opentelemetry-collector/exporter/prometheusexporter/accumulator_test.go

372 lines
13 KiB
Go

// Copyright The OpenTelemetry 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.
package prometheusexporter
import (
"log"
"testing"
"time"
"github.com/stretchr/testify/require"
"go.uber.org/zap"
"go.opentelemetry.io/collector/model/pdata"
)
func TestInvalidDataType(t *testing.T) {
a := newAccumulator(zap.NewNop(), 1*time.Hour).(*lastValueAccumulator)
metric := pdata.NewMetric()
metric.SetDataType(-100)
n := a.addMetric(metric, pdata.NewInstrumentationLibrary(), time.Now())
require.Zero(t, n)
}
func TestAccumulateDeltaAggregation(t *testing.T) {
tests := []struct {
name string
fillMetric func(time.Time, pdata.Metric)
}{
{
name: "IntSum",
fillMetric: func(ts time.Time, metric pdata.Metric) {
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeIntSum)
metric.IntSum().SetAggregationTemporality(pdata.AggregationTemporalityDelta)
dp := metric.IntSum().DataPoints().AppendEmpty()
dp.SetValue(42)
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
{
name: "Sum",
fillMetric: func(ts time.Time, metric pdata.Metric) {
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeSum)
metric.Sum().SetAggregationTemporality(pdata.AggregationTemporalityDelta)
dp := metric.Sum().DataPoints().AppendEmpty()
dp.SetValue(42.42)
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
{
name: "IntHistogram",
fillMetric: func(ts time.Time, metric pdata.Metric) {
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeIntHistogram)
metric.IntHistogram().SetAggregationTemporality(pdata.AggregationTemporalityDelta)
dp := metric.IntHistogram().DataPoints().AppendEmpty()
dp.SetBucketCounts([]uint64{5, 2})
dp.SetCount(7)
dp.SetExplicitBounds([]float64{1.2, 10.0})
dp.SetSum(42)
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
{
name: "Histogram",
fillMetric: func(ts time.Time, metric pdata.Metric) {
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeHistogram)
metric.Histogram().SetAggregationTemporality(pdata.AggregationTemporalityDelta)
metric.SetDescription("test description")
dp := metric.Histogram().DataPoints().AppendEmpty()
dp.SetBucketCounts([]uint64{5, 2})
dp.SetCount(7)
dp.SetExplicitBounds([]float64{3.5, 10.0})
dp.SetSum(42.42)
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
resourceMetrics := pdata.NewResourceMetrics()
ilm := resourceMetrics.InstrumentationLibraryMetrics().AppendEmpty()
ilm.InstrumentationLibrary().SetName("test")
tt.fillMetric(time.Now(), ilm.Metrics().AppendEmpty())
a := newAccumulator(zap.NewNop(), 1*time.Hour).(*lastValueAccumulator)
n := a.Accumulate(resourceMetrics)
require.Equal(t, 0, n)
signature := timeseriesSignature(ilm.InstrumentationLibrary().Name(), ilm.Metrics().At(0), pdata.NewStringMap())
v, ok := a.registeredMetrics.Load(signature)
require.False(t, ok)
require.Nil(t, v)
})
}
}
func TestAccumulateMetrics(t *testing.T) {
tests := []struct {
name string
metric func(time.Time, float64, pdata.MetricSlice)
}{
{
name: "IntGauge",
metric: func(ts time.Time, v float64, metrics pdata.MetricSlice) {
metric := metrics.AppendEmpty()
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeIntGauge)
metric.SetDescription("test description")
dp := metric.IntGauge().DataPoints().AppendEmpty()
dp.SetValue(int64(v))
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
{
name: "DoubleGauge",
metric: func(ts time.Time, v float64, metrics pdata.MetricSlice) {
metric := metrics.AppendEmpty()
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeDoubleGauge)
metric.SetDescription("test description")
dp := metric.DoubleGauge().DataPoints().AppendEmpty()
dp.SetValue(v)
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
{
name: "IntSum",
metric: func(ts time.Time, v float64, metrics pdata.MetricSlice) {
metric := metrics.AppendEmpty()
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeIntSum)
metric.IntSum().SetIsMonotonic(false)
metric.IntSum().SetAggregationTemporality(pdata.AggregationTemporalityCumulative)
metric.SetDescription("test description")
dp := metric.IntSum().DataPoints().AppendEmpty()
dp.SetValue(int64(v))
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
{
name: "Sum",
metric: func(ts time.Time, v float64, metrics pdata.MetricSlice) {
metric := metrics.AppendEmpty()
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeSum)
metric.Sum().SetIsMonotonic(false)
metric.Sum().SetAggregationTemporality(pdata.AggregationTemporalityCumulative)
metric.SetDescription("test description")
dp := metric.Sum().DataPoints().AppendEmpty()
dp.SetValue(v)
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
{
name: "MonotonicIntSum",
metric: func(ts time.Time, v float64, metrics pdata.MetricSlice) {
metric := metrics.AppendEmpty()
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeIntSum)
metric.IntSum().SetIsMonotonic(true)
metric.IntSum().SetAggregationTemporality(pdata.AggregationTemporalityCumulative)
metric.SetDescription("test description")
dp := metric.IntSum().DataPoints().AppendEmpty()
dp.SetValue(int64(v))
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
{
name: "MonotonicSum",
metric: func(ts time.Time, v float64, metrics pdata.MetricSlice) {
metric := metrics.AppendEmpty()
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeSum)
metric.Sum().SetIsMonotonic(true)
metric.Sum().SetAggregationTemporality(pdata.AggregationTemporalityCumulative)
metric.SetDescription("test description")
dp := metric.Sum().DataPoints().AppendEmpty()
dp.SetValue(v)
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
{
name: "IntHistogram",
metric: func(ts time.Time, v float64, metrics pdata.MetricSlice) {
metric := metrics.AppendEmpty()
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeIntHistogram)
metric.IntHistogram().SetAggregationTemporality(pdata.AggregationTemporalityCumulative)
metric.SetDescription("test description")
dp := metric.IntHistogram().DataPoints().AppendEmpty()
dp.SetBucketCounts([]uint64{5, 2})
dp.SetCount(7)
dp.SetExplicitBounds([]float64{1.2, 10.0})
dp.SetSum(int64(v))
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
{
name: "Histogram",
metric: func(ts time.Time, v float64, metrics pdata.MetricSlice) {
metric := metrics.AppendEmpty()
metric.SetName("test_metric")
metric.SetDataType(pdata.MetricDataTypeHistogram)
metric.Histogram().SetAggregationTemporality(pdata.AggregationTemporalityCumulative)
metric.SetDescription("test description")
dp := metric.Histogram().DataPoints().AppendEmpty()
dp.SetBucketCounts([]uint64{5, 2})
dp.SetCount(7)
dp.SetExplicitBounds([]float64{3.5, 10.0})
dp.SetSum(v)
dp.LabelsMap().Insert("label_1", "1")
dp.LabelsMap().Insert("label_2", "2")
dp.SetTimestamp(pdata.TimestampFromTime(ts))
},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
ts1 := time.Now().Add(-3 * time.Second)
ts2 := time.Now().Add(-2 * time.Second)
ts3 := time.Now().Add(-1 * time.Second)
resourceMetrics2 := pdata.NewResourceMetrics()
ilm2 := resourceMetrics2.InstrumentationLibraryMetrics().AppendEmpty()
ilm2.InstrumentationLibrary().SetName("test")
tt.metric(ts2, 21, ilm2.Metrics())
tt.metric(ts1, 13, ilm2.Metrics())
a := newAccumulator(zap.NewNop(), 1*time.Hour).(*lastValueAccumulator)
// 2 metric arrived
n := a.Accumulate(resourceMetrics2)
require.Equal(t, 1, n)
m2Labels, _, m2Value, m2Temporality, m2IsMonotonic := getMerticProperties(ilm2.Metrics().At(0))
signature := timeseriesSignature(ilm2.InstrumentationLibrary().Name(), ilm2.Metrics().At(0), m2Labels)
m, ok := a.registeredMetrics.Load(signature)
require.True(t, ok)
v := m.(*accumulatedValue)
vLabels, vTS, vValue, vTemporality, vIsMonotonic := getMerticProperties(ilm2.Metrics().At(0))
require.Equal(t, v.instrumentationLibrary.Name(), "test")
require.Equal(t, v.value.DataType(), ilm2.Metrics().At(0).DataType())
vLabels.Range(func(k, v string) bool {
r, _ := m2Labels.Get(k)
require.Equal(t, r, v)
return true
})
require.Equal(t, m2Labels.Len(), vLabels.Len())
require.Equal(t, m2Value, vValue)
require.Equal(t, ts2.Unix(), vTS.Unix())
require.Greater(t, v.updated.Unix(), vTS.Unix())
require.Equal(t, m2Temporality, vTemporality)
require.Equal(t, m2IsMonotonic, vIsMonotonic)
// 3 metrics arrived
resourceMetrics3 := pdata.NewResourceMetrics()
ilm3 := resourceMetrics3.InstrumentationLibraryMetrics().AppendEmpty()
ilm3.InstrumentationLibrary().SetName("test")
tt.metric(ts2, 21, ilm3.Metrics())
tt.metric(ts3, 34, ilm3.Metrics())
tt.metric(ts1, 13, ilm3.Metrics())
_, _, m3Value, _, _ := getMerticProperties(ilm3.Metrics().At(1))
n = a.Accumulate(resourceMetrics3)
require.Equal(t, 2, n)
m, ok = a.registeredMetrics.Load(signature)
require.True(t, ok)
v = m.(*accumulatedValue)
_, vTS, vValue, _, _ = getMerticProperties(v.value)
require.Equal(t, m3Value, vValue)
require.Equal(t, ts3.Unix(), vTS.Unix())
})
}
}
func getMerticProperties(metric pdata.Metric) (
labels pdata.StringMap,
ts time.Time,
value float64,
temporality pdata.AggregationTemporality,
isMonotonic bool,
) {
switch metric.DataType() {
case pdata.MetricDataTypeIntGauge:
labels = metric.IntGauge().DataPoints().At(0).LabelsMap()
ts = metric.IntGauge().DataPoints().At(0).Timestamp().AsTime()
value = float64(metric.IntGauge().DataPoints().At(0).Value())
temporality = pdata.AggregationTemporalityUnspecified
isMonotonic = false
case pdata.MetricDataTypeIntSum:
labels = metric.IntSum().DataPoints().At(0).LabelsMap()
ts = metric.IntSum().DataPoints().At(0).Timestamp().AsTime()
value = float64(metric.IntSum().DataPoints().At(0).Value())
temporality = metric.IntSum().AggregationTemporality()
isMonotonic = metric.IntSum().IsMonotonic()
case pdata.MetricDataTypeDoubleGauge:
labels = metric.DoubleGauge().DataPoints().At(0).LabelsMap()
ts = metric.DoubleGauge().DataPoints().At(0).Timestamp().AsTime()
value = metric.DoubleGauge().DataPoints().At(0).Value()
temporality = pdata.AggregationTemporalityUnspecified
isMonotonic = false
case pdata.MetricDataTypeSum:
labels = metric.Sum().DataPoints().At(0).LabelsMap()
ts = metric.Sum().DataPoints().At(0).Timestamp().AsTime()
value = metric.Sum().DataPoints().At(0).Value()
temporality = metric.Sum().AggregationTemporality()
isMonotonic = metric.Sum().IsMonotonic()
case pdata.MetricDataTypeIntHistogram:
labels = metric.IntHistogram().DataPoints().At(0).LabelsMap()
ts = metric.IntHistogram().DataPoints().At(0).Timestamp().AsTime()
value = float64(metric.IntHistogram().DataPoints().At(0).Sum())
temporality = metric.IntHistogram().AggregationTemporality()
isMonotonic = true
case pdata.MetricDataTypeHistogram:
labels = metric.Histogram().DataPoints().At(0).LabelsMap()
ts = metric.Histogram().DataPoints().At(0).Timestamp().AsTime()
value = metric.Histogram().DataPoints().At(0).Sum()
temporality = metric.Histogram().AggregationTemporality()
isMonotonic = true
default:
log.Panicf("Invalid data type %s", metric.DataType().String())
}
return
}