// Copyright The OpenTelemetry Authors // SPDX-License-Identifier: Apache-2.0 package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate" import ( "context" "sort" "testing" "time" "github.com/stretchr/testify/assert" "github.com/stretchr/testify/require" "go.opentelemetry.io/otel/attribute" "go.opentelemetry.io/otel/sdk/metric/metricdata" "go.opentelemetry.io/otel/sdk/metric/metricdata/metricdatatest" ) var ( bounds = []float64{1, 5} noMinMax = false ) func TestHistogram(t *testing.T) { c := new(clock) t.Cleanup(c.Register()) t.Run("Int64/Delta/Sum", testDeltaHist[int64](conf[int64]{hPt: hPointSummed[int64]})) c.Reset() t.Run("Int64/Delta/NoSum", testDeltaHist[int64](conf[int64]{noSum: true, hPt: hPoint[int64]})) c.Reset() t.Run("Float64/Delta/Sum", testDeltaHist[float64](conf[float64]{hPt: hPointSummed[float64]})) c.Reset() t.Run("Float64/Delta/NoSum", testDeltaHist[float64](conf[float64]{noSum: true, hPt: hPoint[float64]})) c.Reset() t.Run("Int64/Cumulative/Sum", testCumulativeHist[int64](conf[int64]{hPt: hPointSummed[int64]})) c.Reset() t.Run("Int64/Cumulative/NoSum", testCumulativeHist[int64](conf[int64]{noSum: true, hPt: hPoint[int64]})) c.Reset() t.Run("Float64/Cumulative/Sum", testCumulativeHist[float64](conf[float64]{hPt: hPointSummed[float64]})) c.Reset() t.Run("Float64/Cumulative/NoSum", testCumulativeHist[float64](conf[float64]{noSum: true, hPt: hPoint[float64]})) } type conf[N int64 | float64] struct { noSum bool hPt func(attribute.Set, N, uint64, time.Time, time.Time) metricdata.HistogramDataPoint[N] } func testDeltaHist[N int64 | float64](c conf[N]) func(t *testing.T) { in, out := Builder[N]{ Temporality: metricdata.DeltaTemporality, Filter: attrFltr, AggregationLimit: 3, }.ExplicitBucketHistogram(bounds, noMinMax, c.noSum) ctx := context.Background() return test[N](in, out, []teststep[N]{ { 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, y2kPlus(1), y2kPlus(2)), c.hPt(fltrBob, 10, 2, y2kPlus(1), y2kPlus(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, y2kPlus(2), y2kPlus(3)), c.hPt(fltrBob, 3, 1, y2kPlus(2), y2kPlus(3)), }, }, }, }, { input: []arg[N]{}, // Delta histograms are expected to reset. expect: output{ n: 0, agg: metricdata.Histogram[N]{ Temporality: metricdata.DeltaTemporality, DataPoints: []metricdata.HistogramDataPoint[N]{}, }, }, }, { input: []arg[N]{ {ctx, 1, alice}, {ctx, 1, bob}, // These will exceed cardinality limit. {ctx, 1, carol}, {ctx, 1, dave}, }, expect: output{ n: 3, agg: metricdata.Histogram[N]{ Temporality: metricdata.DeltaTemporality, DataPoints: []metricdata.HistogramDataPoint[N]{ c.hPt(fltrAlice, 1, 1, y2kPlus(4), y2kPlus(5)), c.hPt(fltrBob, 1, 1, y2kPlus(4), y2kPlus(5)), c.hPt(overflowSet, 1, 2, y2kPlus(4), y2kPlus(5)), }, }, }, }, }) } func testCumulativeHist[N int64 | float64](c conf[N]) func(t *testing.T) { in, out := Builder[N]{ Temporality: metricdata.CumulativeTemporality, Filter: attrFltr, AggregationLimit: 3, }.ExplicitBucketHistogram(bounds, noMinMax, c.noSum) ctx := context.Background() return test[N](in, out, []teststep[N]{ { input: []arg[N]{}, expect: output{ n: 0, agg: metricdata.Histogram[N]{ Temporality: metricdata.CumulativeTemporality, 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.CumulativeTemporality, DataPoints: []metricdata.HistogramDataPoint[N]{ c.hPt(fltrAlice, 2, 3, y2kPlus(0), y2kPlus(2)), c.hPt(fltrBob, 10, 2, y2kPlus(0), y2kPlus(2)), }, }, }, }, { 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, y2kPlus(0), y2kPlus(3)), c.hPt(fltrBob, 10, 3, y2kPlus(0), y2kPlus(3)), }, }, }, }, { input: []arg[N]{}, expect: output{ n: 2, agg: metricdata.Histogram[N]{ Temporality: metricdata.CumulativeTemporality, DataPoints: []metricdata.HistogramDataPoint[N]{ c.hPt(fltrAlice, 2, 4, y2kPlus(0), y2kPlus(4)), c.hPt(fltrBob, 10, 3, y2kPlus(0), y2kPlus(4)), }, }, }, }, { input: []arg[N]{ // These will exceed cardinality limit. {ctx, 1, carol}, {ctx, 1, dave}, }, expect: output{ n: 3, agg: metricdata.Histogram[N]{ Temporality: metricdata.CumulativeTemporality, DataPoints: []metricdata.HistogramDataPoint[N]{ c.hPt(fltrAlice, 2, 4, y2kPlus(0), y2kPlus(5)), c.hPt(fltrBob, 10, 3, y2kPlus(0), y2kPlus(5)), c.hPt(overflowSet, 1, 2, y2kPlus(0), y2kPlus(5)), }, }, }, }, }) } // hPointSummed returns an HistogramDataPoint that started and ended now with // multi number of measurements values v. It includes a min and max (set to v). func hPointSummed[N int64 | float64](a attribute.Set, v N, multi uint64, start, t time.Time) metricdata.HistogramDataPoint[N] { idx := sort.SearchFloat64s(bounds, float64(v)) counts := make([]uint64, len(bounds)+1) counts[idx] += multi return metricdata.HistogramDataPoint[N]{ Attributes: a, StartTime: start, Time: t, Count: multi, Bounds: bounds, BucketCounts: counts, Min: metricdata.NewExtrema(v), Max: metricdata.NewExtrema(v), Sum: v * N(multi), } } // hPoint returns an HistogramDataPoint that started and ended now with multi // number of measurements values v. It includes a min and max (set to v). func hPoint[N int64 | float64](a attribute.Set, v N, multi uint64, start, t time.Time) metricdata.HistogramDataPoint[N] { idx := sort.SearchFloat64s(bounds, float64(v)) counts := make([]uint64, len(bounds)+1) counts[idx] += multi return metricdata.HistogramDataPoint[N]{ Attributes: a, StartTime: start, Time: t, Count: multi, Bounds: bounds, BucketCounts: counts, Min: metricdata.NewExtrema(v), Max: metricdata.NewExtrema(v), } } func TestBucketsBin(t *testing.T) { t.Run("Int64", testBucketsBin[int64]()) t.Run("Float64", testBucketsBin[float64]()) } func testBucketsBin[N int64 | float64]() func(t *testing.T) { return func(t *testing.T) { b := newBuckets[N](alice, 3) assertB := func(counts []uint64, count uint64, min, max N) { t.Helper() assert.Equal(t, counts, b.counts) assert.Equal(t, count, b.count) assert.Equal(t, min, b.min) assert.Equal(t, max, b.max) } assertB([]uint64{0, 0, 0}, 0, 0, 0) b.bin(1, 2) assertB([]uint64{0, 1, 0}, 1, 0, 2) b.bin(0, -1) assertB([]uint64{1, 1, 0}, 2, -1, 2) } } func TestBucketsSum(t *testing.T) { t.Run("Int64", testBucketsSum[int64]()) t.Run("Float64", testBucketsSum[float64]()) } func testBucketsSum[N int64 | float64]() func(t *testing.T) { return func(t *testing.T) { b := newBuckets[N](alice, 3) var want N assert.Equal(t, want, b.total) b.sum(2) want = 2 assert.Equal(t, want, b.total) b.sum(-1) want = 1 assert.Equal(t, want, b.total) } } func TestHistogramImmutableBounds(t *testing.T) { b := []float64{0, 1, 2} cpB := make([]float64, len(b)) copy(cpB, b) h := newHistogram[int64](b, false, false, 0, dropExemplars[int64]) require.Equal(t, cpB, h.bounds) b[0] = 10 assert.Equal(t, cpB, h.bounds, "modifying the bounds argument should not change the bounds") h.measure(context.Background(), 5, alice, nil) var data metricdata.Aggregation = metricdata.Histogram[int64]{} h.cumulative(&data) hdp := data.(metricdata.Histogram[int64]).DataPoints[0] hdp.Bounds[1] = 10 assert.Equal(t, cpB, h.bounds, "modifying the Aggregation bounds should not change the bounds") } func TestCumulativeHistogramImutableCounts(t *testing.T) { h := newHistogram[int64](bounds, noMinMax, false, 0, dropExemplars[int64]) h.measure(context.Background(), 5, alice, nil) var data metricdata.Aggregation = metricdata.Histogram[int64]{} h.cumulative(&data) hdp := data.(metricdata.Histogram[int64]).DataPoints[0] require.Equal(t, hdp.BucketCounts, h.values[alice.Equivalent()].counts) cpCounts := make([]uint64, len(hdp.BucketCounts)) copy(cpCounts, hdp.BucketCounts) hdp.BucketCounts[0] = 10 assert.Equal(t, cpCounts, h.values[alice.Equivalent()].counts, "modifying the Aggregator bucket counts should not change the Aggregator") } func TestDeltaHistogramReset(t *testing.T) { orig := now now = func() time.Time { return y2k } t.Cleanup(func() { now = orig }) h := newHistogram[int64](bounds, noMinMax, false, 0, dropExemplars[int64]) 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, nil) expect := metricdata.Histogram[int64]{Temporality: metricdata.DeltaTemporality} expect.DataPoints = []metricdata.HistogramDataPoint[int64]{hPointSummed[int64](alice, 1, 1, now(), now())} h.delta(&data) metricdatatest.AssertAggregationsEqual(t, expect, data) // The attr set should be forgotten once Aggregations is called. expect.DataPoints = nil 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). h.measure(context.Background(), 1, bob, nil) expect.DataPoints = []metricdata.HistogramDataPoint[int64]{hPointSummed[int64](bob, 1, 1, now(), now())} h.delta(&data) metricdatatest.AssertAggregationsEqual(t, expect, data) } func BenchmarkHistogram(b *testing.B) { b.Run("Int64/Cumulative", benchmarkAggregate(func() (Measure[int64], ComputeAggregation) { return Builder[int64]{ Temporality: metricdata.CumulativeTemporality, }.ExplicitBucketHistogram(bounds, noMinMax, false) })) b.Run("Int64/Delta", benchmarkAggregate(func() (Measure[int64], ComputeAggregation) { return Builder[int64]{ Temporality: metricdata.DeltaTemporality, }.ExplicitBucketHistogram(bounds, noMinMax, false) })) b.Run("Float64/Cumulative", benchmarkAggregate(func() (Measure[float64], ComputeAggregation) { return Builder[float64]{ Temporality: metricdata.CumulativeTemporality, }.ExplicitBucketHistogram(bounds, noMinMax, false) })) b.Run("Float64/Delta", benchmarkAggregate(func() (Measure[float64], ComputeAggregation) { return Builder[float64]{ Temporality: metricdata.DeltaTemporality, }.ExplicitBucketHistogram(bounds, noMinMax, false) })) }