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David Ashpole
65f85fc93a
I'm taking a stab at improving the ConcurrentSafe tests for aggregations before taking on the lockless exponential histogram implementation again. Part of https://github.com/open-telemetry/opentelemetry-go/issues/7796 This PR includes a few improvements: * All concurrent-safe tests now use 10 different attribute sets to make sure we are testing concurrent increments that result in an overflow (the cardinality limit of the test is 3). * All concurrent-safe tests for floats now include decimal valued-inputs. * Improved the validation of the collected metrics: * Validate the total after multiple collects. * Validate that increments are made to the correct bucket for histograms * Validate that the overflow attribute set has the correct total value. This uncovered an apparent race condition where the lastvalue aggregation can collect a value of zero even when no zero-value is recorded. I added a TODO, and will fix this in a follow-up. I used AI to help me design and implement tests, but requested each of the changes, and reviewed the output. --------- Co-authored-by: Tyler Yahn <MrAlias@users.noreply.github.com>
671 lines
16 KiB
Go
671 lines
16 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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"github.com/stretchr/testify/require"
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"go.opentelemetry.io/otel/attribute"
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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 TestSumConcurrentSafe(t *testing.T) {
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t.Run("Int64/DeltaSum", testDeltaSumConcurrentSafe[int64]())
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t.Run("Float64/DeltaSum", testDeltaSumConcurrentSafe[float64]())
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t.Run("Int64/CumulativeSum", testCumulativeSumConcurrentSafe[int64]())
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t.Run("Float64/CumulativeSum", testCumulativeSumConcurrentSafe[float64]())
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t.Run("Int64/DeltaPrecomputedSum", testDeltaPrecomputedSumConcurrentSafe[int64]())
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t.Run("Float64/DeltaPrecomputedSum", testDeltaPrecomputedSumConcurrentSafe[float64]())
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t.Run("Int64/CumulativePrecomputedSum", testCumulativePrecomputedSumConcurrentSafe[int64]())
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t.Run("Float64/CumulativePrecomputedSum", testCumulativePrecomputedSumConcurrentSafe[float64]())
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}
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//nolint:revive // isPrecomputed is used for configuring validation
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func validateSum[N int64 | float64](isPrecomputed bool) func(t *testing.T, aggs []metricdata.Aggregation) {
|
|
return func(t *testing.T, aggs []metricdata.Aggregation) {
|
|
sums := make(map[attribute.Set]N)
|
|
for i, agg := range aggs {
|
|
s, ok := agg.(metricdata.Sum[N])
|
|
require.True(t, ok)
|
|
require.LessOrEqual(t, len(s.DataPoints), 3, "AggregationLimit of 3 exceeded in a single cycle")
|
|
for _, dp := range s.DataPoints {
|
|
if s.Temporality == metricdata.DeltaTemporality {
|
|
sums[dp.Attributes] += dp.Value
|
|
} else if i == len(aggs)-1 {
|
|
sums[dp.Attributes] = dp.Value
|
|
}
|
|
}
|
|
}
|
|
|
|
if isPrecomputed {
|
|
// Precomputed Sums clear the state when collected concurrently. Due to hot/cold overlap
|
|
// during flush, the sum drops intermediate updates, so the final calculation won't cleanly
|
|
// add up to the total number of operations performed by the workers. Therefore, skip exact
|
|
// invariant check, verifying only that limits and map updates occurred safely.
|
|
return
|
|
}
|
|
|
|
var total N
|
|
for _, val := range sums {
|
|
total += val
|
|
}
|
|
|
|
assertSumEqual[N](t, expectedConcurrentSum[N](), total)
|
|
}
|
|
}
|
|
|
|
func testDeltaSumConcurrentSafe[N int64 | float64]() func(t *testing.T) {
|
|
in, out := Builder[N]{
|
|
Temporality: metricdata.DeltaTemporality,
|
|
Filter: attrFltr,
|
|
AggregationLimit: 3,
|
|
}.Sum(false)
|
|
return testAggregationConcurrentSafe[N](in, out, validateSum[N](false))
|
|
}
|
|
|
|
func testCumulativeSumConcurrentSafe[N int64 | float64]() func(t *testing.T) {
|
|
in, out := Builder[N]{
|
|
Temporality: metricdata.CumulativeTemporality,
|
|
Filter: attrFltr,
|
|
AggregationLimit: 3,
|
|
}.Sum(false)
|
|
return testAggregationConcurrentSafe[N](in, out, validateSum[N](false))
|
|
}
|
|
|
|
func testDeltaPrecomputedSumConcurrentSafe[N int64 | float64]() func(t *testing.T) {
|
|
in, out := Builder[N]{
|
|
Temporality: metricdata.DeltaTemporality,
|
|
Filter: attrFltr,
|
|
AggregationLimit: 3,
|
|
}.PrecomputedSum(false)
|
|
return testAggregationConcurrentSafe[N](in, out, validateSum[N](true))
|
|
}
|
|
|
|
func testCumulativePrecomputedSumConcurrentSafe[N int64 | float64]() func(t *testing.T) {
|
|
in, out := Builder[N]{
|
|
Temporality: metricdata.CumulativeTemporality,
|
|
Filter: attrFltr,
|
|
AggregationLimit: 3,
|
|
}.PrecomputedSum(false)
|
|
return testAggregationConcurrentSafe[N](in, out, validateSum[N](true))
|
|
}
|
|
|
|
func BenchmarkSum(b *testing.B) {
|
|
// The monotonic argument is only used to annotate the Sum returned from
|
|
// the Aggregation method. It should not have an effect on operational
|
|
// performance, therefore, only monotonic=false is benchmarked here.
|
|
b.Run("Int64/Cumulative", benchmarkAggregate(func() (Measure[int64], ComputeAggregation) {
|
|
return Builder[int64]{
|
|
Temporality: metricdata.CumulativeTemporality,
|
|
}.Sum(false)
|
|
}))
|
|
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)
|
|
}))
|
|
}
|