Calculate delta sums for delta async counter/up-down-counter types

CHANGELOG.md

@@ -11,6 +11,7 @@ This project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.htm
 ### Fixed
 
 - The `go.opentelemetry.io/otel/exporters/prometheus` exporter fixes duplicated `_total` suffixes. (#3369)
+- Asynchronous counters (`Counter` and `UpDownCounter`) from the metric SDK now produce delta sums when configured with delta temporality. (#3398)
 
 ## [1.11.1/0.33.0] 2022-10-19
 

metric/instrument/asyncfloat64/asyncfloat64.go

@@ -35,8 +35,8 @@ type InstrumentProvider interface {
 
 // Counter is an instrument that records increasing values.
 type Counter interface {
-	// Observe records the state of the instrument to be x. The value of x is
-	// assumed to be the exact Counter value to record.
+	// Observe records the state of the instrument to be x. Implementations
+	// will assume x to be the cumulative sum of the count.
 	//
 	// It is only valid to call this within a callback. If called outside of the
 	// registered callback it should have no effect on the instrument, and an
@@ -48,8 +48,8 @@ type Counter interface {
 
 // UpDownCounter is an instrument that records increasing or decreasing values.
 type UpDownCounter interface {
-	// Observe records the state of the instrument to be x. The value of x is
-	// assumed to be the exact UpDownCounter value to record.
+	// Observe records the state of the instrument to be x. Implementations
+	// will assume x to be the cumulative sum of the count.
 	//
 	// It is only valid to call this within a callback. If called outside of the
 	// registered callback it should have no effect on the instrument, and an

metric/instrument/asyncint64/asyncint64.go

@@ -35,8 +35,8 @@ type InstrumentProvider interface {
 
 // Counter is an instrument that records increasing values.
 type Counter interface {
-	// Observe records the state of the instrument to be x. The value of x is
-	// assumed to be the exact Counter value to record.
+	// Observe records the state of the instrument to be x. Implementations
+	// will assume x to be the cumulative sum of the count.
 	//
 	// It is only valid to call this within a callback. If called outside of the
 	// registered callback it should have no effect on the instrument, and an
@@ -48,8 +48,8 @@ type Counter interface {
 
 // UpDownCounter is an instrument that records increasing or decreasing values.
 type UpDownCounter interface {
-	// Observe records the state of the instrument to be x. The value of x is
-	// assumed to be the exact UpDownCounter value to record.
+	// Observe records the state of the instrument to be x. Implementations
+	// will assume x to be the cumulative sum of the count.
 	//
 	// It is only valid to call this within a callback. If called outside of the
 	// registered callback it should have no effect on the instrument, and an

sdk/metric/internal/sum.go

@@ -177,7 +177,66 @@ func (s *cumulativeSum[N]) Aggregation() metricdata.Aggregation {
 // The output Aggregation will report recorded values as delta temporality. It
 // is up to the caller to ensure this is accurate.
 func NewPrecomputedDeltaSum[N int64 | float64](monotonic bool) Aggregator[N] {
-	return &precomputedSum[N]{settableSum: newDeltaSum[N](monotonic)}
+	return &precomputedDeltaSum[N]{
+		recorded:  make(map[attribute.Set]N),
+		reported:  make(map[attribute.Set]N),
+		monotonic: monotonic,
+		start:     now(),
+	}
+}
+
+// precomputedDeltaSum summarizes a set of measurements recorded over all
+// aggregation cycles as the delta arithmetic sum.
+type precomputedDeltaSum[N int64 | float64] struct {
+	sync.Mutex
+	recorded map[attribute.Set]N
+	reported map[attribute.Set]N
+
+	monotonic bool
+	start     time.Time
+}
+
+// Aggregate records value as a cumulative sum for attr.
+func (s *precomputedDeltaSum[N]) Aggregate(value N, attr attribute.Set) {
+	s.Lock()
+	s.recorded[attr] = value
+	s.Unlock()
+}
+
+func (s *precomputedDeltaSum[N]) Aggregation() metricdata.Aggregation {
+	out := metricdata.Sum[N]{
+		Temporality: metricdata.DeltaTemporality,
+		IsMonotonic: s.monotonic,
+	}
+
+	s.Lock()
+	defer s.Unlock()
+
+	if len(s.recorded) == 0 {
+		return out
+	}
+
+	t := now()
+	out.DataPoints = make([]metricdata.DataPoint[N], 0, len(s.recorded))
+	for attr, recorded := range s.recorded {
+		value := recorded - s.reported[attr]
+		out.DataPoints = append(out.DataPoints, metricdata.DataPoint[N]{
+			Attributes: attr,
+			StartTime:  s.start,
+			Time:       t,
+			Value:      value,
+		})
+		if value != 0 {
+			s.reported[attr] = recorded
+		}
+		// 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.
+	}
+	// The delta collection cycle resets.
+	s.start = t
+	return out
 }
 
 // NewPrecomputedCumulativeSum returns an Aggregator that summarizes a set of
@@ -191,21 +250,16 @@ func NewPrecomputedDeltaSum[N int64 | float64](monotonic bool) Aggregator[N] {
 // The output Aggregation will report recorded values as cumulative
 // temporality. It is up to the caller to ensure this is accurate.
 func NewPrecomputedCumulativeSum[N int64 | float64](monotonic bool) Aggregator[N] {
-	return &precomputedSum[N]{settableSum: newCumulativeSum[N](monotonic)}
-}
-
-type settableSum[N int64 | float64] interface {
-	set(value N, attr attribute.Set)
-	Aggregation() metricdata.Aggregation
+	return &precomputedSum[N]{newCumulativeSum[N](monotonic)}
 }
 
 // precomputedSum summarizes a set of measurements recorded over all
-// aggregation cycles directly as an arithmetic sum.
+// aggregation cycles directly as the cumulative arithmetic sum.
 type precomputedSum[N int64 | float64] struct {
-	settableSum[N]
+	*cumulativeSum[N]
 }
 
-// Aggregate records value directly as a sum for attr.
+// Aggregate records value as a cumulative sum for attr.
 func (s *precomputedSum[N]) Aggregate(value N, attr attribute.Set) {
 	s.set(value, attr)
 }

sdk/metric/internal/sum_test.go

@@ -56,22 +56,22 @@ func testSum[N int64 | float64](t *testing.T) {
 	})
 
 	t.Run("PreComputedDelta", func(t *testing.T) {
-		incr, mono, temp := monoIncr, true, metricdata.DeltaTemporality
-		eFunc := preExpecter[N](incr, mono, temp)
+		incr, mono := monoIncr, true
+		eFunc := preDeltaExpecter[N](incr, mono)
 		t.Run("Monotonic", tester.Run(NewPrecomputedDeltaSum[N](mono), incr, eFunc))
 
 		incr, mono = nonMonoIncr, false
-		eFunc = preExpecter[N](incr, mono, temp)
+		eFunc = preDeltaExpecter[N](incr, mono)
 		t.Run("NonMonotonic", tester.Run(NewPrecomputedDeltaSum[N](mono), incr, eFunc))
 	})
 
 	t.Run("PreComputedCumulative", func(t *testing.T) {
-		incr, mono, temp := monoIncr, true, metricdata.CumulativeTemporality
-		eFunc := preExpecter[N](incr, mono, temp)
+		incr, mono := monoIncr, true
+		eFunc := preCumuExpecter[N](incr, mono)
 		t.Run("Monotonic", tester.Run(NewPrecomputedCumulativeSum[N](mono), incr, eFunc))
 
 		incr, mono = nonMonoIncr, false
-		eFunc = preExpecter[N](incr, mono, temp)
+		eFunc = preCumuExpecter[N](incr, mono)
 		t.Run("NonMonotonic", tester.Run(NewPrecomputedCumulativeSum[N](mono), incr, eFunc))
 	})
 }
@@ -100,8 +100,22 @@ func cumuExpecter[N int64 | float64](incr setMap, mono bool) expectFunc {
 	}
 }
 
-func preExpecter[N int64 | float64](incr setMap, mono bool, temp metricdata.Temporality) expectFunc {
-	sum := metricdata.Sum[N]{Temporality: temp, IsMonotonic: mono}
+func preDeltaExpecter[N int64 | float64](incr setMap, mono bool) expectFunc {
+	sum := metricdata.Sum[N]{Temporality: metricdata.DeltaTemporality, IsMonotonic: mono}
+	last := make(map[attribute.Set]N)
+	return func(int) metricdata.Aggregation {
+		sum.DataPoints = make([]metricdata.DataPoint[N], 0, len(incr))
+		for a, v := range incr {
+			l := last[a]
+			sum.DataPoints = append(sum.DataPoints, point(a, N(v)-l))
+			last[a] = N(v)
+		}
+		return sum
+	}
+}
+
+func preCumuExpecter[N int64 | float64](incr setMap, mono bool) expectFunc {
+	sum := metricdata.Sum[N]{Temporality: metricdata.CumulativeTemporality, IsMonotonic: mono}
 	return func(int) metricdata.Aggregation {
 		sum.DataPoints = make([]metricdata.DataPoint[N], 0, len(incr))
 		for a, v := range incr {