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telemetry_test.go
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telemetry_test.go
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// Copyright The OpenTelemetry Authors
// SPDX-License-Identifier: Apache-2.0
package groupbyattrsprocessor
import (
"context"
"testing"
"github.com/stretchr/testify/require"
"go.opentelemetry.io/collector/component"
"go.opentelemetry.io/collector/processor"
"go.opentelemetry.io/collector/processor/processortest"
"go.opentelemetry.io/otel/attribute"
"go.opentelemetry.io/otel/sdk/metric"
"go.opentelemetry.io/otel/sdk/metric/metricdata"
"go.opentelemetry.io/otel/sdk/metric/metricdata/metricdatatest"
"github.com/open-telemetry/opentelemetry-collector-contrib/processor/groupbyattrsprocessor/internal/metadata"
)
type testTelemetry struct {
reader *metric.ManualReader
meterProvider *metric.MeterProvider
}
type expectedMetrics struct {
mNumGroupedSpans int64
mNumNonGroupedSpans int64
mDistSpanGroups int64
mNumGroupedLogs int64
mNumNonGroupedLogs int64
mDistLogGroups int64
mNumGroupedMetrics int64
mNumNonGroupedMetrics int64
mDistMetricGroups int64
}
func setupTelemetry() testTelemetry {
reader := metric.NewManualReader()
return testTelemetry{
reader: reader,
meterProvider: metric.NewMeterProvider(metric.WithReader(reader)),
}
}
func (tt *testTelemetry) assertMetrics(t *testing.T, expected expectedMetrics) {
var md metricdata.ResourceMetrics
require.NoError(t, tt.reader.Collect(context.Background(), &md))
if expected.mNumGroupedLogs > 0 {
name := "processor/groupbyattrs/num_grouped_logs"
got := tt.getMetric(name, md)
want := metricdata.Metrics{
Name: name,
Description: "Number of logs that had attributes grouped",
Unit: "1",
Data: metricdata.Sum[int64]{
Temporality: metricdata.CumulativeTemporality,
IsMonotonic: true,
DataPoints: []metricdata.DataPoint[int64]{
{
Value: expected.mNumGroupedLogs,
},
},
},
}
metricdatatest.AssertEqual(t, want, got, metricdatatest.IgnoreTimestamp())
}
if expected.mNumGroupedMetrics > 0 {
name := "processor/groupbyattrs/num_grouped_metrics"
got := tt.getMetric(name, md)
want := metricdata.Metrics{
Name: name,
Description: "Number of metrics that had attributes grouped",
Unit: "1",
Data: metricdata.Sum[int64]{
Temporality: metricdata.CumulativeTemporality,
IsMonotonic: true,
DataPoints: []metricdata.DataPoint[int64]{
{
Value: expected.mNumGroupedMetrics,
},
},
},
}
metricdatatest.AssertEqual(t, want, got, metricdatatest.IgnoreTimestamp())
}
if expected.mNumGroupedSpans > 0 {
name := "processor/groupbyattrs/num_grouped_spans"
got := tt.getMetric(name, md)
want := metricdata.Metrics{
Name: name,
Description: "Number of spans that had attributes grouped",
Unit: "1",
Data: metricdata.Sum[int64]{
Temporality: metricdata.CumulativeTemporality,
IsMonotonic: true,
DataPoints: []metricdata.DataPoint[int64]{
{
Value: expected.mNumGroupedSpans,
},
},
},
}
metricdatatest.AssertEqual(t, want, got, metricdatatest.IgnoreTimestamp())
}
if expected.mNumNonGroupedLogs > 0 {
name := "processor/groupbyattrs/num_non_grouped_logs"
got := tt.getMetric(name, md)
want := metricdata.Metrics{
Name: name,
Description: "Number of logs that did not have attributes grouped",
Unit: "1",
Data: metricdata.Sum[int64]{
Temporality: metricdata.CumulativeTemporality,
IsMonotonic: true,
DataPoints: []metricdata.DataPoint[int64]{
{
Value: expected.mNumNonGroupedLogs,
},
},
},
}
metricdatatest.AssertEqual(t, want, got, metricdatatest.IgnoreTimestamp())
}
if expected.mNumNonGroupedMetrics > 0 {
name := "processor/groupbyattrs/num_non_grouped_metrics"
got := tt.getMetric(name, md)
want := metricdata.Metrics{
Name: name,
Description: "Number of metrics that did not have attributes grouped",
Unit: "1",
Data: metricdata.Sum[int64]{
Temporality: metricdata.CumulativeTemporality,
IsMonotonic: true,
DataPoints: []metricdata.DataPoint[int64]{
{
Value: expected.mNumNonGroupedMetrics,
},
},
},
}
metricdatatest.AssertEqual(t, want, got, metricdatatest.IgnoreTimestamp())
}
if expected.mNumNonGroupedSpans > 0 {
name := "processor/groupbyattrs/num_non_grouped_spans"
got := tt.getMetric(name, md)
want := metricdata.Metrics{
Name: name,
Description: "Number of spans that did not have attributes grouped",
Unit: "1",
Data: metricdata.Sum[int64]{
Temporality: metricdata.CumulativeTemporality,
IsMonotonic: true,
DataPoints: []metricdata.DataPoint[int64]{
{
Value: expected.mNumNonGroupedSpans,
},
},
},
}
metricdatatest.AssertEqual(t, want, got, metricdatatest.IgnoreTimestamp())
}
if expected.mDistLogGroups > 0 {
name := "processor/groupbyattrs/log_groups"
got := tt.getMetric(name, md)
want := metricdata.Metrics{
Name: name,
Description: "Distribution of groups extracted for logs",
Unit: "1",
Data: metricdata.Histogram[int64]{
Temporality: metricdata.CumulativeTemporality,
DataPoints: []metricdata.HistogramDataPoint[int64]{
{
Attributes: *attribute.EmptySet(),
Bounds: []float64{0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000},
BucketCounts: []uint64{0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
Count: 1,
Min: metricdata.NewExtrema(expected.mDistLogGroups),
Max: metricdata.NewExtrema(expected.mDistLogGroups),
Sum: expected.mDistLogGroups,
},
},
},
}
metricdatatest.AssertEqual(t, want, got, metricdatatest.IgnoreTimestamp(), metricdatatest.IgnoreExemplars())
}
if expected.mDistMetricGroups > 0 {
name := "processor/groupbyattrs/metric_groups"
got := tt.getMetric(name, md)
want := metricdata.Metrics{
Name: name,
Description: "Distribution of groups extracted for metrics",
Unit: "1",
Data: metricdata.Histogram[int64]{
Temporality: metricdata.CumulativeTemporality,
DataPoints: []metricdata.HistogramDataPoint[int64]{
{
Attributes: *attribute.EmptySet(),
Bounds: []float64{0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000},
BucketCounts: []uint64{0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
Count: 2,
Min: metricdata.NewExtrema(expected.mDistMetricGroups),
Max: metricdata.NewExtrema(expected.mDistMetricGroups),
Sum: 2 * expected.mDistMetricGroups,
},
},
},
}
metricdatatest.AssertEqual(t, want, got, metricdatatest.IgnoreTimestamp(), metricdatatest.IgnoreExemplars())
}
if expected.mDistSpanGroups > 0 {
name := "processor/groupbyattrs/span_groups"
got := tt.getMetric(name, md)
want := metricdata.Metrics{
Name: name,
Description: "Distribution of groups extracted for spans",
Unit: "1",
Data: metricdata.Histogram[int64]{
Temporality: metricdata.CumulativeTemporality,
DataPoints: []metricdata.HistogramDataPoint[int64]{
{
Attributes: *attribute.EmptySet(),
Bounds: []float64{0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000},
BucketCounts: []uint64{0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
Count: 1,
Min: metricdata.NewExtrema(expected.mDistSpanGroups),
Max: metricdata.NewExtrema(expected.mDistSpanGroups),
Sum: expected.mDistSpanGroups,
},
},
},
}
metricdatatest.AssertEqual(t, want, got, metricdatatest.IgnoreTimestamp(), metricdatatest.IgnoreExemplars())
}
}
func (tt *testTelemetry) NewProcessorCreateSettings() processor.CreateSettings {
settings := processortest.NewNopCreateSettings()
settings.MeterProvider = tt.meterProvider
settings.ID = component.NewID(metadata.Type)
return settings
}
func (tt *testTelemetry) getMetric(name string, got metricdata.ResourceMetrics) metricdata.Metrics {
for _, sm := range got.ScopeMetrics {
for _, m := range sm.Metrics {
if m.Name == name {
return m
}
}
}
return metricdata.Metrics{}
}