1 files changed, 45 insertions, 17 deletions

diff --git a/vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/sum.go b/vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/sum.go
index 1e52ff0d1..02de2483f 100644
--- a/vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/sum.go
+++ b/vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/sum.go
@@ -20,31 +20,55 @@ 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.Reservoir[N]
+}
+
 // valueMap is the storage for sums.
 type valueMap[N int64 | float64] struct {
 	sync.Mutex
-	values map[attribute.Set]N
+	newRes func() exemplar.Reservoir[N]
+	limit  limiter[sumValue[N]]
+	values map[attribute.Set]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.Reservoir[N]) *valueMap[N] {
+	return &valueMap[N]{
+		newRes: r,
+		limit:  newLimiter[sumValue[N]](limit),
+		values: make(map[attribute.Set]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) {
+	t := now()
+
 	s.Lock()
-	s.values[attr] += value
-	s.Unlock()
+	defer s.Unlock()
+
+	attr := s.limit.Attributes(fltrAttr, s.values)
+	v, ok := s.values[attr]
+	if !ok {
+		v.res = s.newRes()
+	}
+
+	v.n += value
+	v.res.Offer(ctx, t, value, droppedAttr)
+
+	s.values[attr] = 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.Reservoir[N]) *sum[N] {
 	return &sum[N]{
-		valueMap:  newValueMap[N](),
+		valueMap:  newValueMap[N](limit, r),
 		monotonic: monotonic,
 		start:     now(),
 	}
@@ -74,11 +98,12 @@ func (s *sum[N]) delta(dest *metricdata.Aggregation) int {
 	dPts := reset(sData.DataPoints, n, n)
 
 	var i int
-	for attr, value := range s.values {
+	for attr, val := range s.values {
 		dPts[i].Attributes = attr
 		dPts[i].StartTime = s.start
 		dPts[i].Time = t
-		dPts[i].Value = value
+		dPts[i].Value = val.n
+		val.res.Collect(&dPts[i].Exemplars)
 		// Do not report stale values.
 		delete(s.values, attr)
 		i++
@@ -112,7 +137,8 @@ func (s *sum[N]) cumulative(dest *metricdata.Aggregation) int {
 		dPts[i].Attributes = attr
 		dPts[i].StartTime = s.start
 		dPts[i].Time = t
-		dPts[i].Value = value
+		dPts[i].Value = value.n
+		value.res.Collect(&dPts[i].Exemplars)
 		// 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 +155,9 @@ 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.Reservoir[N]) *precomputedSum[N] {
 	return &precomputedSum[N]{
-		valueMap:  newValueMap[N](),
+		valueMap:  newValueMap[N](limit, r),
 		monotonic: monotonic,
 		start:     now(),
 	}
@@ -165,14 +191,15 @@ func (s *precomputedSum[N]) delta(dest *metricdata.Aggregation) int {
 
 	var i int
 	for attr, value := range s.values {
-		delta := value - s.reported[attr]
+		delta := value.n - s.reported[attr]
 
 		dPts[i].Attributes = attr
 		dPts[i].StartTime = s.start
 		dPts[i].Time = t
 		dPts[i].Value = delta
+		value.res.Collect(&dPts[i].Exemplars)
 
-		newReported[attr] = value
+		newReported[attr] = value.n
 		// Unused attribute sets do not report.
 		delete(s.values, attr)
 		i++
@@ -204,11 +231,12 @@ func (s *precomputedSum[N]) cumulative(dest *metricdata.Aggregation) int {
 	dPts := reset(sData.DataPoints, n, n)
 
 	var i int
-	for attr, value := range s.values {
+	for attr, val := range s.values {
 		dPts[i].Attributes = attr
 		dPts[i].StartTime = s.start
 		dPts[i].Time = t
-		dPts[i].Value = value
+		dPts[i].Value = val.n
+		val.res.Collect(&dPts[i].Exemplars)
 
 		// Unused attribute sets do not report.
 		delete(s.values, attr)