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OTLP Receiver: Add tests (#14764)

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Signed-off-by: Arve Knudsen <arve.knudsen@gmail.com>
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Arve Knudsen 2024-08-30 11:30:57 +02:00 committed by GitHub
parent a77f5007f9
commit bc6c2c5d35
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225
storage/remote/otlptranslator/prometheusremotewrite/helper_test.go
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@ -10,6 +10,10 @@
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and // See the License for the specific language governing permissions and
// limitations under the License. // limitations under the License.
// Provenance-includes-location: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/debbf30360b8d3a0ded8db09c4419d2a9c99b94a/pkg/translator/prometheusremotewrite/helper_test.go
// Provenance-includes-license: Apache-2.0
// Provenance-includes-copyright: Copyright The OpenTelemetry Authors.
package prometheusremotewrite package prometheusremotewrite
import ( import (
@ -18,6 +22,9 @@ import (
"github.com/stretchr/testify/assert" "github.com/stretchr/testify/assert"
"go.opentelemetry.io/collector/pdata/pcommon" "go.opentelemetry.io/collector/pdata/pcommon"
"go.opentelemetry.io/collector/pdata/pmetric"
"github.com/prometheus/common/model"
"github.com/prometheus/prometheus/prompb" "github.com/prometheus/prometheus/prompb"
) )
@ -178,3 +185,221 @@ func Test_convertTimeStamp(t *testing.T) {
}) })
} }
} }
func TestPrometheusConverter_AddSummaryDataPoints(t *testing.T) {
ts := pcommon.Timestamp(time.Now().UnixNano())
tests := []struct {
name string
metric func() pmetric.Metric
want func() map[uint64]*prompb.TimeSeries
}{
{
name: "summary with start time",
metric: func() pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName("test_summary")
metric.SetEmptySummary()
dp := metric.Summary().DataPoints().AppendEmpty()
dp.SetTimestamp(ts)
dp.SetStartTimestamp(ts)
return metric
},
want: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_summary" + countStr},
}
createdLabels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_summary" + createdSuffix},
}
sumLabels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_summary" + sumStr},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(labels): {
Labels: labels,
Samples: []prompb.Sample{
{Value: 0, Timestamp: convertTimeStamp(ts)},
},
},
timeSeriesSignature(sumLabels): {
Labels: sumLabels,
Samples: []prompb.Sample{
{Value: 0, Timestamp: convertTimeStamp(ts)},
},
},
timeSeriesSignature(createdLabels): {
Labels: createdLabels,
Samples: []prompb.Sample{
{Value: float64(convertTimeStamp(ts)), Timestamp: convertTimeStamp(ts)},
},
},
}
},
},
{
name: "summary without start time",
metric: func() pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName("test_summary")
metric.SetEmptySummary()
dp := metric.Summary().DataPoints().AppendEmpty()
dp.SetTimestamp(ts)
return metric
},
want: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_summary" + countStr},
}
sumLabels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_summary" + sumStr},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(labels): {
Labels: labels,
Samples: []prompb.Sample{
{Value: 0, Timestamp: convertTimeStamp(ts)},
},
},
timeSeriesSignature(sumLabels): {
Labels: sumLabels,
Samples: []prompb.Sample{
{Value: 0, Timestamp: convertTimeStamp(ts)},
},
},
}
},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
metric := tt.metric()
converter := NewPrometheusConverter()
converter.addSummaryDataPoints(
metric.Summary().DataPoints(),
pcommon.NewResource(),
Settings{
ExportCreatedMetric: true,
},
metric.Name(),
)
assert.Equal(t, tt.want(), converter.unique)
assert.Empty(t, converter.conflicts)
})
}
}
func TestPrometheusConverter_AddHistogramDataPoints(t *testing.T) {
ts := pcommon.Timestamp(time.Now().UnixNano())
tests := []struct {
name string
metric func() pmetric.Metric
want func() map[uint64]*prompb.TimeSeries
}{
{
name: "histogram with start time",
metric: func() pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName("test_hist")
metric.SetEmptyHistogram().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
pt := metric.Histogram().DataPoints().AppendEmpty()
pt.SetTimestamp(ts)
pt.SetStartTimestamp(ts)
return metric
},
want: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_hist" + countStr},
}
createdLabels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_hist" + createdSuffix},
}
infLabels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_hist_bucket"},
{Name: model.BucketLabel, Value: "+Inf"},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(infLabels): {
Labels: infLabels,
Samples: []prompb.Sample{
{Value: 0, Timestamp: convertTimeStamp(ts)},
},
},
timeSeriesSignature(labels): {
Labels: labels,
Samples: []prompb.Sample{
{Value: 0, Timestamp: convertTimeStamp(ts)},
},
},
timeSeriesSignature(createdLabels): {
Labels: createdLabels,
Samples: []prompb.Sample{
{Value: float64(convertTimeStamp(ts)), Timestamp: convertTimeStamp(ts)},
},
},
}
},
},
{
name: "histogram without start time",
metric: func() pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName("test_hist")
metric.SetEmptyHistogram().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
pt := metric.Histogram().DataPoints().AppendEmpty()
pt.SetTimestamp(ts)
return metric
},
want: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_hist" + countStr},
}
infLabels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_hist_bucket"},
{Name: model.BucketLabel, Value: "+Inf"},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(infLabels): {
Labels: infLabels,
Samples: []prompb.Sample{
{Value: 0, Timestamp: convertTimeStamp(ts)},
},
},
timeSeriesSignature(labels): {
Labels: labels,
Samples: []prompb.Sample{
{Value: 0, Timestamp: convertTimeStamp(ts)},
},
},
}
},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
metric := tt.metric()
converter := NewPrometheusConverter()
converter.addHistogramDataPoints(
metric.Histogram().DataPoints(),
pcommon.NewResource(),
Settings{
ExportCreatedMetric: true,
},
metric.Name(),
)
assert.Equal(t, tt.want(), converter.unique)
assert.Empty(t, converter.conflicts)
})
}
}

771
storage/remote/otlptranslator/prometheusremotewrite/histograms_test.go Normal file
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@ -0,0 +1,771 @@
// Copyright 2024 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Provenance-includes-location: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/247a9f996e09a83cdc25addf70c05e42b8b30186/pkg/translator/prometheusremotewrite/histograms_test.go
// Provenance-includes-license: Apache-2.0
// Provenance-includes-copyright: Copyright The OpenTelemetry Authors.
package prometheusremotewrite
import (
"fmt"
"testing"
"time"
"github.com/prometheus/common/model"
"github.com/prometheus/prometheus/prompb"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
"go.opentelemetry.io/collector/pdata/pcommon"
"go.opentelemetry.io/collector/pdata/pmetric"
prometheustranslator "github.com/prometheus/prometheus/storage/remote/otlptranslator/prometheus"
)
type expectedBucketLayout struct {
wantSpans []prompb.BucketSpan
wantDeltas []int64
}
func TestConvertBucketsLayout(t *testing.T) {
tests := []struct {
name string
buckets func() pmetric.ExponentialHistogramDataPointBuckets
wantLayout map[int32]expectedBucketLayout
}{
{
name: "zero offset",
buckets: func() pmetric.ExponentialHistogramDataPointBuckets {
b := pmetric.NewExponentialHistogramDataPointBuckets()
b.SetOffset(0)
b.BucketCounts().FromRaw([]uint64{4, 3, 2, 1})
return b
},
wantLayout: map[int32]expectedBucketLayout{
0: {
wantSpans: []prompb.BucketSpan{
{
Offset: 1,
Length: 4,
},
},
wantDeltas: []int64{4, -1, -1, -1},
},
1: {
wantSpans: []prompb.BucketSpan{
{
Offset: 1,
Length: 2,
},
},
// 4+3, 2+1 = 7, 3 =delta= 7, -4
wantDeltas: []int64{7, -4},
},
2: {
wantSpans: []prompb.BucketSpan{
{
Offset: 1,
Length: 1,
},
},
// 4+3+2+1 = 10 =delta= 10
wantDeltas: []int64{10},
},
},
},
{
name: "offset 1",
buckets: func() pmetric.ExponentialHistogramDataPointBuckets {
b := pmetric.NewExponentialHistogramDataPointBuckets()
b.SetOffset(1)
b.BucketCounts().FromRaw([]uint64{4, 3, 2, 1})
return b
},
wantLayout: map[int32]expectedBucketLayout{
0: {
wantSpans: []prompb.BucketSpan{
{
Offset: 2,
Length: 4,
},
},
wantDeltas: []int64{4, -1, -1, -1},
},
1: {
wantSpans: []prompb.BucketSpan{
{
Offset: 1,
Length: 3,
},
},
wantDeltas: []int64{4, 1, -4}, // 0+4, 3+2, 1+0 = 4, 5, 1
},
2: {
wantSpans: []prompb.BucketSpan{
{
Offset: 1,
Length: 2,
},
},
wantDeltas: []int64{9, -8}, // 0+4+3+2, 1+0+0+0 = 9, 1
},
},
},
{
name: "positive offset",
buckets: func() pmetric.ExponentialHistogramDataPointBuckets {
b := pmetric.NewExponentialHistogramDataPointBuckets()
b.SetOffset(4)
b.BucketCounts().FromRaw([]uint64{4, 2, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1})
return b
},
wantLayout: map[int32]expectedBucketLayout{
0: {
wantSpans: []prompb.BucketSpan{
{
Offset: 5,
Length: 4,
},
{
Offset: 12,
Length: 1,
},
},
wantDeltas: []int64{4, -2, -2, 2, -1},
},
1: {
wantSpans: []prompb.BucketSpan{
{
Offset: 3,
Length: 2,
},
{
Offset: 6,
Length: 1,
},
},
// Downscale:
// 4+2, 0+2, 0+0, 0+0, 0+0, 0+0, 0+0, 0+0, 1+0 = 6, 2, 0, 0, 0, 0, 0, 0, 1
wantDeltas: []int64{6, -4, -1},
},
2: {
wantSpans: []prompb.BucketSpan{
{
Offset: 2,
Length: 1,
},
{
Offset: 3,
Length: 1,
},
},
// Downscale:
// 4+2+0+2, 0+0+0+0, 0+0+0+0, 0+0+0+0, 1+0+0+0 = 8, 0, 0, 0, 1
// Check from sclaing from previous: 6+2, 0+0, 0+0, 0+0, 1+0 = 8, 0, 0, 0, 1
wantDeltas: []int64{8, -7},
},
},
},
{
name: "scaledown merges spans",
buckets: func() pmetric.ExponentialHistogramDataPointBuckets {
b := pmetric.NewExponentialHistogramDataPointBuckets()
b.SetOffset(4)
b.BucketCounts().FromRaw([]uint64{4, 2, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1})
return b
},
wantLayout: map[int32]expectedBucketLayout{
0: {
wantSpans: []prompb.BucketSpan{
{
Offset: 5,
Length: 4,
},
{
Offset: 8,
Length: 1,
},
},
wantDeltas: []int64{4, -2, -2, 2, -1},
},
1: {
wantSpans: []prompb.BucketSpan{
{
Offset: 3,
Length: 2,
},
{
Offset: 4,
Length: 1,
},
},
// Downscale:
// 4+2, 0+2, 0+0, 0+0, 0+0, 0+0, 1+0 = 6, 2, 0, 0, 0, 0, 1
wantDeltas: []int64{6, -4, -1},
},
2: {
wantSpans: []prompb.BucketSpan{
{
Offset: 2,
Length: 4,
},
},
// Downscale:
// 4+2+0+2, 0+0+0+0, 0+0+0+0, 1+0+0+0 = 8, 0, 0, 1
// Check from sclaing from previous: 6+2, 0+0, 0+0, 1+0 = 8, 0, 0, 1
wantDeltas: []int64{8, -8, 0, 1},
},
},
},
{
name: "negative offset",
buckets: func() pmetric.ExponentialHistogramDataPointBuckets {
b := pmetric.NewExponentialHistogramDataPointBuckets()
b.SetOffset(-2)
b.BucketCounts().FromRaw([]uint64{3, 1, 0, 0, 0, 1})
return b
},
wantLayout: map[int32]expectedBucketLayout{
0: {
wantSpans: []prompb.BucketSpan{
{
Offset: -1,
Length: 2,
},
{
Offset: 3,
Length: 1,
},
},
wantDeltas: []int64{3, -2, 0},
},
1: {
wantSpans: []prompb.BucketSpan{
{
Offset: 0,
Length: 3,
},
},
// Downscale:
// 3+1, 0+0, 0+1 = 4, 0, 1
wantDeltas: []int64{4, -4, 1},
},
2: {
wantSpans: []prompb.BucketSpan{
{
Offset: 0,
Length: 2,
},
},
// Downscale:
// 0+0+3+1, 0+0+0+0 = 4, 1
wantDeltas: []int64{4, -3},
},
},
},
{
name: "buckets with gaps of size 1",
buckets: func() pmetric.ExponentialHistogramDataPointBuckets {
b := pmetric.NewExponentialHistogramDataPointBuckets()
b.SetOffset(-2)
b.BucketCounts().FromRaw([]uint64{3, 1, 0, 1, 0, 1})
return b
},
wantLayout: map[int32]expectedBucketLayout{
0: {
wantSpans: []prompb.BucketSpan{
{
Offset: -1,
Length: 6,
},
},
wantDeltas: []int64{3, -2, -1, 1, -1, 1},
},
1: {
wantSpans: []prompb.BucketSpan{
{
Offset: 0,
Length: 3,
},
},
// Downscale:
// 3+1, 0+1, 0+1 = 4, 1, 1
wantDeltas: []int64{4, -3, 0},
},
2: {
wantSpans: []prompb.BucketSpan{
{
Offset: 0,
Length: 2,
},
},
// Downscale:
// 0+0+3+1, 0+1+0+1 = 4, 2
wantDeltas: []int64{4, -2},
},
},
},
{
name: "buckets with gaps of size 2",
buckets: func() pmetric.ExponentialHistogramDataPointBuckets {
b := pmetric.NewExponentialHistogramDataPointBuckets()
b.SetOffset(-2)
b.BucketCounts().FromRaw([]uint64{3, 0, 0, 1, 0, 0, 1})
return b
},
wantLayout: map[int32]expectedBucketLayout{
0: {
wantSpans: []prompb.BucketSpan{
{
Offset: -1,
Length: 7,
},
},
wantDeltas: []int64{3, -3, 0, 1, -1, 0, 1},
},
1: {
wantSpans: []prompb.BucketSpan{
{
Offset: 0,
Length: 4,
},
},
// Downscale:
// 3+0, 0+1, 0+0, 0+1 = 3, 1, 0, 1
wantDeltas: []int64{3, -2, -1, 1},
},
2: {
wantSpans: []prompb.BucketSpan{
{
Offset: 0,
Length: 3,
},
},
// Downscale:
// 0+0+3+0, 0+1+0+0, 1+0+0+0 = 3, 1, 1
wantDeltas: []int64{3, -2, 0},
},
},
},
{
name: "zero buckets",
buckets: pmetric.NewExponentialHistogramDataPointBuckets,
wantLayout: map[int32]expectedBucketLayout{
0: {
wantSpans: nil,
wantDeltas: nil,
},
1: {
wantSpans: nil,
wantDeltas: nil,
},
2: {
wantSpans: nil,
wantDeltas: nil,
},
},
},
}
for _, tt := range tests {
for scaleDown, wantLayout := range tt.wantLayout {
t.Run(fmt.Sprintf("%s-scaleby-%d", tt.name, scaleDown), func(t *testing.T) {
gotSpans, gotDeltas := convertBucketsLayout(tt.buckets(), scaleDown)
assert.Equal(t, wantLayout.wantSpans, gotSpans)
assert.Equal(t, wantLayout.wantDeltas, gotDeltas)
})
}
}
}
func BenchmarkConvertBucketLayout(b *testing.B) {
scenarios := []struct {
gap int
}{
{gap: 0},
{gap: 1},
{gap: 2},
{gap: 3},
}
for _, scenario := range scenarios {
buckets := pmetric.NewExponentialHistogramDataPointBuckets()
buckets.SetOffset(0)
for i := 0; i < 1000; i++ {
if i%(scenario.gap+1) == 0 {
buckets.BucketCounts().Append(10)
} else {
buckets.BucketCounts().Append(0)
}
}
b.Run(fmt.Sprintf("gap %d", scenario.gap), func(b *testing.B) {
for i := 0; i < b.N; i++ {
convertBucketsLayout(buckets, 0)
}
})
}
}
func TestExponentialToNativeHistogram(t *testing.T) {
tests := []struct {
name string
exponentialHist func() pmetric.ExponentialHistogramDataPoint
wantNativeHist func() prompb.Histogram
wantErrMessage string
}{
{
name: "convert exp. to native histogram",
exponentialHist: func() pmetric.ExponentialHistogramDataPoint {
pt := pmetric.NewExponentialHistogramDataPoint()
pt.SetStartTimestamp(pcommon.NewTimestampFromTime(time.UnixMilli(100)))
pt.SetTimestamp(pcommon.NewTimestampFromTime(time.UnixMilli(500)))
pt.SetCount(4)
pt.SetSum(10.1)
pt.SetScale(1)
pt.SetZeroCount(1)
pt.Positive().BucketCounts().FromRaw([]uint64{1, 1})
pt.Positive().SetOffset(1)
pt.Negative().BucketCounts().FromRaw([]uint64{1, 1})
pt.Negative().SetOffset(1)
return pt
},
wantNativeHist: func() prompb.Histogram {
return prompb.Histogram{
Count: &prompb.Histogram_CountInt{CountInt: 4},
Sum: 10.1,
Schema: 1,
ZeroThreshold: defaultZeroThreshold,
ZeroCount: &prompb.Histogram_ZeroCountInt{ZeroCountInt: 1},
NegativeSpans: []prompb.BucketSpan{{Offset: 2, Length: 2}},
NegativeDeltas: []int64{1, 0},
PositiveSpans: []prompb.BucketSpan{{Offset: 2, Length: 2}},
PositiveDeltas: []int64{1, 0},
Timestamp: 500,
}
},
},
{
name: "convert exp. to native histogram with no sum",
exponentialHist: func() pmetric.ExponentialHistogramDataPoint {
pt := pmetric.NewExponentialHistogramDataPoint()
pt.SetStartTimestamp(pcommon.NewTimestampFromTime(time.UnixMilli(100)))
pt.SetTimestamp(pcommon.NewTimestampFromTime(time.UnixMilli(500)))
pt.SetCount(4)
pt.SetScale(1)
pt.SetZeroCount(1)
pt.Positive().BucketCounts().FromRaw([]uint64{1, 1})
pt.Positive().SetOffset(1)
pt.Negative().BucketCounts().FromRaw([]uint64{1, 1})
pt.Negative().SetOffset(1)
return pt
},
wantNativeHist: func() prompb.Histogram {
return prompb.Histogram{
Count: &prompb.Histogram_CountInt{CountInt: 4},
Schema: 1,
ZeroThreshold: defaultZeroThreshold,
ZeroCount: &prompb.Histogram_ZeroCountInt{ZeroCountInt: 1},
NegativeSpans: []prompb.BucketSpan{{Offset: 2, Length: 2}},
NegativeDeltas: []int64{1, 0},
PositiveSpans: []prompb.BucketSpan{{Offset: 2, Length: 2}},
PositiveDeltas: []int64{1, 0},
Timestamp: 500,
}
},
},
{
name: "invalid negative scale",
exponentialHist: func() pmetric.ExponentialHistogramDataPoint {
pt := pmetric.NewExponentialHistogramDataPoint()
pt.SetScale(-10)
return pt
},
wantErrMessage: "cannot convert exponential to native histogram." +
" Scale must be >= -4, was -10",
},
{
name: "no downscaling at scale 8",
exponentialHist: func() pmetric.ExponentialHistogramDataPoint {
pt := pmetric.NewExponentialHistogramDataPoint()
pt.SetTimestamp(pcommon.NewTimestampFromTime(time.UnixMilli(500)))
pt.SetCount(6)
pt.SetSum(10.1)
pt.SetScale(8)
pt.SetZeroCount(1)
pt.Positive().BucketCounts().FromRaw([]uint64{1, 1, 1})
pt.Positive().SetOffset(1)
pt.Negative().BucketCounts().FromRaw([]uint64{1, 1, 1})
pt.Negative().SetOffset(2)
return pt
},
wantNativeHist: func() prompb.Histogram {
return prompb.Histogram{
Count: &prompb.Histogram_CountInt{CountInt: 6},
Sum: 10.1,
Schema: 8,
ZeroThreshold: defaultZeroThreshold,
ZeroCount: &prompb.Histogram_ZeroCountInt{ZeroCountInt: 1},
PositiveSpans: []prompb.BucketSpan{{Offset: 2, Length: 3}},
PositiveDeltas: []int64{1, 0, 0}, // 1, 1, 1
NegativeSpans: []prompb.BucketSpan{{Offset: 3, Length: 3}},
NegativeDeltas: []int64{1, 0, 0}, // 1, 1, 1
Timestamp: 500,
}
},
},
{
name: "downsample if scale is more than 8",
exponentialHist: func() pmetric.ExponentialHistogramDataPoint {
pt := pmetric.NewExponentialHistogramDataPoint()
pt.SetTimestamp(pcommon.NewTimestampFromTime(time.UnixMilli(500)))
pt.SetCount(6)
pt.SetSum(10.1)
pt.SetScale(9)
pt.SetZeroCount(1)
pt.Positive().BucketCounts().FromRaw([]uint64{1, 1, 1})
pt.Positive().SetOffset(1)
pt.Negative().BucketCounts().FromRaw([]uint64{1, 1, 1})
pt.Negative().SetOffset(2)
return pt
},
wantNativeHist: func() prompb.Histogram {
return prompb.Histogram{
Count: &prompb.Histogram_CountInt{CountInt: 6},
Sum: 10.1,
Schema: 8,
ZeroThreshold: defaultZeroThreshold,
ZeroCount: &prompb.Histogram_ZeroCountInt{ZeroCountInt: 1},
PositiveSpans: []prompb.BucketSpan{{Offset: 1, Length: 2}},
PositiveDeltas: []int64{1, 1}, // 0+1, 1+1 = 1, 2
NegativeSpans: []prompb.BucketSpan{{Offset: 2, Length: 2}},
NegativeDeltas: []int64{2, -1}, // 1+1, 1+0 = 2, 1
Timestamp: 500,
}
},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
validateExponentialHistogramCount(t, tt.exponentialHist()) // Sanity check.
got, annots, err := exponentialToNativeHistogram(tt.exponentialHist())
if tt.wantErrMessage != "" {
assert.ErrorContains(t, err, tt.wantErrMessage)
return
}
require.NoError(t, err)
require.Empty(t, annots)
assert.Equal(t, tt.wantNativeHist(), got)
validateNativeHistogramCount(t, got)
})
}
}
func validateExponentialHistogramCount(t *testing.T, h pmetric.ExponentialHistogramDataPoint) {
actualCount := uint64(0)
for _, bucket := range h.Positive().BucketCounts().AsRaw() {
actualCount += bucket
}
for _, bucket := range h.Negative().BucketCounts().AsRaw() {
actualCount += bucket
}
require.Equal(t, h.Count(), actualCount, "exponential histogram count mismatch")
}
func validateNativeHistogramCount(t *testing.T, h prompb.Histogram) {
require.NotNil(t, h.Count)
require.IsType(t, &prompb.Histogram_CountInt{}, h.Count)
want := h.Count.(*prompb.Histogram_CountInt).CountInt
var (
actualCount uint64
prevBucket int64
)
for _, delta := range h.PositiveDeltas {
prevBucket += delta
actualCount += uint64(prevBucket)
}
prevBucket = 0
for _, delta := range h.NegativeDeltas {
prevBucket += delta
actualCount += uint64(prevBucket)
}
assert.Equal(t, want, actualCount, "native histogram count mismatch")
}
func TestPrometheusConverter_addExponentialHistogramDataPoints(t *testing.T) {
tests := []struct {
name string
metric func() pmetric.Metric
wantSeries func() map[uint64]*prompb.TimeSeries
}{
{
name: "histogram data points with same labels",
metric: func() pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName("test_hist")
metric.SetEmptyExponentialHistogram().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
pt := metric.ExponentialHistogram().DataPoints().AppendEmpty()
pt.SetCount(7)
pt.SetScale(1)
pt.Positive().SetOffset(-1)
pt.Positive().BucketCounts().FromRaw([]uint64{4, 2})
pt.Exemplars().AppendEmpty().SetDoubleValue(1)
pt.Attributes().PutStr("attr", "test_attr")
pt = metric.ExponentialHistogram().DataPoints().AppendEmpty()
pt.SetCount(4)
pt.SetScale(1)
pt.Positive().SetOffset(-1)
pt.Positive().BucketCounts().FromRaw([]uint64{4, 2, 1})
pt.Exemplars().AppendEmpty().SetDoubleValue(2)
pt.Attributes().PutStr("attr", "test_attr")
return metric
},
wantSeries: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_hist"},
{Name: "attr", Value: "test_attr"},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(labels): {
Labels: labels,
Histograms: []prompb.Histogram{
{
Count: &prompb.Histogram_CountInt{CountInt: 7},
Schema: 1,
ZeroThreshold: defaultZeroThreshold,
ZeroCount: &prompb.Histogram_ZeroCountInt{ZeroCountInt: 0},
PositiveSpans: []prompb.BucketSpan{{Offset: 0, Length: 2}},
PositiveDeltas: []int64{4, -2},
},
{
Count: &prompb.Histogram_CountInt{CountInt: 4},
Schema: 1,
ZeroThreshold: defaultZeroThreshold,
ZeroCount: &prompb.Histogram_ZeroCountInt{ZeroCountInt: 0},
PositiveSpans: []prompb.BucketSpan{{Offset: 0, Length: 3}},
PositiveDeltas: []int64{4, -2, -1},
},
},
Exemplars: []prompb.Exemplar{
{Value: 1},
{Value: 2},
},
},
}
},
},
{
name: "histogram data points with different labels",
metric: func() pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName("test_hist")
metric.SetEmptyExponentialHistogram().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
pt := metric.ExponentialHistogram().DataPoints().AppendEmpty()
pt.SetCount(7)
pt.SetScale(1)
pt.Positive().SetOffset(-1)
pt.Positive().BucketCounts().FromRaw([]uint64{4, 2})
pt.Exemplars().AppendEmpty().SetDoubleValue(1)
pt.Attributes().PutStr("attr", "test_attr")
pt = metric.ExponentialHistogram().DataPoints().AppendEmpty()
pt.SetCount(4)
pt.SetScale(1)
pt.Negative().SetOffset(-1)
pt.Negative().BucketCounts().FromRaw([]uint64{4, 2, 1})
pt.Exemplars().AppendEmpty().SetDoubleValue(2)
pt.Attributes().PutStr("attr", "test_attr_two")
return metric
},
wantSeries: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_hist"},
{Name: "attr", Value: "test_attr"},
}
labelsAnother := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_hist"},
{Name: "attr", Value: "test_attr_two"},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(labels): {
Labels: labels,
Histograms: []prompb.Histogram{
{
Count: &prompb.Histogram_CountInt{CountInt: 7},
Schema: 1,
ZeroThreshold: defaultZeroThreshold,
ZeroCount: &prompb.Histogram_ZeroCountInt{ZeroCountInt: 0},
PositiveSpans: []prompb.BucketSpan{{Offset: 0, Length: 2}},
PositiveDeltas: []int64{4, -2},
},
},
Exemplars: []prompb.Exemplar{
{Value: 1},
},
},
timeSeriesSignature(labelsAnother): {
Labels: labelsAnother,
Histograms: []prompb.Histogram{
{
Count: &prompb.Histogram_CountInt{CountInt: 4},
Schema: 1,
ZeroThreshold: defaultZeroThreshold,
ZeroCount: &prompb.Histogram_ZeroCountInt{ZeroCountInt: 0},
NegativeSpans: []prompb.BucketSpan{{Offset: 0, Length: 3}},
NegativeDeltas: []int64{4, -2, -1},
},
},
Exemplars: []prompb.Exemplar{
{Value: 2},
},
},
}
},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
metric := tt.metric()
converter := NewPrometheusConverter()
annots, err := converter.addExponentialHistogramDataPoints(
metric.ExponentialHistogram().DataPoints(),
pcommon.NewResource(),
Settings{
ExportCreatedMetric: true,
},
prometheustranslator.BuildCompliantName(metric, "", true),
)
require.NoError(t, err)
require.Empty(t, annots)
assert.Equal(t, tt.wantSeries(), converter.unique)
assert.Empty(t, converter.conflicts)
})
}
}

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storage/remote/otlptranslator/prometheusremotewrite/number_data_points_test.go Normal file
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// Copyright 2024 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Provenance-includes-location: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/247a9f996e09a83cdc25addf70c05e42b8b30186/pkg/translator/prometheusremotewrite/number_data_points_test.go
// Provenance-includes-license: Apache-2.0
// Provenance-includes-copyright: Copyright The OpenTelemetry Authors.
package prometheusremotewrite
import (
"testing"
"time"
"github.com/prometheus/common/model"
"github.com/prometheus/prometheus/prompb"
"github.com/stretchr/testify/assert"
"go.opentelemetry.io/collector/pdata/pcommon"
"go.opentelemetry.io/collector/pdata/pmetric"
)
func TestPrometheusConverter_addGaugeNumberDataPoints(t *testing.T) {
ts := uint64(time.Now().UnixNano())
tests := []struct {
name string
metric func() pmetric.Metric
want func() map[uint64]*prompb.TimeSeries
}{
{
name: "gauge",
metric: func() pmetric.Metric {
return getIntGaugeMetric(
"test",
pcommon.NewMap(),
1, ts,
)
},
want: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test"},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(labels): {
Labels: labels,
Samples: []prompb.Sample{
{
Value: 1,
Timestamp: convertTimeStamp(pcommon.Timestamp(ts)),
}},
},
}
},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
metric := tt.metric()
converter := NewPrometheusConverter()
converter.addGaugeNumberDataPoints(
metric.Gauge().DataPoints(),
pcommon.NewResource(),
Settings{
ExportCreatedMetric: true,
},
metric.Name(),
)
assert.Equal(t, tt.want(), converter.unique)
assert.Empty(t, converter.conflicts)
})
}
}
func TestPrometheusConverter_addSumNumberDataPoints(t *testing.T) {
ts := pcommon.Timestamp(time.Now().UnixNano())
tests := []struct {
name string
metric func() pmetric.Metric
want func() map[uint64]*prompb.TimeSeries
}{
{
name: "sum",
metric: func() pmetric.Metric {
return getIntSumMetric(
"test",
pcommon.NewMap(),
1,
uint64(ts.AsTime().UnixNano()),
)
},
want: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test"},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(labels): {
Labels: labels,
Samples: []prompb.Sample{
{
Value: 1,
Timestamp: convertTimeStamp(ts),
}},
},
}
},
},
{
name: "sum with exemplars",
metric: func() pmetric.Metric {
m := getIntSumMetric(
"test",
pcommon.NewMap(),
1,
uint64(ts.AsTime().UnixNano()),
)
m.Sum().DataPoints().At(0).Exemplars().AppendEmpty().SetDoubleValue(2)
return m
},
want: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test"},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(labels): {
Labels: labels,
Samples: []prompb.Sample{{
Value: 1,
Timestamp: convertTimeStamp(ts),
}},
Exemplars: []prompb.Exemplar{
{Value: 2},
},
},
}
},
},
{
name: "monotonic cumulative sum with start timestamp",
metric: func() pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName("test_sum")
metric.SetEmptySum().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
metric.SetEmptySum().SetIsMonotonic(true)
dp := metric.Sum().DataPoints().AppendEmpty()
dp.SetDoubleValue(1)
dp.SetTimestamp(ts)
dp.SetStartTimestamp(ts)
return metric
},
want: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_sum"},
}
createdLabels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_sum" + createdSuffix},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(labels): {
Labels: labels,
Samples: []prompb.Sample{
{Value: 1, Timestamp: convertTimeStamp(ts)},
},
},
timeSeriesSignature(createdLabels): {
Labels: createdLabels,
Samples: []prompb.Sample{
{Value: float64(convertTimeStamp(ts)), Timestamp: convertTimeStamp(ts)},
},
},
}
},
},
{
name: "monotonic cumulative sum with no start time",
metric: func() pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName("test_sum")
metric.SetEmptySum().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
metric.SetEmptySum().SetIsMonotonic(true)
dp := metric.Sum().DataPoints().AppendEmpty()
dp.SetTimestamp(ts)
return metric
},
want: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_sum"},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(labels): {
Labels: labels,
Samples: []prompb.Sample{
{Value: 0, Timestamp: convertTimeStamp(ts)},
},
},
}
},
},
{
name: "non-monotonic cumulative sum with start time",
metric: func() pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName("test_sum")
metric.SetEmptySum().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
metric.SetEmptySum().SetIsMonotonic(false)
dp := metric.Sum().DataPoints().AppendEmpty()
dp.SetTimestamp(ts)
return metric
},
want: func() map[uint64]*prompb.TimeSeries {
labels := []prompb.Label{
{Name: model.MetricNameLabel, Value: "test_sum"},
}
return map[uint64]*prompb.TimeSeries{
timeSeriesSignature(labels): {
Labels: labels,
Samples: []prompb.Sample{
{Value: 0, Timestamp: convertTimeStamp(ts)},
},
},
}
},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
metric := tt.metric()
converter := NewPrometheusConverter()
converter.addSumNumberDataPoints(
metric.Sum().DataPoints(),
pcommon.NewResource(),
metric,
Settings{
ExportCreatedMetric: true,
},
metric.Name(),
)
assert.Equal(t, tt.want(), converter.unique)
assert.Empty(t, converter.conflicts)
})
}
}

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storage/remote/otlptranslator/prometheusremotewrite/testutil_test.go Normal file
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// Copyright 2024 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Provenance-includes-location: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/247a9f996e09a83cdc25addf70c05e42b8b30186/pkg/translator/prometheusremotewrite/testutil_test.go
// Provenance-includes-license: Apache-2.0
// Provenance-includes-copyright: Copyright The OpenTelemetry Authors.
package prometheusremotewrite
import (
"strings"
"go.opentelemetry.io/collector/pdata/pcommon"
"go.opentelemetry.io/collector/pdata/pmetric"
)
func getIntGaugeMetric(name string, attributes pcommon.Map, value int64, ts uint64) pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName(name)
dp := metric.SetEmptyGauge().DataPoints().AppendEmpty()
if strings.HasPrefix(name, "staleNaN") {
dp.SetFlags(pmetric.DefaultDataPointFlags.WithNoRecordedValue(true))
}
dp.SetIntValue(value)
attributes.CopyTo(dp.Attributes())
dp.SetStartTimestamp(pcommon.Timestamp(0))
dp.SetTimestamp(pcommon.Timestamp(ts))
return metric
}
func getIntSumMetric(name string, attributes pcommon.Map, value int64, ts uint64) pmetric.Metric {
metric := pmetric.NewMetric()
metric.SetName(name)
metric.SetEmptySum().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
dp := metric.Sum().DataPoints().AppendEmpty()
if strings.HasPrefix(name, "staleNaN") {
dp.SetFlags(pmetric.DefaultDataPointFlags.WithNoRecordedValue(true))
}
dp.SetIntValue(value)
attributes.CopyTo(dp.Attributes())
dp.SetStartTimestamp(pcommon.Timestamp(0))
dp.SetTimestamp(pcommon.Timestamp(ts))
return metric
}