() (Measure[N], ComputeAggregation) {
// Delta temporality is the only temporality that makes semantic sense for
// a last-value aggregate.
lv := newLastValue[N]()
lv := newLastValue[N](b.AggregationLimit, b.resFunc())
switch b.Temporality {
case metricdata.DeltaTemporality:
return b.filter(lv.measure), lv.delta
default:
return b.filter(lv.measure), lv.cumulative
}
}
return b.filter(lv.measure), func(dest *metricdata.Aggregation) int {
// Ignore if dest is not a metricdata.Gauge. The chance for memory
// reuse of the DataPoints is missed (better luck next time).
gData, _ := (*dest).(metricdata.Gauge[N])
lv.computeAggregation(&gData.DataPoints)
*dest = gData
return len(gData.DataPoints)
// PrecomputedLastValue returns a last-value aggregate function input and
// output. The aggregation returned from the returned ComputeAggregation
// function will always only return values from the previous collection cycle.
func (b Builder[N]) PrecomputedLastValue() (Measure[N], ComputeAggregation) {
lv := newPrecomputedLastValue[N](b.AggregationLimit, b.resFunc())
switch b.Temporality {
case metricdata.DeltaTemporality:
return b.filter(lv.measure), lv.delta
default:
return b.filter(lv.measure), lv.cumulative
}
}
// PrecomputedSum returns a sum aggregate function input and output. The
// arguments passed to the input are expected to be the precomputed sum values.
func (b Builder[N]) PrecomputedSum(monotonic bool) (Measure[N], ComputeAggregation) {
s := newPrecomputedSum[N](monotonic)
s := newPrecomputedSum[N](monotonic, b.AggregationLimit, b.resFunc())
switch b.Temporality {
case metricdata.DeltaTemporality:
return b.filter(s.measure), s.delta
@ -90,7 +111,7 @@ func (b Builder[N]) PrecomputedSum(monotonic bool) (Measure[N], ComputeAggregati
// Sum returns a sum aggregate function input and output.
func (b Builder[N]) Sum(monotonic bool) (Measure[N], ComputeAggregation) {
s := newSum[N](monotonic)
s := newSum[N](monotonic, b.AggregationLimit, b.resFunc())
switch b.Temporality {
case metricdata.DeltaTemporality:
return b.filter(s.measure), s.delta
@ -102,7 +123,7 @@ func (b Builder[N]) Sum(monotonic bool) (Measure[N], ComputeAggregation) {
// ExplicitBucketHistogram returns a histogram aggregate function input and
// output.
func (b Builder[N]) ExplicitBucketHistogram(boundaries []float64, noMinMax, noSum bool) (Measure[N], ComputeAggregation) {
h := newHistogram[N](boundaries, noMinMax, noSum)
h := newHistogram[N](boundaries, noMinMax, noSum, b.AggregationLimit, b.resFunc())
switch b.Temporality {
case metricdata.DeltaTemporality:
return b.filter(h.measure), h.delta
@ -114,7 +135,7 @@ func (b Builder[N]) ExplicitBucketHistogram(boundaries []float64, noMinMax, noSu
// ExponentialBucketHistogram returns a histogram aggregate function input and
// output.
func (b Builder[N]) ExponentialBucketHistogram(maxSize, maxScale int32, noMinMax, noSum bool) (Measure[N], ComputeAggregation) {
h := newExponentialHistogram[N](maxSize, maxScale, noMinMax, noSum)
h := newExponentialHistogram[N](maxSize, maxScale, noMinMax, noSum, b.AggregationLimit, b.resFunc())
switch b.Temporality {
case metricdata.DeltaTemporality:
return b.filter(h.measure), h.delta