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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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104
vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/sum.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"
@ -20,31 +9,55 @@ import (
"time"
"go.opentelemetry.io/otel/attribute"
"go.opentelemetry.io/otel/sdk/metric/internal/exemplar"
"go.opentelemetry.io/otel/sdk/metric/metricdata"
)
type sumValue[N int64 | float64] struct {
n N
res exemplar.FilteredReservoir[N]
attrs attribute.Set
}
// valueMap is the storage for sums.
type valueMap[N int64 | float64] struct {
sync.Mutex
values map[attribute.Set]N
newRes func() exemplar.FilteredReservoir[N]
limit limiter[sumValue[N]]
values map[attribute.Distinct]sumValue[N]
}
func newValueMap[N int64 | float64]() *valueMap[N] {
return &valueMap[N]{values: make(map[attribute.Set]N)}
func newValueMap[N int64 | float64](limit int, r func() exemplar.FilteredReservoir[N]) *valueMap[N] {
return &valueMap[N]{
newRes: r,
limit: newLimiter[sumValue[N]](limit),
values: make(map[attribute.Distinct]sumValue[N]),
}
}
func (s *valueMap[N]) measure(_ context.Context, value N, attr attribute.Set) {
func (s *valueMap[N]) measure(ctx context.Context, value N, fltrAttr attribute.Set, droppedAttr []attribute.KeyValue) {
s.Lock()
s.values[attr] += value
s.Unlock()
defer s.Unlock()
attr := s.limit.Attributes(fltrAttr, s.values)
v, ok := s.values[attr.Equivalent()]
if !ok {
v.res = s.newRes()
}
v.attrs = attr
v.n += value
v.res.Offer(ctx, value, droppedAttr)
s.values[attr.Equivalent()] = v
}
// newSum returns an aggregator that summarizes a set of measurements as their
// arithmetic sum. Each sum is scoped by attributes and the aggregation cycle
// the measurements were made in.
func newSum[N int64 | float64](monotonic bool) *sum[N] {
func newSum[N int64 | float64](monotonic bool, limit int, r func() exemplar.FilteredReservoir[N]) *sum[N] {
return &sum[N]{
valueMap: newValueMap[N](),
valueMap: newValueMap[N](limit, r),
monotonic: monotonic,
start: now(),
}
@ -74,15 +87,16 @@ func (s *sum[N]) delta(dest *metricdata.Aggregation) int {
dPts := reset(sData.DataPoints, n, n)
var i int
for attr, value := range s.values {
dPts[i].Attributes = attr
for _, val := range s.values {
dPts[i].Attributes = val.attrs
dPts[i].StartTime = s.start
dPts[i].Time = t
dPts[i].Value = value
// Do not report stale values.
delete(s.values, attr)
dPts[i].Value = val.n
collectExemplars(&dPts[i].Exemplars, val.res.Collect)
i++
}
// Do not report stale values.
clear(s.values)
// The delta collection cycle resets.
s.start = t
@ -108,11 +122,12 @@ func (s *sum[N]) cumulative(dest *metricdata.Aggregation) int {
dPts := reset(sData.DataPoints, n, n)
var i int
for attr, value := range s.values {
dPts[i].Attributes = attr
for _, value := range s.values {
dPts[i].Attributes = value.attrs
dPts[i].StartTime = s.start
dPts[i].Time = t
dPts[i].Value = value
dPts[i].Value = value.n
collectExemplars(&dPts[i].Exemplars, value.res.Collect)
// TODO (#3006): This will use an unbounded amount of memory if there
// are unbounded number of attribute sets being aggregated. Attribute
// sets that become "stale" need to be forgotten so this will not
@ -129,9 +144,9 @@ func (s *sum[N]) cumulative(dest *metricdata.Aggregation) int {
// newPrecomputedSum returns an aggregator that summarizes a set of
// observatrions as their arithmetic sum. Each sum is scoped by attributes and
// the aggregation cycle the measurements were made in.
func newPrecomputedSum[N int64 | float64](monotonic bool) *precomputedSum[N] {
func newPrecomputedSum[N int64 | float64](monotonic bool, limit int, r func() exemplar.FilteredReservoir[N]) *precomputedSum[N] {
return &precomputedSum[N]{
valueMap: newValueMap[N](),
valueMap: newValueMap[N](limit, r),
monotonic: monotonic,
start: now(),
}
@ -144,12 +159,12 @@ type precomputedSum[N int64 | float64] struct {
monotonic bool
start time.Time
reported map[attribute.Set]N
reported map[attribute.Distinct]N
}
func (s *precomputedSum[N]) delta(dest *metricdata.Aggregation) int {
t := now()
newReported := make(map[attribute.Set]N)
newReported := make(map[attribute.Distinct]N)
// If *dest is not a metricdata.Sum, memory reuse is missed. In that case,
// use the zero-value sData and hope for better alignment next cycle.
@ -164,20 +179,20 @@ func (s *precomputedSum[N]) delta(dest *metricdata.Aggregation) int {
dPts := reset(sData.DataPoints, n, n)
var i int
for attr, value := range s.values {
delta := value - s.reported[attr]
for key, value := range s.values {
delta := value.n - s.reported[key]
dPts[i].Attributes = attr
dPts[i].Attributes = value.attrs
dPts[i].StartTime = s.start
dPts[i].Time = t
dPts[i].Value = delta
collectExemplars(&dPts[i].Exemplars, value.res.Collect)
newReported[attr] = value
// Unused attribute sets do not report.
delete(s.values, attr)
newReported[key] = value.n
i++
}
// Unused attribute sets are forgotten.
// Unused attribute sets do not report.
clear(s.values)
s.reported = newReported
// The delta collection cycle resets.
s.start = t
@ -204,16 +219,17 @@ func (s *precomputedSum[N]) cumulative(dest *metricdata.Aggregation) int {
dPts := reset(sData.DataPoints, n, n)
var i int
for attr, value := range s.values {
dPts[i].Attributes = attr
for _, val := range s.values {
dPts[i].Attributes = val.attrs
dPts[i].StartTime = s.start
dPts[i].Time = t
dPts[i].Value = value
dPts[i].Value = val.n
collectExemplars(&dPts[i].Exemplars, val.res.Collect)
// Unused attribute sets do not report.
delete(s.values, attr)
i++
}
// Unused attribute sets do not report.
clear(s.values)
sData.DataPoints = dPts
*dest = sData