remove unneccessary FilteredExemplarReservoir interface

sdk/metric/internal/aggregate/aggregate.go

@@ -50,14 +50,13 @@ type Builder[N int64 | float64] struct {
 	AggregationLimit int
 }
 
-func (b Builder[N]) resFunc() func(attribute.Set) FilteredExemplarReservoir[N] {
-	if b.ExemplarFilter != nil {
-		return func(attrs attribute.Set) FilteredExemplarReservoir[N] {
-			return newFilteredExemplarReservoir[N](b.ExemplarFilter, b.ExemplarReservoirProvider(attrs))
+func (b Builder[N]) resFunc() func(attribute.Set) *filteredExemplarReservoir[N] {
+	return func(attrs attribute.Set) *filteredExemplarReservoir[N] {
+		if b.ExemplarReservoirProvider == nil {
+			return newFilteredExemplarReservoir[N](b.ExemplarFilter, exemplar.NewFixedSizeReservoir(0))
 		}
+		return newFilteredExemplarReservoir[N](b.ExemplarFilter, b.ExemplarReservoirProvider(attrs))
 	}
-
-	return dropReservoir
 }
 
 type fltrMeasure[N int64 | float64] func(ctx context.Context, value N, fltrAttr attribute.Set, droppedAttr []attribute.KeyValue)

sdk/metric/internal/aggregate/aggregate_test.go

@@ -13,6 +13,7 @@ import (
 	"github.com/stretchr/testify/assert"
 
 	"go.opentelemetry.io/otel/attribute"
+	"go.opentelemetry.io/otel/sdk/metric/exemplar"
 	"go.opentelemetry.io/otel/sdk/metric/metricdata"
 	"go.opentelemetry.io/otel/sdk/metric/metricdata/metricdatatest"
 )
@@ -72,8 +73,8 @@ func (c *clock) Register() (unregister func()) {
 	return func() { now = orig }
 }
 
-func dropExemplars[N int64 | float64](attr attribute.Set) FilteredExemplarReservoir[N] {
-	return dropReservoir[N](attr)
+func dropExemplars[N int64 | float64](attr attribute.Set) *filteredExemplarReservoir[N] {
+	return newFilteredExemplarReservoir[N](exemplar.AlwaysOffFilter, exemplar.NewFixedSizeReservoir(0))
 }
 
 func TestBuilderFilter(t *testing.T) {

sdk/metric/internal/aggregate/exponential_histogram.go

@@ -30,7 +30,7 @@ const (
 // expoHistogramDataPoint is a single data point in an exponential histogram.
 type expoHistogramDataPoint[N int64 | float64] struct {
 	attrs attribute.Set
-	res   FilteredExemplarReservoir[N]
+	res   *filteredExemplarReservoir[N]
 
 	count uint64
 	min   N
@@ -283,7 +283,7 @@ func (b *expoBuckets) downscale(delta int32) {
 // newExponentialHistogram returns an Aggregator that summarizes a set of
 // measurements as an exponential histogram. Each histogram is scoped by attributes
 // and the aggregation cycle the measurements were made in.
-func newExponentialHistogram[N int64 | float64](maxSize, maxScale int32, noMinMax, noSum bool, limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *expoHistogram[N] {
+func newExponentialHistogram[N int64 | float64](maxSize, maxScale int32, noMinMax, noSum bool, limit int, r func(attribute.Set) *filteredExemplarReservoir[N]) *expoHistogram[N] {
 	return &expoHistogram[N]{
 		noSum:    noSum,
 		noMinMax: noMinMax,
@@ -306,7 +306,7 @@ type expoHistogram[N int64 | float64] struct {
 	maxSize  int
 	maxScale int32
 
-	newRes   func(attribute.Set) FilteredExemplarReservoir[N]
+	newRes   func(attribute.Set) *filteredExemplarReservoir[N]
 	limit    limiter[*expoHistogramDataPoint[N]]
 	values   map[attribute.Distinct]*expoHistogramDataPoint[N]
 	valuesMu sync.Mutex

sdk/metric/internal/aggregate/filtered_reservoir.go

@@ -11,37 +11,24 @@ import (
 	"go.opentelemetry.io/otel/sdk/metric/exemplar"
 )
 
-// FilteredExemplarReservoir wraps a [exemplar.Reservoir] with a filter.
-type FilteredExemplarReservoir[N int64 | float64] interface {
-	// Offer accepts the parameters associated with a measurement. The
-	// parameters will be stored as an exemplar if the filter decides to
-	// sample the measurement.
-	//
-	// The passed ctx needs to contain any baggage or span that were active
-	// when the measurement was made. This information may be used by the
-	// Reservoir in making a sampling decision.
-	Offer(ctx context.Context, val N, attr []attribute.KeyValue)
-	// Collect returns all the held exemplars in the reservoir.
-	Collect(dest *[]exemplar.Exemplar)
-}
-
 // filteredExemplarReservoir handles the pre-sampled exemplar of measurements made.
 type filteredExemplarReservoir[N int64 | float64] struct {
 	filter    exemplar.Filter
 	reservoir exemplar.Reservoir
 }
 
-// newFilteredExemplarReservoir creates a [FilteredExemplarReservoir] which only offers values
-// that are allowed by the filter.
-func newFilteredExemplarReservoir[N int64 | float64](f exemplar.Filter, r exemplar.Reservoir) FilteredExemplarReservoir[N] {
+// newFilteredExemplarReservoir creates a [FilteredExemplarReservoir] which
+// only offers values that are allowed by the filter. If the provided filter is
+// nil, all measurements are dropped..
+func newFilteredExemplarReservoir[N int64 | float64](f exemplar.Filter, r exemplar.Reservoir) *filteredExemplarReservoir[N] {
 	return &filteredExemplarReservoir[N]{
 		filter:    f,
 		reservoir: r,
 	}
 }
 
 func (f *filteredExemplarReservoir[N]) Offer(ctx context.Context, val N, attr []attribute.KeyValue) {
-	if f.filter(ctx) {
+	if f.filter != nil && f.filter(ctx) {
 		// only record the current time if we are sampling this measurement.
 		f.reservoir.Offer(ctx, time.Now(), exemplar.NewValue(val), attr)
 	}

sdk/metric/internal/aggregate/histogram.go

@@ -16,7 +16,7 @@ import (
 
 type buckets[N int64 | float64] struct {
 	attrs attribute.Set
-	res   FilteredExemplarReservoir[N]
+	res   *filteredExemplarReservoir[N]
 
 	counts   []uint64
 	count    uint64
@@ -47,13 +47,13 @@ type histValues[N int64 | float64] struct {
 	noSum  bool
 	bounds []float64
 
-	newRes   func(attribute.Set) FilteredExemplarReservoir[N]
+	newRes   func(attribute.Set) *filteredExemplarReservoir[N]
 	limit    limiter[*buckets[N]]
 	values   map[attribute.Distinct]*buckets[N]
 	valuesMu sync.Mutex
 }
 
-func newHistValues[N int64 | float64](bounds []float64, noSum bool, limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *histValues[N] {
+func newHistValues[N int64 | float64](bounds []float64, noSum bool, limit int, r func(attribute.Set) *filteredExemplarReservoir[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
@@ -108,7 +108,7 @@ func (s *histValues[N]) measure(ctx context.Context, value N, fltrAttr attribute
 
 // 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(attribute.Set) FilteredExemplarReservoir[N]) *histogram[N] {
+func newHistogram[N int64 | float64](boundaries []float64, noMinMax, noSum bool, limit int, r func(attribute.Set) *filteredExemplarReservoir[N]) *histogram[N] {
 	return &histogram[N]{
 		histValues: newHistValues[N](boundaries, noSum, limit, r),
 		noMinMax:   noMinMax,

sdk/metric/internal/aggregate/lastvalue.go

@@ -16,10 +16,10 @@ import (
 type datapoint[N int64 | float64] struct {
 	attrs attribute.Set
 	value N
-	res   FilteredExemplarReservoir[N]
+	res   *filteredExemplarReservoir[N]
 }
 
-func newLastValue[N int64 | float64](limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *lastValue[N] {
+func newLastValue[N int64 | float64](limit int, r func(attribute.Set) *filteredExemplarReservoir[N]) *lastValue[N] {
 	return &lastValue[N]{
 		newRes: r,
 		limit:  newLimiter[datapoint[N]](limit),
@@ -32,7 +32,7 @@ func newLastValue[N int64 | float64](limit int, r func(attribute.Set) FilteredEx
 type lastValue[N int64 | float64] struct {
 	sync.Mutex
 
-	newRes func(attribute.Set) FilteredExemplarReservoir[N]
+	newRes func(attribute.Set) *filteredExemplarReservoir[N]
 	limit  limiter[datapoint[N]]
 	values map[attribute.Distinct]datapoint[N]
 	start  time.Time
@@ -114,7 +114,7 @@ func (s *lastValue[N]) copyDpts(dest *[]metricdata.DataPoint[N], t time.Time) in
 
 // newPrecomputedLastValue returns an aggregator that summarizes a set of
 // observations as the last one made.
-func newPrecomputedLastValue[N int64 | float64](limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *precomputedLastValue[N] {
+func newPrecomputedLastValue[N int64 | float64](limit int, r func(attribute.Set) *filteredExemplarReservoir[N]) *precomputedLastValue[N] {
 	return &precomputedLastValue[N]{lastValue: newLastValue[N](limit, r)}
 }
 

sdk/metric/internal/aggregate/sum.go

@@ -14,19 +14,19 @@ import (
 
 type sumValue[N int64 | float64] struct {
 	n     N
-	res   FilteredExemplarReservoir[N]
+	res   *filteredExemplarReservoir[N]
 	attrs attribute.Set
 }
 
 // valueMap is the storage for sums.
 type valueMap[N int64 | float64] struct {
 	sync.Mutex
-	newRes func(attribute.Set) FilteredExemplarReservoir[N]
+	newRes func(attribute.Set) *filteredExemplarReservoir[N]
 	limit  limiter[sumValue[N]]
 	values map[attribute.Distinct]sumValue[N]
 }
 
-func newValueMap[N int64 | float64](limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *valueMap[N] {
+func newValueMap[N int64 | float64](limit int, r func(attribute.Set) *filteredExemplarReservoir[N]) *valueMap[N] {
 	return &valueMap[N]{
 		newRes: r,
 		limit:  newLimiter[sumValue[N]](limit),
@@ -54,7 +54,7 @@ func (s *valueMap[N]) measure(ctx context.Context, value N, fltrAttr attribute.S
 // 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, limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *sum[N] {
+func newSum[N int64 | float64](monotonic bool, limit int, r func(attribute.Set) *filteredExemplarReservoir[N]) *sum[N] {
 	return &sum[N]{
 		valueMap:  newValueMap[N](limit, r),
 		monotonic: monotonic,
@@ -143,7 +143,7 @@ func (s *sum[N]) cumulative(dest *metricdata.Aggregation) int {
 // newPrecomputedSum returns an aggregator that summarizes a set of
 // observations 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, limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *precomputedSum[N] {
+func newPrecomputedSum[N int64 | float64](monotonic bool, limit int, r func(attribute.Set) *filteredExemplarReservoir[N]) *precomputedSum[N] {
 	return &precomputedSum[N]{
 		valueMap:  newValueMap[N](limit, r),
 		monotonic: monotonic,