Refactor exemplars to not use generic argument

sdk/metric/exemplar.go

@@ -19,21 +19,21 @@ import (
 // Note: This will only return non-nil values when the experimental exemplar
 // feature is enabled and the OTEL_METRICS_EXEMPLAR_FILTER environment variable
 // is not set to always_off.
-func reservoirFunc[N int64 | float64](agg Aggregation) func() exemplar.Reservoir[N] {
+func reservoirFunc(agg Aggregation) func() exemplar.Reservoir {
 	if !x.Exemplars.Enabled() {
 		return nil
 	}
 
 	// https://github.com/open-telemetry/opentelemetry-specification/blob/d4b241f451674e8f611bb589477680341006ad2b/specification/metrics/sdk.md#exemplar-defaults
-	resF := func() func() exemplar.Reservoir[N] {
+	resF := func() func() exemplar.Reservoir {
 		// Explicit bucket histogram aggregation with more than 1 bucket will
 		// use AlignedHistogramBucketExemplarReservoir.
 		a, ok := agg.(AggregationExplicitBucketHistogram)
 		if ok && len(a.Boundaries) > 0 {
 			cp := slices.Clone(a.Boundaries)
-			return func() exemplar.Reservoir[N] {
+			return func() exemplar.Reservoir {
 				bounds := cp
-				return exemplar.Histogram[N](bounds)
+				return exemplar.Histogram(bounds)
 			}
 		}
 
@@ -61,8 +61,8 @@ func reservoirFunc[N int64 | float64](agg Aggregation) func() exemplar.Reservoir
 			}
 		}
 
-		return func() exemplar.Reservoir[N] {
-			return exemplar.FixedSize[N](n)
+		return func() exemplar.Reservoir {
+			return exemplar.FixedSize(n)
 		}
 	}
 
@@ -73,12 +73,12 @@ func reservoirFunc[N int64 | float64](agg Aggregation) func() exemplar.Reservoir
 	case "always_on":
 		return resF()
 	case "always_off":
-		return exemplar.Drop[N]
+		return exemplar.Drop
 	case "trace_based":
 		fallthrough
 	default:
 		newR := resF()
-		return func() exemplar.Reservoir[N] {
+		return func() exemplar.Reservoir {
 			return exemplar.SampledFilter(newR())
 		}
 	}

sdk/metric/internal/aggregate/aggregate.go

@@ -39,7 +39,7 @@ type Builder[N int64 | float64] struct {
 	//
 	// If this is not provided a default factory function that returns an
 	// exemplar.Drop reservoir will be used.
-	ReservoirFunc func() exemplar.Reservoir[N]
+	ReservoirFunc func() exemplar.Reservoir
 	// 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"
@@ -50,12 +50,12 @@ type Builder[N int64 | float64] struct {
 	AggregationLimit int
 }
 
-func (b Builder[N]) resFunc() func() exemplar.Reservoir[N] {
+func (b Builder[N]) resFunc() func() exemplar.Reservoir {
 	if b.ReservoirFunc != nil {
 		return b.ReservoirFunc
 	}
 
-	return exemplar.Drop[N]
+	return exemplar.Drop
 }
 
 type fltrMeasure[N int64 | float64] func(ctx context.Context, value N, fltrAttr attribute.Set, droppedAttr []attribute.KeyValue)

sdk/metric/internal/aggregate/aggregate_test.go

@@ -49,8 +49,8 @@ var (
 	}
 )
 
-func dropExemplars[N int64 | float64]() exemplar.Reservoir[N] {
-	return exemplar.Drop[N]()
+func dropExemplars[N int64 | float64]() exemplar.Reservoir {
+	return exemplar.Drop()
 }
 
 func TestBuilderFilter(t *testing.T) {

sdk/metric/internal/aggregate/exemplar.go

@@ -0,0 +1,42 @@
+// Copyright The OpenTelemetry Authors
+// SPDX-License-Identifier: Apache-2.0
+
+package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate"
+
+import (
+	"sync"
+
+	"go.opentelemetry.io/otel/sdk/metric/internal/exemplar"
+	"go.opentelemetry.io/otel/sdk/metric/metricdata"
+)
+
+var exemplarPool = sync.Pool{
+	New: func() any { return new([]exemplar.Exemplar) },
+}
+
+func collectExemplars[N int64 | float64](out *[]metricdata.Exemplar[N], f func(*[]exemplar.Exemplar)) {
+	dest := exemplarPool.Get().(*[]exemplar.Exemplar)
+	defer func() {
+		*dest = (*dest)[:0]
+		exemplarPool.Put(dest)
+	}()
+
+	*dest = reset(*dest, len(*out), cap(*out))
+
+	f(dest)
+
+	*out = reset(*out, len(*dest), cap(*dest))
+	for i, e := range *dest {
+		(*out)[i].FilteredAttributes = e.FilteredAttributes
+		(*out)[i].Time = e.Time
+		(*out)[i].SpanID = e.SpanID
+		(*out)[i].TraceID = e.TraceID
+
+		switch e.Value.Type() {
+		case exemplar.Int64ValueType:
+			(*out)[i].Value = N(e.Value.Int64())
+		case exemplar.Float64ValueType:
+			(*out)[i].Value = N(e.Value.Float64())
+		}
+	}
+}

sdk/metric/internal/aggregate/exemplar_test.go

@@ -0,0 +1,50 @@
+// Copyright The OpenTelemetry Authors
+// SPDX-License-Identifier: Apache-2.0
+
+package aggregate
+
+import (
+	"testing"
+	"time"
+
+	"github.com/stretchr/testify/assert"
+
+	"go.opentelemetry.io/otel/attribute"
+	"go.opentelemetry.io/otel/sdk/metric/internal/exemplar"
+	"go.opentelemetry.io/otel/sdk/metric/metricdata"
+)
+
+func TestCollectExemplars(t *testing.T) {
+	t.Run("Int64", testCollectExemplars[int64]())
+	t.Run("Float64", testCollectExemplars[float64]())
+}
+
+func testCollectExemplars[N int64 | float64]() func(t *testing.T) {
+	return func(t *testing.T) {
+		now := time.Now()
+		alice := attribute.String("user", "Alice")
+		value := N(1)
+		spanID := [8]byte{0x1}
+		traceID := [16]byte{0x1}
+
+		out := new([]metricdata.Exemplar[N])
+		collectExemplars(out, func(in *[]exemplar.Exemplar) {
+			*in = reset(*in, 1, 1)
+			(*in)[0] = exemplar.Exemplar{
+				FilteredAttributes: []attribute.KeyValue{alice},
+				Time:               now,
+				Value:              exemplar.NewValue(value),
+				SpanID:             spanID[:],
+				TraceID:            traceID[:],
+			}
+		})
+
+		assert.Equal(t, []metricdata.Exemplar[N]{{
+			FilteredAttributes: []attribute.KeyValue{alice},
+			Time:               now,
+			Value:              value,
+			SpanID:             spanID[:],
+			TraceID:            traceID[:],
+		}}, *out)
+	}
+}

sdk/metric/internal/aggregate/exponential_histogram.go

@@ -31,7 +31,7 @@ const (
 // expoHistogramDataPoint is a single data point in an exponential histogram.
 type expoHistogramDataPoint[N int64 | float64] struct {
 	attrs attribute.Set
-	res   exemplar.Reservoir[N]
+	res   exemplar.Reservoir
 
 	count uint64
 	min   N
@@ -282,7 +282,7 @@ func (b *expoBuckets) downscale(delta int) {
 // 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() exemplar.Reservoir[N]) *expoHistogram[N] {
+func newExponentialHistogram[N int64 | float64](maxSize, maxScale int32, noMinMax, noSum bool, limit int, r func() exemplar.Reservoir) *expoHistogram[N] {
 	return &expoHistogram[N]{
 		noSum:    noSum,
 		noMinMax: noMinMax,
@@ -305,7 +305,7 @@ type expoHistogram[N int64 | float64] struct {
 	maxSize  int
 	maxScale int
 
-	newRes   func() exemplar.Reservoir[N]
+	newRes   func() exemplar.Reservoir
 	limit    limiter[*expoHistogramDataPoint[N]]
 	values   map[attribute.Distinct]*expoHistogramDataPoint[N]
 	valuesMu sync.Mutex
@@ -333,7 +333,7 @@ func (e *expoHistogram[N]) measure(ctx context.Context, value N, fltrAttr attrib
 		e.values[attr.Equivalent()] = v
 	}
 	v.record(value)
-	v.res.Offer(ctx, t, value, droppedAttr)
+	v.res.Offer(ctx, t, exemplar.NewValue(value), droppedAttr)
 }
 
 func (e *expoHistogram[N]) delta(dest *metricdata.Aggregation) int {
@@ -376,7 +376,7 @@ func (e *expoHistogram[N]) delta(dest *metricdata.Aggregation) int {
 			hDPts[i].Max = metricdata.NewExtrema(val.max)
 		}
 
-		val.res.Collect(&hDPts[i].Exemplars)
+		collectExemplars(&hDPts[i].Exemplars, val.res.Collect)
 
 		i++
 	}
@@ -429,7 +429,7 @@ func (e *expoHistogram[N]) cumulative(dest *metricdata.Aggregation) int {
 			hDPts[i].Max = metricdata.NewExtrema(val.max)
 		}
 
-		val.res.Collect(&hDPts[i].Exemplars)
+		collectExemplars(&hDPts[i].Exemplars, val.res.Collect)
 
 		i++
 		// TODO (#3006): This will use an unbounded amount of memory if there

sdk/metric/internal/aggregate/histogram.go

@@ -17,7 +17,7 @@ import (
 
 type buckets[N int64 | float64] struct {
 	attrs attribute.Set
-	res   exemplar.Reservoir[N]
+	res   exemplar.Reservoir
 
 	counts   []uint64
 	count    uint64
@@ -48,13 +48,13 @@ type histValues[N int64 | float64] struct {
 	noSum  bool
 	bounds []float64
 
-	newRes   func() exemplar.Reservoir[N]
+	newRes   func() exemplar.Reservoir
 	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() exemplar.Reservoir[N]) *histValues[N] {
+func newHistValues[N int64 | float64](bounds []float64, noSum bool, limit int, r func() exemplar.Reservoir) *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
@@ -106,12 +106,12 @@ func (s *histValues[N]) measure(ctx context.Context, value N, fltrAttr attribute
 	if !s.noSum {
 		b.sum(value)
 	}
-	b.res.Offer(ctx, t, value, droppedAttr)
+	b.res.Offer(ctx, t, exemplar.NewValue(value), droppedAttr)
 }
 
 // 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() exemplar.Reservoir[N]) *histogram[N] {
+func newHistogram[N int64 | float64](boundaries []float64, noMinMax, noSum bool, limit int, r func() exemplar.Reservoir) *histogram[N] {
 	return &histogram[N]{
 		histValues: newHistValues[N](boundaries, noSum, limit, r),
 		noMinMax:   noMinMax,
@@ -163,7 +163,7 @@ func (s *histogram[N]) delta(dest *metricdata.Aggregation) int {
 			hDPts[i].Max = metricdata.NewExtrema(val.max)
 		}
 
-		val.res.Collect(&hDPts[i].Exemplars)
+		collectExemplars(&hDPts[i].Exemplars, val.res.Collect)
 
 		i++
 	}
@@ -219,7 +219,7 @@ func (s *histogram[N]) cumulative(dest *metricdata.Aggregation) int {
 			hDPts[i].Max = metricdata.NewExtrema(val.max)
 		}
 
-		val.res.Collect(&hDPts[i].Exemplars)
+		collectExemplars(&hDPts[i].Exemplars, val.res.Collect)
 
 		i++
 		// TODO (#3006): This will use an unbounded amount of memory if there

sdk/metric/internal/aggregate/lastvalue.go

@@ -18,10 +18,10 @@ type datapoint[N int64 | float64] struct {
 	attrs     attribute.Set
 	timestamp time.Time
 	value     N
-	res       exemplar.Reservoir[N]
+	res       exemplar.Reservoir
 }
 
-func newLastValue[N int64 | float64](limit int, r func() exemplar.Reservoir[N]) *lastValue[N] {
+func newLastValue[N int64 | float64](limit int, r func() exemplar.Reservoir) *lastValue[N] {
 	return &lastValue[N]{
 		newRes: r,
 		limit:  newLimiter[datapoint[N]](limit),
@@ -33,7 +33,7 @@ func newLastValue[N int64 | float64](limit int, r func() exemplar.Reservoir[N])
 type lastValue[N int64 | float64] struct {
 	sync.Mutex
 
-	newRes func() exemplar.Reservoir[N]
+	newRes func() exemplar.Reservoir
 	limit  limiter[datapoint[N]]
 	values map[attribute.Distinct]datapoint[N]
 }
@@ -53,7 +53,7 @@ func (s *lastValue[N]) measure(ctx context.Context, value N, fltrAttr attribute.
 	d.attrs = attr
 	d.timestamp = t
 	d.value = value
-	d.res.Offer(ctx, t, value, droppedAttr)
+	d.res.Offer(ctx, t, exemplar.NewValue(value), droppedAttr)
 
 	s.values[attr.Equivalent()] = d
 }
@@ -72,7 +72,7 @@ func (s *lastValue[N]) computeAggregation(dest *[]metricdata.DataPoint[N]) {
 		// ignored.
 		(*dest)[i].Time = v.timestamp
 		(*dest)[i].Value = v.value
-		v.res.Collect(&(*dest)[i].Exemplars)
+		collectExemplars(&(*dest)[i].Exemplars, v.res.Collect)
 		i++
 	}
 	// Do not report stale values.