mirror of https://github.com/prometheus/prometheus
Jan Fajerski
3 months ago
114 changed files with 4954 additions and 1066 deletions
@ -0,0 +1,2 @@
|
||||
scrape_configs: |
||||
- job_name: prometheus |
||||
@ -0,0 +1,4 @@
|
||||
global: |
||||
metric_name_validation_scheme: utf8 |
||||
scrape_configs: |
||||
- job_name: prometheus |
||||
@ -0,0 +1,5 @@
|
||||
global: |
||||
metric_name_validation_scheme: utf8 |
||||
scrape_configs: |
||||
- job_name: prometheus |
||||
metric_name_validation_scheme: legacy |
||||
@ -0,0 +1,3 @@
|
||||
scrape_configs: |
||||
- job_name: prometheus |
||||
metric_name_validation_scheme: utf8 |
||||
@ -0,0 +1,84 @@
|
||||
# Test for __name__ label drop. |
||||
load 5m |
||||
metric{env="1"} 0 60 120 |
||||
another_metric{env="1"} 60 120 180 |
||||
|
||||
# Does not drop __name__ for vector selector |
||||
eval instant at 15m metric{env="1"} |
||||
metric{env="1"} 120 |
||||
|
||||
# Drops __name__ for unary operators |
||||
eval instant at 15m -metric |
||||
{env="1"} -120 |
||||
|
||||
# Drops __name__ for binary operators |
||||
eval instant at 15m metric + another_metric |
||||
{env="1"} 300 |
||||
|
||||
# Does not drop __name__ for binary comparison operators |
||||
eval instant at 15m metric <= another_metric |
||||
metric{env="1"} 120 |
||||
|
||||
# Drops __name__ for binary comparison operators with "bool" modifier |
||||
eval instant at 15m metric <= bool another_metric |
||||
{env="1"} 1 |
||||
|
||||
# Drops __name__ for vector-scalar operations |
||||
eval instant at 15m metric * 2 |
||||
{env="1"} 240 |
||||
|
||||
# Drops __name__ for instant-vector functions |
||||
eval instant at 15m clamp(metric, 0, 100) |
||||
{env="1"} 100 |
||||
|
||||
# Drops __name__ for range-vector functions |
||||
eval instant at 15m rate(metric{env="1"}[10m]) |
||||
{env="1"} 0.2 |
||||
|
||||
# Does not drop __name__ for last_over_time function |
||||
eval instant at 15m last_over_time(metric{env="1"}[10m]) |
||||
metric{env="1"} 120 |
||||
|
||||
# Drops name for other _over_time functions |
||||
eval instant at 15m max_over_time(metric{env="1"}[10m]) |
||||
{env="1"} 120 |
||||
|
||||
# Allows relabeling (to-be-dropped) __name__ via label_replace |
||||
eval instant at 15m label_replace(rate({env="1"}[10m]), "my_name", "rate_$1", "__name__", "(.+)") |
||||
{my_name="rate_metric", env="1"} 0.2 |
||||
{my_name="rate_another_metric", env="1"} 0.2 |
||||
|
||||
# Allows preserving __name__ via label_replace |
||||
eval instant at 15m label_replace(rate({env="1"}[10m]), "__name__", "rate_$1", "__name__", "(.+)") |
||||
rate_metric{env="1"} 0.2 |
||||
rate_another_metric{env="1"} 0.2 |
||||
|
||||
# Allows relabeling (to-be-dropped) __name__ via label_join |
||||
eval instant at 15m label_join(rate({env="1"}[10m]), "my_name", "_", "__name__") |
||||
{my_name="metric", env="1"} 0.2 |
||||
{my_name="another_metric", env="1"} 0.2 |
||||
|
||||
# Allows preserving __name__ via label_join |
||||
eval instant at 15m label_join(rate({env="1"}[10m]), "__name__", "_", "__name__", "env") |
||||
metric_1{env="1"} 0.2 |
||||
another_metric_1{env="1"} 0.2 |
||||
|
||||
# Does not drop metric names fro aggregation operators |
||||
eval instant at 15m sum by (__name__, env) (metric{env="1"}) |
||||
metric{env="1"} 120 |
||||
|
||||
# Aggregation operators by __name__ lead to duplicate labelset errors (aggregation is partitioned by not yet removed __name__ label) |
||||
# This is an accidental side effect of delayed __name__ label dropping |
||||
eval_fail instant at 15m sum by (__name__) (rate({env="1"}[10m])) |
||||
|
||||
# Aggregation operators aggregate metrics with same labelset and to-be-dropped names |
||||
# This is an accidental side effect of delayed __name__ label dropping |
||||
eval instant at 15m sum(rate({env="1"}[10m])) by (env) |
||||
{env="1"} 0.4 |
||||
|
||||
# Aggregationk operators propagate __name__ label dropping information |
||||
eval instant at 15m topk(10, sum by (__name__, env) (metric{env="1"})) |
||||
metric{env="1"} 120 |
||||
|
||||
eval instant at 15m topk(10, sum by (__name__, env) (rate(metric{env="1"}[10m]))) |
||||
{env="1"} 0.2 |
||||
@ -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) |
||||
}) |
||||
} |
||||
} |
||||
@ -0,0 +1,258 @@
|
||||
// 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) |
||||
}) |
||||
} |
||||
} |
||||
@ -0,0 +1,55 @@
|
||||
// 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 |
||||
} |
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in new issue