Merge branch 'main' into simplify_filtered

CHANGELOG.md

@@ -32,11 +32,14 @@ This project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.htm
   This change is made to ensure compatibility with the OpenTelemetry specification. (#4288)
 - If an attribute set is omitted from an async callback, the previous value will no longer be exported. (#4290)
 - If an attribute set is Observed multiple times in an async callback, the values will be summed instead of the last observation winning. (#4289)
+- Allow the explicit bucket histogram aggregation to be used for the up-down counter, observable counter, observable up-down counter, and observable gauge in the `go.opentelemetry.io/otel/sdk/metric` package. (#4332)
+- Restrict `Meter`s in `go.opentelemetry.io/otel/sdk/metric` to only register and collect instruments it created. (#4333)
 
 ### Fixed
 
 - Correctly format log messages from the `go.opentelemetry.io/otel/exporters/zipkin` exporter. (#4143)
 - Log an error for calls to `NewView` in `go.opentelemetry.io/otel/sdk/metric` that have empty criteria. (#4307)
+- Fix `resource.WithHostID()` to not set an empty `host.id`. (#4317)
 
 ## [1.16.0/0.39.0] 2023-05-18
 

sdk/metric/instrument.go

@@ -277,9 +277,9 @@ var _ metric.Float64ObservableCounter = float64Observable{}
 var _ metric.Float64ObservableUpDownCounter = float64Observable{}
 var _ metric.Float64ObservableGauge = float64Observable{}
 
-func newFloat64Observable(scope instrumentation.Scope, kind InstrumentKind, name, desc, u string, meas []aggregate.Measure[float64]) float64Observable {
+func newFloat64Observable(m *meter, kind InstrumentKind, name, desc, u string, meas []aggregate.Measure[float64]) float64Observable {
 	return float64Observable{
-		observable: newObservable(scope, kind, name, desc, u, meas),
+		observable: newObservable(m, kind, name, desc, u, meas),
 	}
 }
 
@@ -296,28 +296,30 @@ var _ metric.Int64ObservableCounter = int64Observable{}
 var _ metric.Int64ObservableUpDownCounter = int64Observable{}
 var _ metric.Int64ObservableGauge = int64Observable{}
 
-func newInt64Observable(scope instrumentation.Scope, kind InstrumentKind, name, desc, u string, meas []aggregate.Measure[int64]) int64Observable {
+func newInt64Observable(m *meter, kind InstrumentKind, name, desc, u string, meas []aggregate.Measure[int64]) int64Observable {
 	return int64Observable{
-		observable: newObservable(scope, kind, name, desc, u, meas),
+		observable: newObservable(m, kind, name, desc, u, meas),
 	}
 }
 
 type observable[N int64 | float64] struct {
 	metric.Observable
 	observablID[N]
 
+	meter    *meter
 	measures []aggregate.Measure[N]
 }
 
-func newObservable[N int64 | float64](scope instrumentation.Scope, kind InstrumentKind, name, desc, u string, meas []aggregate.Measure[N]) *observable[N] {
+func newObservable[N int64 | float64](m *meter, kind InstrumentKind, name, desc, u string, meas []aggregate.Measure[N]) *observable[N] {
 	return &observable[N]{
 		observablID: observablID[N]{
 			name:        name,
 			description: desc,
 			kind:        kind,
 			unit:        u,
-			scope:       scope,
+			scope:       m.scope,
 		},
+		meter:    m,
 		measures: meas,
 	}
 }
@@ -335,16 +337,16 @@ var errEmptyAgg = errors.New("no aggregators for observable instrument")
 // and nil if it should. An errEmptyAgg error is returned if o is effectively a
 // no-op because it does not have any aggregators. Also, an error is returned
 // if scope defines a Meter other than the one o was created by.
-func (o *observable[N]) registerable(scope instrumentation.Scope) error {
+func (o *observable[N]) registerable(m *meter) error {
 	if len(o.measures) == 0 {
 		return errEmptyAgg
 	}
-	if scope != o.scope {
+	if m != o.meter {
 		return fmt.Errorf(
 			"invalid registration: observable %q from Meter %q, registered with Meter %q",
 			o.name,
 			o.scope.Name,
-			scope.Name,
+			m.scope.Name,
 		)
 	}
 	return nil

sdk/metric/internal/aggregate/aggregate.go

@@ -109,13 +109,13 @@ 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) (Measure[N], ComputeAggregation) {
+func (b Builder[N]) ExplicitBucketHistogram(cfg aggregation.ExplicitBucketHistogram, noSum bool) (Measure[N], ComputeAggregation) {
 	var h aggregator[N]
 	switch b.Temporality {
 	case metricdata.DeltaTemporality:
-		h = newDeltaHistogram[N](cfg)
+		h = newDeltaHistogram[N](cfg, noSum)
 	default:
-		h = newCumulativeHistogram[N](cfg)
+		h = newCumulativeHistogram[N](cfg, noSum)
 	}
 	return b.input(h), func(dest *metricdata.Aggregation) int {
 		// TODO (#4220): optimize memory reuse here.

sdk/metric/internal/aggregate/histogram.go

@@ -27,7 +27,7 @@ import (
 type buckets[N int64 | float64] struct {
 	counts   []uint64
 	count    uint64
-	sum      N
+	total    N
 	min, max N
 }
 
@@ -36,10 +36,11 @@ func newBuckets[N int64 | float64](n int) *buckets[N] {
 	return &buckets[N]{counts: make([]uint64, n)}
 }
 
+func (b *buckets[N]) sum(value N) { b.total += value }
+
 func (b *buckets[N]) bin(idx int, value N) {
 	b.counts[idx]++
 	b.count++
-	b.sum += value
 	if value < b.min {
 		b.min = value
 	} else if value > b.max {
@@ -50,13 +51,14 @@ func (b *buckets[N]) bin(idx int, value N) {
 // histValues summarizes a set of measurements as an histValues with
 // explicitly defined buckets.
 type histValues[N int64 | float64] struct {
+	noSum  bool
 	bounds []float64
 
 	values   map[attribute.Set]*buckets[N]
 	valuesMu sync.Mutex
 }
 
-func newHistValues[N int64 | float64](bounds []float64) *histValues[N] {
+func newHistValues[N int64 | float64](bounds []float64, noSum bool) *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
@@ -65,6 +67,7 @@ func newHistValues[N int64 | float64](bounds []float64) *histValues[N] {
 	copy(b, bounds)
 	sort.Float64s(b)
 	return &histValues[N]{
+		noSum:  noSum,
 		bounds: b,
 		values: make(map[attribute.Set]*buckets[N]),
 	}
@@ -98,6 +101,9 @@ func (s *histValues[N]) Aggregate(value N, attr attribute.Set) {
 		s.values[attr] = b
 	}
 	b.bin(idx, value)
+	if !s.noSum {
+		b.sum(value)
+	}
 }
 
 // newDeltaHistogram returns an Aggregator that summarizes a set of
@@ -107,9 +113,9 @@ func (s *histValues[N]) Aggregate(value N, attr attribute.Set) {
 // 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) aggregator[N] {
+func newDeltaHistogram[N int64 | float64](cfg aggregation.ExplicitBucketHistogram, noSum bool) aggregator[N] {
 	return &deltaHistogram[N]{
-		histValues: newHistValues[N](cfg.Boundaries),
+		histValues: newHistValues[N](cfg.Boundaries, noSum),
 		noMinMax:   cfg.NoMinMax,
 		start:      now(),
 	}
@@ -148,7 +154,9 @@ func (s *deltaHistogram[N]) Aggregation() metricdata.Aggregation {
 			Count:        b.count,
 			Bounds:       bounds,
 			BucketCounts: b.counts,
-			Sum:          b.sum,
+		}
+		if !s.noSum {
+			hdp.Sum = b.total
 		}
 		if !s.noMinMax {
 			hdp.Min = metricdata.NewExtrema(b.min)
@@ -170,9 +178,9 @@ func (s *deltaHistogram[N]) Aggregation() metricdata.Aggregation {
 // 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) aggregator[N] {
+func newCumulativeHistogram[N int64 | float64](cfg aggregation.ExplicitBucketHistogram, noSum bool) aggregator[N] {
 	return &cumulativeHistogram[N]{
-		histValues: newHistValues[N](cfg.Boundaries),
+		histValues: newHistValues[N](cfg.Boundaries, noSum),
 		noMinMax:   cfg.NoMinMax,
 		start:      now(),
 	}
@@ -219,7 +227,9 @@ func (s *cumulativeHistogram[N]) Aggregation() metricdata.Aggregation {
 			Count:        b.count,
 			Bounds:       bounds,
 			BucketCounts: counts,
-			Sum:          b.sum,
+		}
+		if !s.noSum {
+			hdp.Sum = b.total
 		}
 		if !s.noMinMax {
 			hdp.Min = metricdata.NewExtrema(b.min)