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3429e15b9a
Topic: #5249
This reverts commit 8041156518 (PR: #5899)
due to the performance degradation found by Benchmarks CI
https://github.com/open-telemetry/opentelemetry-go/actions/runs/11447364022/job/31848519243
Here is the benchmark test on my machine:
```
goos: darwin
goarch: arm64
pkg: go.opentelemetry.io/otel/sdk/metric
│ old.txt │ new.txt │
│ sec/op │ sec/op vs base │
Instrument/instrumentImpl/aggregate-10 3.378µ ± 3% 49.366µ ± 1% +1361.40% (p=0.000 n=10)
Instrument/observable/observe-10 2.288µ ± 2% 37.791µ ± 1% +1551.73% (p=0.000 n=10)
geomean 2.780µ 43.19µ +1453.65%
│ old.txt │ new.txt │
│ B/op │ B/op vs base │
Instrument/instrumentImpl/aggregate-10 1.245Ki ± 1% 22.363Ki ± 0% +1696.08% (p=0.000 n=10)
Instrument/observable/observe-10 823.0 ± 1% 17432.5 ± 0% +2018.17% (p=0.000 n=10)
geomean 1.000Ki 19.51Ki +1850.48%
│ old.txt │ new.txt │
│ allocs/op │ allocs/op vs base │
Instrument/instrumentImpl/aggregate-10 1.000 ± 0% 21.000 ± 0% +2000.00% (p=0.000 n=10)
Instrument/observable/observe-10 1.000 ± 0% 16.000 ± 0% +1500.00% (p=0.000 n=10)
```
587 lines
13 KiB
Go
587 lines
13 KiB
Go
// Copyright The OpenTelemetry Authors
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// SPDX-License-Identifier: Apache-2.0
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package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate"
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import (
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"context"
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"testing"
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"go.opentelemetry.io/otel/sdk/metric/metricdata"
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)
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func TestSum(t *testing.T) {
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c := new(clock)
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t.Cleanup(c.Register())
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t.Run("Int64/DeltaSum", testDeltaSum[int64]())
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c.Reset()
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t.Run("Float64/DeltaSum", testDeltaSum[float64]())
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c.Reset()
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t.Run("Int64/CumulativeSum", testCumulativeSum[int64]())
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c.Reset()
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t.Run("Float64/CumulativeSum", testCumulativeSum[float64]())
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c.Reset()
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t.Run("Int64/DeltaPrecomputedSum", testDeltaPrecomputedSum[int64]())
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c.Reset()
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t.Run("Float64/DeltaPrecomputedSum", testDeltaPrecomputedSum[float64]())
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c.Reset()
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t.Run("Int64/CumulativePrecomputedSum", testCumulativePrecomputedSum[int64]())
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c.Reset()
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t.Run("Float64/CumulativePrecomputedSum", testCumulativePrecomputedSum[float64]())
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}
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func testDeltaSum[N int64 | float64]() func(t *testing.T) {
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mono := false
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in, out := Builder[N]{
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Temporality: metricdata.DeltaTemporality,
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Filter: attrFltr,
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AggregationLimit: 3,
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}.Sum(mono)
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ctx := context.Background()
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return test[N](in, out, []teststep[N]{
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{
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input: []arg[N]{},
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expect: output{
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n: 0,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.DataPoint[N]{},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 1, alice},
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{ctx, -1, bob},
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{ctx, 1, alice},
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{ctx, 2, alice},
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{ctx, -10, bob},
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},
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expect: output{
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n: 2,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(1),
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Time: y2kPlus(2),
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Value: 4,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(1),
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Time: y2kPlus(2),
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Value: -11,
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},
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},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 10, alice},
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{ctx, 3, bob},
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},
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expect: output{
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n: 2,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(2),
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Time: y2kPlus(3),
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Value: 10,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(2),
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Time: y2kPlus(3),
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Value: 3,
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},
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},
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},
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},
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},
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{
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input: []arg[N]{},
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// Delta sums are expected to reset.
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expect: output{
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n: 0,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.DataPoint[N]{},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 1, alice},
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{ctx, 1, bob},
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// These will exceed cardinality limit.
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{ctx, 1, carol},
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{ctx, 1, dave},
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},
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expect: output{
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n: 3,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(4),
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Time: y2kPlus(5),
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Value: 1,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(4),
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Time: y2kPlus(5),
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Value: 1,
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},
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{
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Attributes: overflowSet,
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StartTime: y2kPlus(4),
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Time: y2kPlus(5),
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Value: 2,
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},
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},
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},
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},
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},
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})
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}
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func testCumulativeSum[N int64 | float64]() func(t *testing.T) {
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mono := false
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in, out := Builder[N]{
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Temporality: metricdata.CumulativeTemporality,
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Filter: attrFltr,
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AggregationLimit: 3,
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}.Sum(mono)
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ctx := context.Background()
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return test[N](in, out, []teststep[N]{
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{
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input: []arg[N]{},
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expect: output{
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n: 0,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.DataPoint[N]{},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 1, alice},
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{ctx, -1, bob},
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{ctx, 1, alice},
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{ctx, 2, alice},
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{ctx, -10, bob},
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},
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expect: output{
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n: 2,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(0),
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Time: y2kPlus(2),
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Value: 4,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(0),
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Time: y2kPlus(2),
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Value: -11,
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},
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},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 10, alice},
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{ctx, 3, bob},
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},
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expect: output{
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n: 2,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(0),
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Time: y2kPlus(3),
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Value: 14,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(0),
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Time: y2kPlus(3),
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Value: -8,
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},
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},
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},
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},
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},
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{
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input: []arg[N]{
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// These will exceed cardinality limit.
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{ctx, 1, carol},
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{ctx, 1, dave},
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},
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expect: output{
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n: 3,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(0),
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Time: y2kPlus(4),
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Value: 14,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(0),
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Time: y2kPlus(4),
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Value: -8,
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},
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{
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Attributes: overflowSet,
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StartTime: y2kPlus(0),
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Time: y2kPlus(4),
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Value: 2,
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},
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},
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},
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},
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},
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})
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}
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func testDeltaPrecomputedSum[N int64 | float64]() func(t *testing.T) {
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mono := false
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in, out := Builder[N]{
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Temporality: metricdata.DeltaTemporality,
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Filter: attrFltr,
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AggregationLimit: 3,
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}.PrecomputedSum(mono)
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ctx := context.Background()
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return test[N](in, out, []teststep[N]{
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{
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input: []arg[N]{},
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expect: output{
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n: 0,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.DataPoint[N]{},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 1, alice},
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{ctx, -1, bob},
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{ctx, 1, fltrAlice},
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{ctx, 2, alice},
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{ctx, -10, bob},
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},
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expect: output{
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n: 2,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(1),
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Time: y2kPlus(2),
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Value: 4,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(1),
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Time: y2kPlus(2),
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Value: -11,
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},
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},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 1, fltrAlice},
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{ctx, 10, alice},
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{ctx, 3, bob},
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},
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expect: output{
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n: 2,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(2),
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Time: y2kPlus(3),
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Value: 7,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(2),
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Time: y2kPlus(3),
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Value: 14,
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},
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},
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},
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},
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},
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{
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input: []arg[N]{},
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// Precomputed sums are expected to reset.
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expect: output{
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n: 0,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.DataPoint[N]{},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 1, alice},
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{ctx, 1, bob},
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// These will exceed cardinality limit.
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{ctx, 1, carol},
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{ctx, 1, dave},
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},
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expect: output{
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n: 3,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(4),
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Time: y2kPlus(5),
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Value: 1,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(4),
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Time: y2kPlus(5),
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Value: 1,
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},
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{
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Attributes: overflowSet,
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StartTime: y2kPlus(4),
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Time: y2kPlus(5),
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Value: 2,
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},
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},
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},
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},
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},
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})
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}
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func testCumulativePrecomputedSum[N int64 | float64]() func(t *testing.T) {
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mono := false
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in, out := Builder[N]{
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Temporality: metricdata.CumulativeTemporality,
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Filter: attrFltr,
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AggregationLimit: 3,
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}.PrecomputedSum(mono)
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ctx := context.Background()
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return test[N](in, out, []teststep[N]{
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{
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input: []arg[N]{},
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expect: output{
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n: 0,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.DataPoint[N]{},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 1, alice},
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{ctx, -1, bob},
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{ctx, 1, fltrAlice},
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{ctx, 2, alice},
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{ctx, -10, bob},
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},
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expect: output{
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n: 2,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(0),
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Time: y2kPlus(2),
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Value: 4,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(0),
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Time: y2kPlus(2),
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Value: -11,
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},
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},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 1, fltrAlice},
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{ctx, 10, alice},
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{ctx, 3, bob},
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},
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expect: output{
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n: 2,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(0),
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Time: y2kPlus(3),
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Value: 11,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(0),
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Time: y2kPlus(3),
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Value: 3,
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},
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},
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},
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},
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},
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{
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input: []arg[N]{},
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// Precomputed sums are expected to reset.
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expect: output{
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n: 0,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.DataPoint[N]{},
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},
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},
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},
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{
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input: []arg[N]{
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{ctx, 1, alice},
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{ctx, 1, bob},
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// These will exceed cardinality limit.
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{ctx, 1, carol},
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{ctx, 1, dave},
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},
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expect: output{
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n: 3,
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agg: metricdata.Sum[N]{
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IsMonotonic: mono,
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.DataPoint[N]{
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{
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Attributes: fltrAlice,
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StartTime: y2kPlus(0),
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Time: y2kPlus(5),
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Value: 1,
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},
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{
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Attributes: fltrBob,
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StartTime: y2kPlus(0),
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Time: y2kPlus(5),
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Value: 1,
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},
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{
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Attributes: overflowSet,
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StartTime: y2kPlus(0),
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Time: y2kPlus(5),
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Value: 2,
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},
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},
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},
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},
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},
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})
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}
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|
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func BenchmarkSum(b *testing.B) {
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// The monotonic argument is only used to annotate the Sum returned from
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// the Aggregation method. It should not have an effect on operational
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// performance, therefore, only monotonic=false is benchmarked here.
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b.Run("Int64/Cumulative", benchmarkAggregate(func() (Measure[int64], ComputeAggregation) {
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return Builder[int64]{
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Temporality: metricdata.CumulativeTemporality,
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}.Sum(false)
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}))
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|
b.Run("Int64/Delta", benchmarkAggregate(func() (Measure[int64], ComputeAggregation) {
|
|
return Builder[int64]{
|
|
Temporality: metricdata.DeltaTemporality,
|
|
}.Sum(false)
|
|
}))
|
|
b.Run("Float64/Cumulative", benchmarkAggregate(func() (Measure[float64], ComputeAggregation) {
|
|
return Builder[float64]{
|
|
Temporality: metricdata.CumulativeTemporality,
|
|
}.Sum(false)
|
|
}))
|
|
b.Run("Float64/Delta", benchmarkAggregate(func() (Measure[float64], ComputeAggregation) {
|
|
return Builder[float64]{
|
|
Temporality: metricdata.DeltaTemporality,
|
|
}.Sum(false)
|
|
}))
|
|
|
|
b.Run("Precomputed/Int64/Cumulative", benchmarkAggregate(func() (Measure[int64], ComputeAggregation) {
|
|
return Builder[int64]{
|
|
Temporality: metricdata.CumulativeTemporality,
|
|
}.PrecomputedSum(false)
|
|
}))
|
|
b.Run("Precomputed/Int64/Delta", benchmarkAggregate(func() (Measure[int64], ComputeAggregation) {
|
|
return Builder[int64]{
|
|
Temporality: metricdata.DeltaTemporality,
|
|
}.PrecomputedSum(false)
|
|
}))
|
|
b.Run("Precomputed/Float64/Cumulative", benchmarkAggregate(func() (Measure[float64], ComputeAggregation) {
|
|
return Builder[float64]{
|
|
Temporality: metricdata.CumulativeTemporality,
|
|
}.PrecomputedSum(false)
|
|
}))
|
|
b.Run("Precomputed/Float64/Delta", benchmarkAggregate(func() (Measure[float64], ComputeAggregation) {
|
|
return Builder[float64]{
|
|
Temporality: metricdata.DeltaTemporality,
|
|
}.PrecomputedSum(false)
|
|
}))
|
|
}
|