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f57bf14de2
Implement a lockless histogram using atomics, and use a sync.Map for attribute access. This improves performance by ~2x. The design is very similar to https://github.com/open-telemetry/opentelemetry-go/pull/7427, but with one additional change to make the histogram data point itself atomic: * For cumulative histograms, which do not use a hot/cold limitedSyncMap, we use a hot/cold data point. This way, we maintain the keys in the sync map, but still ensure that collection gets a consistent view of measure() calls. Parallel benchmarks: ``` │ main.txt │ hist.txt │ │ sec/op │ sec/op vs base │ SyncMeasure/NoView/ExemplarsDisabled/Int64Histogram/Attributes/10-24 274.5n ± 2% 125.2n ± 5% -54.42% (p=0.002 n=6) SyncMeasure/NoView/ExemplarsDisabled/Float64Histogram/Attributes/10-24 274.1n ± 2% 132.5n ± 2% -51.65% (p=0.002 n=6) geomean 274.3n 128.8n -53.05% ``` zero memory allocations before and after this change for Measure(). Omitted for brevity Benchmarks for collect: ``` │ main.txt │ hist.txt │ │ sec/op │ sec/op vs base │ Collect/NoView/Int64Histogram/1/Attributes/0-24 1.799µ ± 60% 1.702µ ± 6% ~ (p=1.000 n=6) Collect/NoView/Int64Histogram/1/Attributes/1-24 973.7n ± 28% 1720.0n ± 5% +76.65% (p=0.002 n=6) Collect/NoView/Int64Histogram/1/Attributes/10-24 881.0n ± 17% 1710.0n ± 5% +94.09% (p=0.002 n=6) Collect/NoView/Int64Histogram/10/Attributes/0-24 996.1n ± 14% 1781.5n ± 4% +78.85% (p=0.002 n=6) Collect/NoView/Int64Histogram/10/Attributes/1-24 1.029µ ± 67% 1.733µ ± 3% +68.42% (p=0.009 n=6) Collect/NoView/Int64Histogram/10/Attributes/10-24 1.533µ ± 18% 1.708µ ± 4% ~ (p=0.240 n=6) Collect/NoView/Float64Histogram/1/Attributes/0-24 1.222µ ± 120% 1.733µ ± 4% ~ (p=0.065 n=6) Collect/NoView/Float64Histogram/1/Attributes/1-24 893.3n ± 8% 1733.0n ± 4% +94.00% (p=0.002 n=6) Collect/NoView/Float64Histogram/1/Attributes/10-24 860.7n ± 2% 1732.0n ± 5% +101.23% (p=0.002 n=6) Collect/NoView/Float64Histogram/10/Attributes/0-24 852.5n ± 4% 1758.0n ± 3% +106.22% (p=0.002 n=6) Collect/NoView/Float64Histogram/10/Attributes/1-24 853.8n ± 3% 1725.0n ± 3% +102.04% (p=0.002 n=6) Collect/NoView/Float64Histogram/10/Attributes/10-24 843.4n ± 2% 1755.0n ± 4% +108.10% (p=0.002 n=6) geomean 1.028µ 1.732µ +68.46% │ main.txt │ hist.txt │ │ B/op │ B/op vs base │ Collect/NoView/Int64Histogram/1/Attributes/0-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) Collect/NoView/Int64Histogram/1/Attributes/1-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) Collect/NoView/Int64Histogram/1/Attributes/10-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) Collect/NoView/Int64Histogram/10/Attributes/0-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) Collect/NoView/Int64Histogram/10/Attributes/1-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) Collect/NoView/Int64Histogram/10/Attributes/10-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) Collect/NoView/Float64Histogram/1/Attributes/0-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) Collect/NoView/Float64Histogram/1/Attributes/1-24 336.0 ± 0% 2130.5 ± 0% +534.08% (p=0.002 n=6) Collect/NoView/Float64Histogram/1/Attributes/10-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) Collect/NoView/Float64Histogram/10/Attributes/0-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) Collect/NoView/Float64Histogram/10/Attributes/1-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) Collect/NoView/Float64Histogram/10/Attributes/10-24 336.0 ± 0% 2131.0 ± 0% +534.23% (p=0.002 n=6) geomean 336.0 2.081Ki +534.21% │ main.txt │ hist.txt │ │ allocs/op │ allocs/op vs base │ Collect/NoView/Int64Histogram/1/Attributes/0-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Int64Histogram/1/Attributes/1-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Int64Histogram/1/Attributes/10-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Int64Histogram/10/Attributes/0-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Int64Histogram/10/Attributes/1-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Int64Histogram/10/Attributes/10-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Float64Histogram/1/Attributes/0-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Float64Histogram/1/Attributes/1-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Float64Histogram/1/Attributes/10-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Float64Histogram/10/Attributes/0-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Float64Histogram/10/Attributes/1-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) Collect/NoView/Float64Histogram/10/Attributes/10-24 5.000 ± 0% 6.000 ± 0% +20.00% (p=0.002 n=6) geomean 5.000 6.000 +20.00% ``` Collect does get substantially worse, but Measure is expected to be called significantly more often than collect. --------- Co-authored-by: Bartlomiej Plotka <bwplotka@gmail.com>
439 lines
13 KiB
Go
439 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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"sort"
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"testing"
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"time"
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"github.com/stretchr/testify/assert"
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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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"go.opentelemetry.io/otel/sdk/metric/metricdata/metricdatatest"
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)
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var (
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bounds = []float64{1, 5}
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noMinMax = false
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)
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func TestHistogram(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/Delta/Sum", testDeltaHist[int64](conf[int64]{hPt: hPointSummed[int64]}))
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c.Reset()
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t.Run("Int64/Delta/NoSum", testDeltaHist[int64](conf[int64]{noSum: true, hPt: hPoint[int64]}))
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c.Reset()
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t.Run("Float64/Delta/Sum", testDeltaHist[float64](conf[float64]{hPt: hPointSummed[float64]}))
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c.Reset()
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t.Run("Float64/Delta/NoSum", testDeltaHist[float64](conf[float64]{noSum: true, hPt: hPoint[float64]}))
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c.Reset()
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t.Run("Int64/Cumulative/Sum", testCumulativeHist[int64](conf[int64]{hPt: hPointSummed[int64]}))
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c.Reset()
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t.Run("Int64/Cumulative/NoSum", testCumulativeHist[int64](conf[int64]{noSum: true, hPt: hPoint[int64]}))
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c.Reset()
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t.Run("Float64/Cumulative/Sum", testCumulativeHist[float64](conf[float64]{hPt: hPointSummed[float64]}))
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c.Reset()
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t.Run("Float64/Cumulative/NoSum", testCumulativeHist[float64](conf[float64]{noSum: true, hPt: hPoint[float64]}))
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}
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type conf[N int64 | float64] struct {
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noSum bool
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hPt func(attribute.Set, N, uint64, time.Time, time.Time) metricdata.HistogramDataPoint[N]
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}
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func testDeltaHist[N int64 | float64](c conf[N]) func(t *testing.T) {
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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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}.ExplicitBucketHistogram(bounds, noMinMax, c.noSum)
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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.Histogram[N]{
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.HistogramDataPoint[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, 2, alice},
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{ctx, 10, bob},
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{ctx, 2, 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.Histogram[N]{
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.HistogramDataPoint[N]{
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c.hPt(fltrAlice, 2, 3, y2kPlus(1), y2kPlus(2)),
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c.hPt(fltrBob, 10, 2, y2kPlus(1), y2kPlus(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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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.Histogram[N]{
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.HistogramDataPoint[N]{
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c.hPt(fltrAlice, 10, 1, y2kPlus(2), y2kPlus(3)),
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c.hPt(fltrBob, 3, 1, y2kPlus(2), y2kPlus(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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input: []arg[N]{},
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// Delta histograms are expected to reset.
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expect: output{
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n: 0,
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agg: metricdata.Histogram[N]{
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.HistogramDataPoint[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.Histogram[N]{
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Temporality: metricdata.DeltaTemporality,
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DataPoints: []metricdata.HistogramDataPoint[N]{
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c.hPt(fltrAlice, 1, 1, y2kPlus(4), y2kPlus(5)),
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c.hPt(fltrBob, 1, 1, y2kPlus(4), y2kPlus(5)),
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c.hPt(overflowSet, 1, 2, y2kPlus(4), y2kPlus(5)),
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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 testCumulativeHist[N int64 | float64](c conf[N]) func(t *testing.T) {
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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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}.ExplicitBucketHistogram(bounds, noMinMax, c.noSum)
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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.Histogram[N]{
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.HistogramDataPoint[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, 2, alice},
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{ctx, 10, bob},
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{ctx, 2, 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.Histogram[N]{
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.HistogramDataPoint[N]{
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c.hPt(fltrAlice, 2, 3, y2kPlus(0), y2kPlus(2)),
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c.hPt(fltrBob, 10, 2, y2kPlus(0), y2kPlus(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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input: []arg[N]{
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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.Histogram[N]{
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.HistogramDataPoint[N]{
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c.hPt(fltrAlice, 2, 4, y2kPlus(0), y2kPlus(3)),
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c.hPt(fltrBob, 10, 3, y2kPlus(0), y2kPlus(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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input: []arg[N]{},
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expect: output{
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n: 2,
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agg: metricdata.Histogram[N]{
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.HistogramDataPoint[N]{
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c.hPt(fltrAlice, 2, 4, y2kPlus(0), y2kPlus(4)),
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c.hPt(fltrBob, 10, 3, y2kPlus(0), y2kPlus(4)),
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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.Histogram[N]{
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Temporality: metricdata.CumulativeTemporality,
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DataPoints: []metricdata.HistogramDataPoint[N]{
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c.hPt(fltrAlice, 2, 4, y2kPlus(0), y2kPlus(5)),
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c.hPt(fltrBob, 10, 3, y2kPlus(0), y2kPlus(5)),
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c.hPt(overflowSet, 1, 2, y2kPlus(0), y2kPlus(5)),
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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 TestHistogramConcurrentSafe(t *testing.T) {
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t.Run("Int64/Delta", testDeltaHistConcurrentSafe[int64]())
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t.Run("Float64/Delta", testDeltaHistConcurrentSafe[float64]())
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t.Run("Int64/Cumulative", testCumulativeHistConcurrentSafe[int64]())
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t.Run("Float64/Cumulative", testCumulativeHistConcurrentSafe[float64]())
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}
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func validateHistogram[N int64 | float64](t *testing.T, got metricdata.Aggregation) {
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s, ok := got.(metricdata.Histogram[N])
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if !ok {
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t.Fatalf("wrong aggregation type: %+v", got)
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}
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for _, dp := range s.DataPoints {
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assert.False(t,
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dp.Time.Before(dp.StartTime),
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"Timestamp %v must not be before start time %v", dp.Time, dp.StartTime,
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)
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switch dp.Attributes {
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case fltrAlice:
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// alice observations are always a multiple of 2
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assert.Equal(t, int64(0), int64(dp.Sum)%2)
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case fltrBob:
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// bob observations are always a multiple of 3
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assert.Equal(t, int64(0), int64(dp.Sum)%3)
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default:
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t.Fatalf("wrong attributes %+v", dp.Attributes)
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}
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avg := float64(dp.Sum) / float64(dp.Count)
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if minVal, ok := dp.Min.Value(); ok {
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assert.GreaterOrEqual(t, avg, float64(minVal))
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}
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if maxVal, ok := dp.Max.Value(); ok {
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assert.LessOrEqual(t, avg, float64(maxVal))
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}
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var totalCount uint64
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for _, bc := range dp.BucketCounts {
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totalCount += bc
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}
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assert.Equal(t, totalCount, dp.Count)
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}
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}
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func testDeltaHistConcurrentSafe[N int64 | float64]() func(t *testing.T) {
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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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}.ExplicitBucketHistogram(bounds, noMinMax, false)
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return testAggergationConcurrentSafe[N](in, out, validateHistogram[N])
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}
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func testCumulativeHistConcurrentSafe[N int64 | float64]() func(t *testing.T) {
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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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}.ExplicitBucketHistogram(bounds, noMinMax, false)
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return testAggergationConcurrentSafe[N](in, out, validateHistogram[N])
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}
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// hPointSummed returns an HistogramDataPoint that started and ended now with
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// multi number of measurements values v. It includes a min and max (set to v).
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func hPointSummed[N int64 | float64](
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a attribute.Set,
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v N,
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multi uint64,
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start, t time.Time,
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) metricdata.HistogramDataPoint[N] {
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idx := sort.SearchFloat64s(bounds, float64(v))
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counts := make([]uint64, len(bounds)+1)
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counts[idx] += multi
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return metricdata.HistogramDataPoint[N]{
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Attributes: a,
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StartTime: start,
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Time: t,
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Count: multi,
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Bounds: bounds,
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BucketCounts: counts,
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Min: metricdata.NewExtrema(v),
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Max: metricdata.NewExtrema(v),
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Sum: v * N(multi),
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}
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}
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// hPoint returns an HistogramDataPoint that started and ended now with multi
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// number of measurements values v. It includes a min and max (set to v).
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func hPoint[N int64 | float64](
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a attribute.Set,
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v N,
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multi uint64,
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start, t time.Time,
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) metricdata.HistogramDataPoint[N] {
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idx := sort.SearchFloat64s(bounds, float64(v))
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counts := make([]uint64, len(bounds)+1)
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counts[idx] += multi
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return metricdata.HistogramDataPoint[N]{
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Attributes: a,
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StartTime: start,
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Time: t,
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Count: multi,
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Bounds: bounds,
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BucketCounts: counts,
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Min: metricdata.NewExtrema(v),
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Max: metricdata.NewExtrema(v),
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}
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}
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func TestHistogramImmutableBounds(t *testing.T) {
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b := []float64{0, 1, 2}
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cpB := make([]float64, len(b))
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copy(cpB, b)
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h := newCumulativeHistogram[int64](b, false, false, 0, dropExemplars[int64])
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require.Equal(t, cpB, h.bounds)
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b[0] = 10
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assert.Equal(t, cpB, h.bounds, "modifying the bounds argument should not change the bounds")
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h.measure(t.Context(), 5, alice, nil)
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var data metricdata.Aggregation = metricdata.Histogram[int64]{}
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h.collect(&data)
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hdp := data.(metricdata.Histogram[int64]).DataPoints[0]
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hdp.Bounds[1] = 10
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assert.Equal(t, cpB, h.bounds, "modifying the Aggregation bounds should not change the bounds")
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}
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func TestCumulativeHistogramImmutableCounts(t *testing.T) {
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h := newCumulativeHistogram[int64](bounds, noMinMax, false, 0, dropExemplars[int64])
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h.measure(t.Context(), 5, alice, nil)
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|
|
var data metricdata.Aggregation = metricdata.Histogram[int64]{}
|
|
h.collect(&data)
|
|
hdp := data.(metricdata.Histogram[int64]).DataPoints[0]
|
|
|
|
hPt, ok := h.values.Load(alice.Equivalent())
|
|
require.True(t, ok)
|
|
hcHistPt := hPt.(*hotColdHistogramPoint[int64])
|
|
readIdx := hcHistPt.hcwg.swapHotAndWait()
|
|
var bucketCounts []uint64
|
|
hcHistPt.hotColdPoint[readIdx].loadCountsInto(&bucketCounts)
|
|
require.Equal(t, hdp.BucketCounts, bucketCounts)
|
|
hotIdx := (readIdx + 1) % 2
|
|
hcHistPt.hotColdPoint[readIdx].mergeIntoAndReset(&hcHistPt.hotColdPoint[hotIdx], noMinMax, false)
|
|
|
|
cpCounts := make([]uint64, len(hdp.BucketCounts))
|
|
copy(cpCounts, hdp.BucketCounts)
|
|
hdp.BucketCounts[0] = 10
|
|
hPt, ok = h.values.Load(alice.Equivalent())
|
|
require.True(t, ok)
|
|
hcHistPt = hPt.(*hotColdHistogramPoint[int64])
|
|
readIdx = hcHistPt.hcwg.swapHotAndWait()
|
|
hcHistPt.hotColdPoint[readIdx].loadCountsInto(&bucketCounts)
|
|
assert.Equal(
|
|
t,
|
|
cpCounts,
|
|
bucketCounts,
|
|
"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 := newDeltaHistogram[int64](bounds, noMinMax, false, 0, dropExemplars[int64])
|
|
|
|
var data metricdata.Aggregation = metricdata.Histogram[int64]{}
|
|
require.Equal(t, 0, h.collect(&data))
|
|
require.Empty(t, data.(metricdata.Histogram[int64]).DataPoints)
|
|
|
|
h.measure(t.Context(), 1, alice, nil)
|
|
|
|
expect := metricdata.Histogram[int64]{Temporality: metricdata.DeltaTemporality}
|
|
expect.DataPoints = []metricdata.HistogramDataPoint[int64]{hPointSummed[int64](alice, 1, 1, now(), now())}
|
|
h.collect(&data)
|
|
metricdatatest.AssertAggregationsEqual(t, expect, data)
|
|
|
|
// The attr set should be forgotten once Aggregations is called.
|
|
expect.DataPoints = nil
|
|
assert.Equal(t, 0, h.collect(&data))
|
|
assert.Empty(t, data.(metricdata.Histogram[int64]).DataPoints)
|
|
|
|
// Aggregating another set should not affect the original (alice).
|
|
h.measure(t.Context(), 1, bob, nil)
|
|
expect.DataPoints = []metricdata.HistogramDataPoint[int64]{hPointSummed[int64](bob, 1, 1, now(), now())}
|
|
h.collect(&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)
|
|
}))
|
|
}
|