Simplify the histogram implementation (#4370)

sdk/metric/internal/aggregate/aggregate.go

@@ -16,12 +16,17 @@ package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggreg
 
 import (
 	"context"
+	"time"
 
 	"go.opentelemetry.io/otel/attribute"
 	"go.opentelemetry.io/otel/sdk/metric/aggregation"
 	"go.opentelemetry.io/otel/sdk/metric/metricdata"
 )
 
+// now is used to return the current local time while allowing tests to
+// override the default time.Now function.
+var now = time.Now
+
 // Measure receives measurements to be aggregated.
 type Measure[N int64 | float64] func(context.Context, N, attribute.Set)
 
@@ -53,19 +58,6 @@ func (b Builder[N]) filter(f Measure[N]) Measure[N] {
 	return f
 }
 
-func (b Builder[N]) input(agg aggregator[N]) Measure[N] {
-	if b.Filter != nil {
-		fltr := b.Filter // Copy to make it immutable after assignment.
-		return func(_ context.Context, n N, a attribute.Set) {
-			fAttr, _ := a.Filter(fltr)
-			agg.Aggregate(n, fAttr)
-		}
-	}
-	return func(_ context.Context, n N, a attribute.Set) {
-		agg.Aggregate(n, a)
-	}
-}
-
 // LastValue returns a last-value aggregate function input and output.
 //
 // The Builder.Temporality is ignored and delta is use always.
@@ -111,19 +103,12 @@ func (b Builder[N]) Sum(monotonic bool) (Measure[N], ComputeAggregation) {
 // ExplicitBucketHistogram returns a histogram aggregate function input and
 // output.
 func (b Builder[N]) ExplicitBucketHistogram(cfg aggregation.ExplicitBucketHistogram, noSum bool) (Measure[N], ComputeAggregation) {
-	var h aggregator[N]
+	h := newHistogram[N](cfg, noSum)
 	switch b.Temporality {
 	case metricdata.DeltaTemporality:
-		h = newDeltaHistogram[N](cfg, noSum)
+		return b.filter(h.measure), h.delta
 	default:
-		h = newCumulativeHistogram[N](cfg, noSum)
+		return b.filter(h.measure), h.cumulative
-	}
-	return b.input(h), func(dest *metricdata.Aggregation) int {
-		// TODO (#4220): optimize memory reuse here.
-		*dest = h.Aggregation()
-
-		hData, _ := (*dest).(metricdata.Histogram[N])
-		return len(hData.DataPoints)
 	}
 }
 

sdk/metric/internal/aggregate/aggregate_test.go

@@ -55,21 +55,12 @@ var (
 	}
 )
 
-type inputTester[N int64 | float64] struct {
+func TestBuilderFilter(t *testing.T) {
-	aggregator[N]
+	t.Run("Int64", testBuilderFilter[int64]())
-
+	t.Run("Float64", testBuilderFilter[float64]())
-	value N
-	attr  attribute.Set
 }
 
-func (it *inputTester[N]) Aggregate(v N, a attribute.Set) { it.value, it.attr = v, a }
+func testBuilderFilter[N int64 | float64]() func(t *testing.T) {
-
-func TestBuilderInput(t *testing.T) {
-	t.Run("Int64", testBuilderInput[int64]())
-	t.Run("Float64", testBuilderInput[float64]())
-}
-
-func testBuilderInput[N int64 | float64]() func(t *testing.T) {
 	return func(t *testing.T) {
 		t.Helper()
 
@@ -78,12 +69,11 @@ func testBuilderInput[N int64 | float64]() func(t *testing.T) {
 			return func(t *testing.T) {
 				t.Helper()
 
-				it := &inputTester[N]{}
+				meas := b.filter(func(_ context.Context, v N, a attribute.Set) {
-				meas := b.input(it)
+					assert.Equal(t, value, v, "measured incorrect value")
+					assert.Equal(t, wantA, a, "measured incorrect attributes")
+				})
 				meas(context.Background(), value, attr)
-
-				assert.Equal(t, value, it.value, "measured incorrect value")
-				assert.Equal(t, wantA, it.attr, "measured incorrect attributes")
 			}
 		}
 

sdk/metric/internal/aggregate/aggregator.go

@@ -1,40 +0,0 @@
-// 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.
-
-package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate"
-
-import (
-	"time"
-
-	"go.opentelemetry.io/otel/attribute"
-	"go.opentelemetry.io/otel/sdk/metric/metricdata"
-)
-
-// now is used to return the current local time while allowing tests to
-// override the default time.Now function.
-var now = time.Now
-
-// aggregator forms an aggregation from a collection of recorded measurements.
-//
-// Aggregators need to be comparable so they can be de-duplicated by the SDK
-// when it creates them for multiple views.
-type aggregator[N int64 | float64] interface {
-	// Aggregate records the measurement, scoped by attr, and aggregates it
-	// into an aggregation.
-	Aggregate(measurement N, attr attribute.Set)
-
-	// Aggregation returns an Aggregation, for all the aggregated
-	// measurements made and ends an aggregation cycle.
-	Aggregation() metricdata.Aggregation
-}

sdk/metric/internal/aggregate/aggregator_test.go

@@ -1,148 +0,0 @@
-// 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.
-
-package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate"
-
-import (
-	"strconv"
-	"sync"
-	"testing"
-
-	"github.com/stretchr/testify/assert"
-
-	"go.opentelemetry.io/otel/attribute"
-	"go.opentelemetry.io/otel/sdk/metric/metricdata"
-	"go.opentelemetry.io/otel/sdk/metric/metricdata/metricdatatest"
-)
-
-const (
-	defaultGoroutines   = 5
-	defaultMeasurements = 30
-	defaultCycles       = 3
-)
-
-var carol = attribute.NewSet(attribute.String("user", "carol"), attribute.Bool("admin", false))
-
-func monoIncr[N int64 | float64]() setMap[N] {
-	return setMap[N]{alice: 1, bob: 10, carol: 2}
-}
-
-// setMap maps attribute sets to a number.
-type setMap[N int64 | float64] map[attribute.Set]N
-
-// expectFunc is a function that returns an Aggregation of expected values for
-// a cycle that contains m measurements (total across all goroutines). Each
-// call advances the cycle.
-type expectFunc func(m int) metricdata.Aggregation
-
-// aggregatorTester runs an acceptance test on an Aggregator. It will ask an
-// Aggregator to aggregate a set of values as if they were real measurements
-// made MeasurementN number of times. This will be done in GoroutineN number
-// of different goroutines. After the Aggregator has been asked to aggregate
-// all these measurements, it is validated using a passed expecterFunc. This
-// set of operation is a single cycle, and the the aggregatorTester will run
-// CycleN number of cycles.
-type aggregatorTester[N int64 | float64] struct {
-	// GoroutineN is the number of goroutines aggregatorTester will use to run
-	// the test with.
-	GoroutineN int
-	// MeasurementN is the number of measurements that are made each cycle a
-	// goroutine runs the test.
-	MeasurementN int
-	// CycleN is the number of times a goroutine will make a set of
-	// measurements.
-	CycleN int
-}
-
-func (at *aggregatorTester[N]) Run(a aggregator[N], incr setMap[N], eFunc expectFunc) func(*testing.T) {
-	m := at.MeasurementN * at.GoroutineN
-	return func(t *testing.T) {
-		t.Run("Comparable", func(t *testing.T) {
-			assert.NotPanics(t, func() {
-				_ = map[aggregator[N]]struct{}{a: {}}
-			})
-		})
-
-		t.Run("CorrectnessConcurrentSafe", func(t *testing.T) {
-			for i := 0; i < at.CycleN; i++ {
-				var wg sync.WaitGroup
-				wg.Add(at.GoroutineN)
-				for j := 0; j < at.GoroutineN; j++ {
-					go func() {
-						defer wg.Done()
-						for k := 0; k < at.MeasurementN; k++ {
-							for attrs, n := range incr {
-								a.Aggregate(N(n), attrs)
-							}
-						}
-					}()
-				}
-				wg.Wait()
-
-				metricdatatest.AssertAggregationsEqual(t, eFunc(m), a.Aggregation())
-			}
-		})
-	}
-}
-
-var bmarkResults metricdata.Aggregation
-
-func benchmarkAggregatorN[N int64 | float64](b *testing.B, factory func() aggregator[N], count int) {
-	attrs := make([]attribute.Set, count)
-	for i := range attrs {
-		attrs[i] = attribute.NewSet(attribute.Int("value", i))
-	}
-
-	b.Run("Aggregate", func(b *testing.B) {
-		agg := factory()
-		b.ReportAllocs()
-		b.ResetTimer()
-
-		for n := 0; n < b.N; n++ {
-			for _, attr := range attrs {
-				agg.Aggregate(1, attr)
-			}
-		}
-		bmarkResults = agg.Aggregation()
-	})
-
-	b.Run("Aggregations", func(b *testing.B) {
-		aggs := make([]aggregator[N], b.N)
-		for n := range aggs {
-			a := factory()
-			for _, attr := range attrs {
-				a.Aggregate(1, attr)
-			}
-			aggs[n] = a
-		}
-
-		b.ReportAllocs()
-		b.ResetTimer()
-
-		for n := 0; n < b.N; n++ {
-			bmarkResults = aggs[n].Aggregation()
-		}
-	})
-}
-
-func benchmarkAggregator[N int64 | float64](factory func() aggregator[N]) func(*testing.B) {
-	counts := []int{1, 10, 100}
-	return func(b *testing.B) {
-		for _, n := range counts {
-			b.Run(strconv.Itoa(n), func(b *testing.B) {
-				benchmarkAggregatorN(b, factory, n)
-			})
-		}
-	}
-}

sdk/metric/internal/aggregate/histogram.go

@@ -15,6 +15,7 @@
 package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate"
 
 import (
+	"context"
 	"sort"
 	"sync"
 	"time"
@@ -75,7 +76,7 @@ func newHistValues[N int64 | float64](bounds []float64, noSum bool) *histValues[
 
 // Aggregate records the measurement value, scoped by attr, and aggregates it
 // into a histogram.
-func (s *histValues[N]) Aggregate(value N, attr attribute.Set) {
+func (s *histValues[N]) measure(_ context.Context, value N, attr attribute.Set) {
 	// This search will return an index in the range [0, len(s.bounds)], where
 	// it will return len(s.bounds) if value is greater than the last element
 	// of s.bounds. This aligns with the buckets in that the length of buckets
@@ -106,111 +107,93 @@ func (s *histValues[N]) Aggregate(value N, attr attribute.Set) {
 	}
 }
 
-// newDeltaHistogram returns an Aggregator that summarizes a set of
+// newHistogram returns an Aggregator that summarizes a set of measurements as
-// measurements as an histogram. Each histogram is scoped by attributes and
+// an histogram.
-// the aggregation cycle the measurements were made in.
+func newHistogram[N int64 | float64](cfg aggregation.ExplicitBucketHistogram, noSum bool) *histogram[N] {
-//
+	return &histogram[N]{
-// Each aggregation cycle is treated independently. When the returned
-// Aggregator's Aggregations method is called it will reset all histogram
-// counts to zero.
-func newDeltaHistogram[N int64 | float64](cfg aggregation.ExplicitBucketHistogram, noSum bool) aggregator[N] {
-	return &deltaHistogram[N]{
 		histValues: newHistValues[N](cfg.Boundaries, noSum),
 		noMinMax:   cfg.NoMinMax,
 		start:      now(),
 	}
 }
 
-// deltaHistogram summarizes a set of measurements made in a single
+// histogram summarizes a set of measurements as an histogram with explicitly
-// aggregation cycle as an histogram with explicitly defined buckets.
+// defined buckets.
-type deltaHistogram[N int64 | float64] struct {
+type histogram[N int64 | float64] struct {
 	*histValues[N]
 
 	noMinMax bool
 	start    time.Time
 }
 
-func (s *deltaHistogram[N]) Aggregation() metricdata.Aggregation {
+func (s *histogram[N]) delta(dest *metricdata.Aggregation) int {
+	t := now()
+
+	// If *dest is not a metricdata.Histogram, memory reuse is missed. In that
+	// case, use the zero-value h and hope for better alignment next cycle.
+	h, _ := (*dest).(metricdata.Histogram[N])
+	h.Temporality = metricdata.DeltaTemporality
+
 	s.valuesMu.Lock()
 	defer s.valuesMu.Unlock()
 
-	if len(s.values) == 0 {
-		return nil
-	}
-
-	t := now()
 	// Do not allow modification of our copy of bounds.
 	bounds := make([]float64, len(s.bounds))
 	copy(bounds, s.bounds)
-	h := metricdata.Histogram[N]{
+
-		Temporality: metricdata.DeltaTemporality,
+	n := len(s.values)
-		DataPoints:  make([]metricdata.HistogramDataPoint[N], 0, len(s.values)),
+	hDPts := reset(h.DataPoints, n, n)
-	}
+
+	var i int
 	for a, b := range s.values {
-		hdp := metricdata.HistogramDataPoint[N]{
+		hDPts[i].Attributes = a
-			Attributes:   a,
+		hDPts[i].StartTime = s.start
-			StartTime:    s.start,
+		hDPts[i].Time = t
-			Time:         t,
+		hDPts[i].Count = b.count
-			Count:        b.count,
+		hDPts[i].Bounds = bounds
-			Bounds:       bounds,
+		hDPts[i].BucketCounts = b.counts
-			BucketCounts: b.counts,
+
-		}
 		if !s.noSum {
-			hdp.Sum = b.total
+			hDPts[i].Sum = b.total
 		}
+
 		if !s.noMinMax {
-			hdp.Min = metricdata.NewExtrema(b.min)
+			hDPts[i].Min = metricdata.NewExtrema(b.min)
-			hdp.Max = metricdata.NewExtrema(b.max)
+			hDPts[i].Max = metricdata.NewExtrema(b.max)
 		}
-		h.DataPoints = append(h.DataPoints, hdp)
 
 		// Unused attribute sets do not report.
 		delete(s.values, a)
+		i++
 	}
 	// The delta collection cycle resets.
 	s.start = t
-	return h
+
+	h.DataPoints = hDPts
+	*dest = h
+
+	return n
 }
 
-// newCumulativeHistogram returns an Aggregator that summarizes a set of
+func (s *histogram[N]) cumulative(dest *metricdata.Aggregation) int {
-// measurements as an histogram. Each histogram is scoped by attributes.
+	t := now()
-//
-// Each aggregation cycle builds from the previous, the histogram counts are
-// the bucketed counts of all values aggregated since the returned Aggregator
-// was created.
-func newCumulativeHistogram[N int64 | float64](cfg aggregation.ExplicitBucketHistogram, noSum bool) aggregator[N] {
-	return &cumulativeHistogram[N]{
-		histValues: newHistValues[N](cfg.Boundaries, noSum),
-		noMinMax:   cfg.NoMinMax,
-		start:      now(),
-	}
-}
 
-// cumulativeHistogram summarizes a set of measurements made over all
+	// If *dest is not a metricdata.Histogram, memory reuse is missed. In that
-// aggregation cycles as an histogram with explicitly defined buckets.
+	// case, use the zero-value h and hope for better alignment next cycle.
-type cumulativeHistogram[N int64 | float64] struct {
+	h, _ := (*dest).(metricdata.Histogram[N])
-	*histValues[N]
+	h.Temporality = metricdata.CumulativeTemporality
 
-	noMinMax bool
-	start    time.Time
-}
-
-func (s *cumulativeHistogram[N]) Aggregation() metricdata.Aggregation {
 	s.valuesMu.Lock()
 	defer s.valuesMu.Unlock()
 
-	if len(s.values) == 0 {
-		return nil
-	}
-
-	t := now()
 	// Do not allow modification of our copy of bounds.
 	bounds := make([]float64, len(s.bounds))
 	copy(bounds, s.bounds)
-	h := metricdata.Histogram[N]{
+
-		Temporality: metricdata.CumulativeTemporality,
+	n := len(s.values)
-		DataPoints:  make([]metricdata.HistogramDataPoint[N], 0, len(s.values)),
+	hDPts := reset(h.DataPoints, n, n)
-	}
+
+	var i int
 	for a, b := range s.values {
 		// The HistogramDataPoint field values returned need to be copies of
 		// the buckets value as we will keep updating them.
@@ -220,26 +203,30 @@ func (s *cumulativeHistogram[N]) Aggregation() metricdata.Aggregation {
 		counts := make([]uint64, len(b.counts))
 		copy(counts, b.counts)
 
-		hdp := metricdata.HistogramDataPoint[N]{
+		hDPts[i].Attributes = a
-			Attributes:   a,
+		hDPts[i].StartTime = s.start
-			StartTime:    s.start,
+		hDPts[i].Time = t
-			Time:         t,
+		hDPts[i].Count = b.count
-			Count:        b.count,
+		hDPts[i].Bounds = bounds
-			Bounds:       bounds,
+		hDPts[i].BucketCounts = counts
-			BucketCounts: counts,
+
-		}
 		if !s.noSum {
-			hdp.Sum = b.total
+			hDPts[i].Sum = b.total
 		}
+
 		if !s.noMinMax {
-			hdp.Min = metricdata.NewExtrema(b.min)
+			hDPts[i].Min = metricdata.NewExtrema(b.min)
-			hdp.Max = metricdata.NewExtrema(b.max)
+			hDPts[i].Max = metricdata.NewExtrema(b.max)
 		}
-		h.DataPoints = append(h.DataPoints, hdp)
+		i++
 		// 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
 		// overload the system.
 	}
-	return h
+
+	h.DataPoints = hDPts
+	*dest = h
+
+	return n
 }

sdk/metric/internal/aggregate/histogram_test.go

@@ -15,6 +15,7 @@
 package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate"
 
 import (
+	"context"
 	"sort"
 	"testing"
 
@@ -37,74 +38,155 @@ var (
 
 func TestHistogram(t *testing.T) {
 	t.Cleanup(mockTime(now))
-	t.Run("Int64", testHistogram[int64])
+
-	t.Run("Float64", testHistogram[float64])
+	t.Run("Int64/Delta/Sum", testDeltaHist[int64](conf[int64]{hPt: hPointSummed[int64]}))
+	t.Run("Int64/Delta/NoSum", testDeltaHist[int64](conf[int64]{noSum: true, hPt: hPoint[int64]}))
+	t.Run("Float64/Delta/Sum", testDeltaHist[float64](conf[float64]{hPt: hPointSummed[float64]}))
+	t.Run("Float64/Delta/NoSum", testDeltaHist[float64](conf[float64]{noSum: true, hPt: hPoint[float64]}))
+
+	t.Run("Int64/Cumulative/Sum", testCumulativeHist[int64](conf[int64]{hPt: hPointSummed[int64]}))
+	t.Run("Int64/Cumulative/NoSum", testCumulativeHist[int64](conf[int64]{noSum: true, hPt: hPoint[int64]}))
+	t.Run("Float64/Cumulative/Sum", testCumulativeHist[float64](conf[float64]{hPt: hPointSummed[float64]}))
+	t.Run("Float64/Cumulative/NoSum", testCumulativeHist[float64](conf[float64]{noSum: true, hPt: hPoint[float64]}))
 }
 
-func testHistogram[N int64 | float64](t *testing.T) {
+type conf[N int64 | float64] struct {
-	tester := &aggregatorTester[N]{
+	noSum bool
-		GoroutineN:   defaultGoroutines,
+	hPt   func(attribute.Set, N, uint64) metricdata.HistogramDataPoint[N]
-		MeasurementN: defaultMeasurements,
-		CycleN:       defaultCycles,
-	}
-
-	incr := monoIncr[N]()
-	eFunc := deltaHistSummedExpecter[N](incr)
-	t.Run("Delta/Summed", tester.Run(newDeltaHistogram[N](histConf, false), incr, eFunc))
-	eFunc = deltaHistExpecter[N](incr)
-	t.Run("Delta/NoSum", tester.Run(newDeltaHistogram[N](histConf, true), incr, eFunc))
-	eFunc = cumuHistSummedExpecter[N](incr)
-	t.Run("Cumulative/Summed", tester.Run(newCumulativeHistogram[N](histConf, false), incr, eFunc))
-	eFunc = cumuHistExpecter[N](incr)
-	t.Run("Cumulative/NoSum", tester.Run(newCumulativeHistogram[N](histConf, true), incr, eFunc))
 }
 
-func deltaHistSummedExpecter[N int64 | float64](incr setMap[N]) expectFunc {
+func testDeltaHist[N int64 | float64](c conf[N]) func(t *testing.T) {
-	h := metricdata.Histogram[N]{Temporality: metricdata.DeltaTemporality}
+	in, out := Builder[N]{
-	return func(m int) metricdata.Aggregation {
+		Temporality: metricdata.DeltaTemporality,
-		h.DataPoints = make([]metricdata.HistogramDataPoint[N], 0, len(incr))
+		Filter:      attrFltr,
-		for a, v := range incr {
+	}.ExplicitBucketHistogram(histConf, c.noSum)
-			h.DataPoints = append(h.DataPoints, hPointSummed[N](a, v, uint64(m)))
+	ctx := context.Background()
-		}
+	return test[N](in, out, []teststep[N]{
-		return h
+		{
-	}
+			input: []arg[N]{},
+			expect: output{
+				n: 0,
+				agg: metricdata.Histogram[N]{
+					Temporality: metricdata.DeltaTemporality,
+					DataPoints:  []metricdata.HistogramDataPoint[N]{},
+				},
+			},
+		},
+		{
+			input: []arg[N]{
+				{ctx, 2, alice},
+				{ctx, 10, bob},
+				{ctx, 2, alice},
+				{ctx, 2, alice},
+				{ctx, 10, bob},
+			},
+			expect: output{
+				n: 2,
+				agg: metricdata.Histogram[N]{
+					Temporality: metricdata.DeltaTemporality,
+					DataPoints: []metricdata.HistogramDataPoint[N]{
+						c.hPt(fltrAlice, 2, 3),
+						c.hPt(fltrBob, 10, 2),
+					},
+				},
+			},
+		},
+		{
+			input: []arg[N]{
+				{ctx, 10, alice},
+				{ctx, 3, bob},
+			},
+			expect: output{
+				n: 2,
+				agg: metricdata.Histogram[N]{
+					Temporality: metricdata.DeltaTemporality,
+					DataPoints: []metricdata.HistogramDataPoint[N]{
+						c.hPt(fltrAlice, 10, 1),
+						c.hPt(fltrBob, 3, 1),
+					},
+				},
+			},
+		},
+		{
+			input: []arg[N]{},
+			// Delta histograms are expected to reset.
+			expect: output{
+				n: 0,
+				agg: metricdata.Histogram[N]{
+					Temporality: metricdata.DeltaTemporality,
+					DataPoints:  []metricdata.HistogramDataPoint[N]{},
+				},
+			},
+		},
+	})
 }
 
-func deltaHistExpecter[N int64 | float64](incr setMap[N]) expectFunc {
+func testCumulativeHist[N int64 | float64](c conf[N]) func(t *testing.T) {
-	h := metricdata.Histogram[N]{Temporality: metricdata.DeltaTemporality}
+	in, out := Builder[N]{
-	return func(m int) metricdata.Aggregation {
+		Temporality: metricdata.CumulativeTemporality,
-		h.DataPoints = make([]metricdata.HistogramDataPoint[N], 0, len(incr))
+		Filter:      attrFltr,
-		for a, v := range incr {
+	}.ExplicitBucketHistogram(histConf, c.noSum)
-			h.DataPoints = append(h.DataPoints, hPoint[N](a, v, uint64(m)))
+	ctx := context.Background()
-		}
+	return test[N](in, out, []teststep[N]{
-		return h
+		{
-	}
+			input: []arg[N]{},
-}
+			expect: output{
-
+				n: 0,
-func cumuHistSummedExpecter[N int64 | float64](incr setMap[N]) expectFunc {
+				agg: metricdata.Histogram[N]{
-	var cycle int
+					Temporality: metricdata.CumulativeTemporality,
-	h := metricdata.Histogram[N]{Temporality: metricdata.CumulativeTemporality}
+					DataPoints:  []metricdata.HistogramDataPoint[N]{},
-	return func(m int) metricdata.Aggregation {
+				},
-		cycle++
+			},
-		h.DataPoints = make([]metricdata.HistogramDataPoint[N], 0, len(incr))
+		},
-		for a, v := range incr {
+		{
-			h.DataPoints = append(h.DataPoints, hPointSummed[N](a, v, uint64(cycle*m)))
+			input: []arg[N]{
-		}
+				{ctx, 2, alice},
-		return h
+				{ctx, 10, bob},
-	}
+				{ctx, 2, alice},
-}
+				{ctx, 2, alice},
-
+				{ctx, 10, bob},
-func cumuHistExpecter[N int64 | float64](incr setMap[N]) expectFunc {
+			},
-	var cycle int
+			expect: output{
-	h := metricdata.Histogram[N]{Temporality: metricdata.CumulativeTemporality}
+				n: 2,
-	return func(m int) metricdata.Aggregation {
+				agg: metricdata.Histogram[N]{
-		cycle++
+					Temporality: metricdata.CumulativeTemporality,
-		h.DataPoints = make([]metricdata.HistogramDataPoint[N], 0, len(incr))
+					DataPoints: []metricdata.HistogramDataPoint[N]{
-		for a, v := range incr {
+						c.hPt(fltrAlice, 2, 3),
-			h.DataPoints = append(h.DataPoints, hPoint[N](a, v, uint64(cycle*m)))
+						c.hPt(fltrBob, 10, 2),
-		}
+					},
-		return h
+				},
-	}
+			},
+		},
+		{
+			input: []arg[N]{
+				{ctx, 2, alice},
+				{ctx, 10, bob},
+			},
+			expect: output{
+				n: 2,
+				agg: metricdata.Histogram[N]{
+					Temporality: metricdata.CumulativeTemporality,
+					DataPoints: []metricdata.HistogramDataPoint[N]{
+						c.hPt(fltrAlice, 2, 4),
+						c.hPt(fltrBob, 10, 3),
+					},
+				},
+			},
+		},
+		{
+			input: []arg[N]{},
+			expect: output{
+				n: 2,
+				agg: metricdata.Histogram[N]{
+					Temporality: metricdata.CumulativeTemporality,
+					DataPoints: []metricdata.HistogramDataPoint[N]{
+						c.hPt(fltrAlice, 2, 4),
+						c.hPt(fltrBob, 10, 3),
+					},
+				},
+			},
+		},
+	})
 }
 
 // hPointSummed returns an HistogramDataPoint that started and ended now with
@@ -190,93 +272,89 @@ func testBucketsSum[N int64 | float64]() func(t *testing.T) {
 	}
 }
 
-func testHistImmutableBounds[N int64 | float64](newA func(aggregation.ExplicitBucketHistogram, bool) aggregator[N], getBounds func(aggregator[N]) []float64) func(t *testing.T) {
+func TestHistogramImmutableBounds(t *testing.T) {
 	b := []float64{0, 1, 2}
 	cpB := make([]float64, len(b))
 	copy(cpB, b)
 
-	a := newA(aggregation.ExplicitBucketHistogram{Boundaries: b}, false)
+	h := newHistogram[int64](aggregation.ExplicitBucketHistogram{Boundaries: b}, false)
-	return func(t *testing.T) {
+	require.Equal(t, cpB, h.bounds)
-		require.Equal(t, cpB, getBounds(a))
 
-		b[0] = 10
+	b[0] = 10
-		assert.Equal(t, cpB, getBounds(a), "modifying the bounds argument should not change the bounds")
+	assert.Equal(t, cpB, h.bounds, "modifying the bounds argument should not change the bounds")
 
-		a.Aggregate(5, alice)
+	h.measure(context.Background(), 5, alice)
-		hdp := a.Aggregation().(metricdata.Histogram[N]).DataPoints[0]
-		hdp.Bounds[1] = 10
-		assert.Equal(t, cpB, getBounds(a), "modifying the Aggregation bounds should not change the bounds")
-	}
-}
 
-func TestHistogramImmutableBounds(t *testing.T) {
+	var data metricdata.Aggregation = metricdata.Histogram[int64]{}
-	t.Run("Delta", testHistImmutableBounds(
+	h.cumulative(&data)
-		newDeltaHistogram[int64],
+	hdp := data.(metricdata.Histogram[int64]).DataPoints[0]
-		func(a aggregator[int64]) []float64 {
+	hdp.Bounds[1] = 10
-			deltaH := a.(*deltaHistogram[int64])
+	assert.Equal(t, cpB, h.bounds, "modifying the Aggregation bounds should not change the bounds")
-			return deltaH.bounds
-		},
-	))
-
-	t.Run("Cumulative", testHistImmutableBounds(
-		newCumulativeHistogram[int64],
-		func(a aggregator[int64]) []float64 {
-			cumuH := a.(*cumulativeHistogram[int64])
-			return cumuH.bounds
-		},
-	))
 }
 
 func TestCumulativeHistogramImutableCounts(t *testing.T) {
-	a := newCumulativeHistogram[int64](histConf, false)
+	h := newHistogram[int64](histConf, false)
-	a.Aggregate(5, alice)
+	h.measure(context.Background(), 5, alice)
-	hdp := a.Aggregation().(metricdata.Histogram[int64]).DataPoints[0]
 
-	cumuH := a.(*cumulativeHistogram[int64])
+	var data metricdata.Aggregation = metricdata.Histogram[int64]{}
-	require.Equal(t, hdp.BucketCounts, cumuH.values[alice].counts)
+	h.cumulative(&data)
+	hdp := data.(metricdata.Histogram[int64]).DataPoints[0]
+
+	require.Equal(t, hdp.BucketCounts, h.values[alice].counts)
 
 	cpCounts := make([]uint64, len(hdp.BucketCounts))
 	copy(cpCounts, hdp.BucketCounts)
 	hdp.BucketCounts[0] = 10
-	assert.Equal(t, cpCounts, cumuH.values[alice].counts, "modifying the Aggregator bucket counts should not change the Aggregator")
+	assert.Equal(t, cpCounts, h.values[alice].counts, "modifying the Aggregator bucket counts should not change the Aggregator")
 }
 
 func TestDeltaHistogramReset(t *testing.T) {
 	t.Cleanup(mockTime(now))
 
-	a := newDeltaHistogram[int64](histConf, false)
+	h := newHistogram[int64](histConf, false)
-	assert.Nil(t, a.Aggregation())
+
+	var data metricdata.Aggregation = metricdata.Histogram[int64]{}
+	require.Equal(t, 0, h.delta(&data))
+	require.Len(t, data.(metricdata.Histogram[int64]).DataPoints, 0)
+
+	h.measure(context.Background(), 1, alice)
 
-	a.Aggregate(1, alice)
 	expect := metricdata.Histogram[int64]{Temporality: metricdata.DeltaTemporality}
 	expect.DataPoints = []metricdata.HistogramDataPoint[int64]{hPointSummed[int64](alice, 1, 1)}
-	metricdatatest.AssertAggregationsEqual(t, expect, a.Aggregation())
+	h.delta(&data)
+	metricdatatest.AssertAggregationsEqual(t, expect, data)
 
 	// The attr set should be forgotten once Aggregations is called.
 	expect.DataPoints = nil
-	assert.Nil(t, a.Aggregation())
+	assert.Equal(t, 0, h.delta(&data))
+	assert.Len(t, data.(metricdata.Histogram[int64]).DataPoints, 0)
 
 	// Aggregating another set should not affect the original (alice).
-	a.Aggregate(1, bob)
+	h.measure(context.Background(), 1, bob)
 	expect.DataPoints = []metricdata.HistogramDataPoint[int64]{hPointSummed[int64](bob, 1, 1)}
-	metricdatatest.AssertAggregationsEqual(t, expect, a.Aggregation())
+	h.delta(&data)
-}
+	metricdatatest.AssertAggregationsEqual(t, expect, data)
-
-func TestEmptyHistogramNilAggregation(t *testing.T) {
-	assert.Nil(t, newCumulativeHistogram[int64](histConf, false).Aggregation())
-	assert.Nil(t, newCumulativeHistogram[float64](histConf, false).Aggregation())
-	assert.Nil(t, newDeltaHistogram[int64](histConf, false).Aggregation())
-	assert.Nil(t, newDeltaHistogram[float64](histConf, false).Aggregation())
 }
 
 func BenchmarkHistogram(b *testing.B) {
-	b.Run("Int64", benchmarkHistogram[int64])
+	b.Run("Int64/Cumulative", benchmarkAggregate(func() (Measure[int64], ComputeAggregation) {
-	b.Run("Float64", benchmarkHistogram[float64])
+		return Builder[int64]{
-}
+			Temporality: metricdata.CumulativeTemporality,
-
+		}.ExplicitBucketHistogram(histConf, false)
-func benchmarkHistogram[N int64 | float64](b *testing.B) {
+	}))
-	factory := func() aggregator[N] { return newDeltaHistogram[N](histConf, false) }
+	b.Run("Int64/Delta", benchmarkAggregate(func() (Measure[int64], ComputeAggregation) {
-	b.Run("Delta", benchmarkAggregator(factory))
+		return Builder[int64]{
-	factory = func() aggregator[N] { return newCumulativeHistogram[N](histConf, false) }
+			Temporality: metricdata.DeltaTemporality,
-	b.Run("Cumulative", benchmarkAggregator(factory))
+		}.ExplicitBucketHistogram(histConf, false)
+	}))
+	b.Run("Float64/Cumulative", benchmarkAggregate(func() (Measure[float64], ComputeAggregation) {
+		return Builder[float64]{
+			Temporality: metricdata.CumulativeTemporality,
+		}.ExplicitBucketHistogram(histConf, false)
+	}))
+	b.Run("Float64/Delta", benchmarkAggregate(func() (Measure[float64], ComputeAggregation) {
+		return Builder[float64]{
+			Temporality: metricdata.DeltaTemporality,
+		}.ExplicitBucketHistogram(histConf, false)
+	}))
 }