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7c4f877881
* otlptranslator: Harmonize non-UTF8 sanitization w/ naming rules. Harmonize non-UTF8 sanitization w/ Prometheus naming rules. --------- Signed-off-by: Arve Knudsen <arve.knudsen@gmail.com>
443 lines
12 KiB
Go
443 lines
12 KiB
Go
// Copyright 2024 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// Provenance-includes-location: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/debbf30360b8d3a0ded8db09c4419d2a9c99b94a/pkg/translator/prometheusremotewrite/helper_test.go
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// Provenance-includes-license: Apache-2.0
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// Provenance-includes-copyright: Copyright The OpenTelemetry Authors.
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package prometheusremotewrite
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import (
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"context"
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"testing"
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"time"
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"github.com/stretchr/testify/assert"
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"go.opentelemetry.io/collector/pdata/pcommon"
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"go.opentelemetry.io/collector/pdata/pmetric"
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"github.com/prometheus/common/model"
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"github.com/prometheus/prometheus/prompb"
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)
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func TestCreateAttributes(t *testing.T) {
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resourceAttrs := map[string]string{
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"service.name": "service name",
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"service.instance.id": "service ID",
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"existent-attr": "resource value",
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// This one is for testing conflict with metric attribute.
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"metric-attr": "resource value",
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// This one is for testing conflict with auto-generated job attribute.
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"job": "resource value",
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// This one is for testing conflict with auto-generated instance attribute.
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"instance": "resource value",
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}
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resource := pcommon.NewResource()
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for k, v := range resourceAttrs {
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resource.Attributes().PutStr(k, v)
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}
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attrs := pcommon.NewMap()
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attrs.PutStr("metric-attr", "metric value")
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testCases := []struct {
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name string
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promoteResourceAttributes []string
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expectedLabels []prompb.Label
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}{
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{
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name: "Successful conversion without resource attribute promotion",
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promoteResourceAttributes: nil,
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expectedLabels: []prompb.Label{
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{
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Name: "__name__",
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Value: "test_metric",
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},
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{
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Name: "instance",
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Value: "service ID",
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},
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{
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Name: "job",
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Value: "service name",
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},
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{
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Name: "metric_attr",
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Value: "metric value",
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},
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},
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},
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{
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name: "Successful conversion with resource attribute promotion",
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promoteResourceAttributes: []string{"non-existent-attr", "existent-attr"},
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expectedLabels: []prompb.Label{
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{
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Name: "__name__",
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Value: "test_metric",
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},
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{
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Name: "instance",
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Value: "service ID",
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},
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{
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Name: "job",
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Value: "service name",
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},
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{
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Name: "metric_attr",
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Value: "metric value",
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},
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{
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Name: "existent_attr",
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Value: "resource value",
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},
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},
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},
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{
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name: "Successful conversion with resource attribute promotion, conflicting resource attributes are ignored",
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promoteResourceAttributes: []string{"non-existent-attr", "existent-attr", "metric-attr", "job", "instance"},
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expectedLabels: []prompb.Label{
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{
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Name: "__name__",
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Value: "test_metric",
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},
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{
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Name: "instance",
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Value: "service ID",
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},
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{
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Name: "job",
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Value: "service name",
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},
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{
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Name: "existent_attr",
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Value: "resource value",
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},
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{
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Name: "metric_attr",
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Value: "metric value",
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},
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},
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},
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{
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name: "Successful conversion with resource attribute promotion, attributes are only promoted once",
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promoteResourceAttributes: []string{"existent-attr", "existent-attr"},
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expectedLabels: []prompb.Label{
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{
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Name: "__name__",
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Value: "test_metric",
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},
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{
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Name: "instance",
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Value: "service ID",
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},
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{
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Name: "job",
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Value: "service name",
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},
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{
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Name: "existent_attr",
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Value: "resource value",
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},
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{
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Name: "metric_attr",
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Value: "metric value",
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},
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},
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},
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}
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for _, tc := range testCases {
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t.Run(tc.name, func(t *testing.T) {
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settings := Settings{
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PromoteResourceAttributes: tc.promoteResourceAttributes,
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}
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lbls := createAttributes(resource, attrs, settings, nil, false, model.MetricNameLabel, "test_metric")
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assert.ElementsMatch(t, lbls, tc.expectedLabels)
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})
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}
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}
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func Test_convertTimeStamp(t *testing.T) {
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tests := []struct {
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name string
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arg pcommon.Timestamp
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want int64
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}{
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{"zero", 0, 0},
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{"1ms", 1_000_000, 1},
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{"1s", pcommon.Timestamp(time.Unix(1, 0).UnixNano()), 1000},
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}
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for _, tt := range tests {
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t.Run(tt.name, func(t *testing.T) {
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got := convertTimeStamp(tt.arg)
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assert.Equal(t, tt.want, got)
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})
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}
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}
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func TestPrometheusConverter_AddSummaryDataPoints(t *testing.T) {
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ts := pcommon.Timestamp(time.Now().UnixNano())
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tests := []struct {
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name string
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metric func() pmetric.Metric
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want func() map[uint64]*prompb.TimeSeries
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}{
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{
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name: "summary with start time",
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metric: func() pmetric.Metric {
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metric := pmetric.NewMetric()
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metric.SetName("test_summary")
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metric.SetEmptySummary()
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dp := metric.Summary().DataPoints().AppendEmpty()
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dp.SetTimestamp(ts)
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dp.SetStartTimestamp(ts)
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return metric
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},
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want: func() map[uint64]*prompb.TimeSeries {
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labels := []prompb.Label{
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{Name: model.MetricNameLabel, Value: "test_summary" + countStr},
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}
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createdLabels := []prompb.Label{
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{Name: model.MetricNameLabel, Value: "test_summary" + createdSuffix},
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}
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sumLabels := []prompb.Label{
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{Name: model.MetricNameLabel, Value: "test_summary" + sumStr},
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}
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return map[uint64]*prompb.TimeSeries{
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timeSeriesSignature(labels): {
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Labels: labels,
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Samples: []prompb.Sample{
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{Value: 0, Timestamp: convertTimeStamp(ts)},
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},
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},
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timeSeriesSignature(sumLabels): {
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Labels: sumLabels,
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Samples: []prompb.Sample{
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{Value: 0, Timestamp: convertTimeStamp(ts)},
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},
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},
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timeSeriesSignature(createdLabels): {
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Labels: createdLabels,
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Samples: []prompb.Sample{
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{Value: float64(convertTimeStamp(ts)), Timestamp: convertTimeStamp(ts)},
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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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name: "summary without start time",
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metric: func() pmetric.Metric {
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metric := pmetric.NewMetric()
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metric.SetName("test_summary")
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metric.SetEmptySummary()
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dp := metric.Summary().DataPoints().AppendEmpty()
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dp.SetTimestamp(ts)
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return metric
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},
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want: func() map[uint64]*prompb.TimeSeries {
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labels := []prompb.Label{
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{Name: model.MetricNameLabel, Value: "test_summary" + countStr},
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}
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sumLabels := []prompb.Label{
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{Name: model.MetricNameLabel, Value: "test_summary" + sumStr},
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}
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return map[uint64]*prompb.TimeSeries{
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timeSeriesSignature(labels): {
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Labels: labels,
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Samples: []prompb.Sample{
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{Value: 0, Timestamp: convertTimeStamp(ts)},
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},
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},
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timeSeriesSignature(sumLabels): {
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Labels: sumLabels,
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Samples: []prompb.Sample{
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{Value: 0, Timestamp: convertTimeStamp(ts)},
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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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for _, tt := range tests {
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t.Run(tt.name, func(t *testing.T) {
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metric := tt.metric()
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converter := NewPrometheusConverter()
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converter.addSummaryDataPoints(
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context.Background(),
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metric.Summary().DataPoints(),
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pcommon.NewResource(),
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Settings{
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ExportCreatedMetric: true,
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},
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metric.Name(),
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)
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assert.Equal(t, tt.want(), converter.unique)
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assert.Empty(t, converter.conflicts)
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})
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}
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}
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func TestPrometheusConverter_AddHistogramDataPoints(t *testing.T) {
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ts := pcommon.Timestamp(time.Now().UnixNano())
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tests := []struct {
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name string
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metric func() pmetric.Metric
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want func() map[uint64]*prompb.TimeSeries
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}{
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{
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name: "histogram with start time",
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metric: func() pmetric.Metric {
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metric := pmetric.NewMetric()
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metric.SetName("test_hist")
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metric.SetEmptyHistogram().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
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pt := metric.Histogram().DataPoints().AppendEmpty()
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pt.SetTimestamp(ts)
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pt.SetStartTimestamp(ts)
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return metric
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},
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want: func() map[uint64]*prompb.TimeSeries {
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labels := []prompb.Label{
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{Name: model.MetricNameLabel, Value: "test_hist" + countStr},
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}
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createdLabels := []prompb.Label{
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{Name: model.MetricNameLabel, Value: "test_hist" + createdSuffix},
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}
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infLabels := []prompb.Label{
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{Name: model.MetricNameLabel, Value: "test_hist_bucket"},
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{Name: model.BucketLabel, Value: "+Inf"},
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}
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return map[uint64]*prompb.TimeSeries{
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timeSeriesSignature(infLabels): {
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Labels: infLabels,
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Samples: []prompb.Sample{
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{Value: 0, Timestamp: convertTimeStamp(ts)},
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},
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},
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timeSeriesSignature(labels): {
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Labels: labels,
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Samples: []prompb.Sample{
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{Value: 0, Timestamp: convertTimeStamp(ts)},
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},
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},
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timeSeriesSignature(createdLabels): {
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Labels: createdLabels,
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Samples: []prompb.Sample{
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{Value: float64(convertTimeStamp(ts)), Timestamp: convertTimeStamp(ts)},
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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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name: "histogram without start time",
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metric: func() pmetric.Metric {
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metric := pmetric.NewMetric()
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metric.SetName("test_hist")
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metric.SetEmptyHistogram().SetAggregationTemporality(pmetric.AggregationTemporalityCumulative)
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pt := metric.Histogram().DataPoints().AppendEmpty()
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pt.SetTimestamp(ts)
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return metric
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},
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want: func() map[uint64]*prompb.TimeSeries {
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labels := []prompb.Label{
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{Name: model.MetricNameLabel, Value: "test_hist" + countStr},
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}
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infLabels := []prompb.Label{
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{Name: model.MetricNameLabel, Value: "test_hist_bucket"},
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{Name: model.BucketLabel, Value: "+Inf"},
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}
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return map[uint64]*prompb.TimeSeries{
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timeSeriesSignature(infLabels): {
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Labels: infLabels,
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Samples: []prompb.Sample{
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{Value: 0, Timestamp: convertTimeStamp(ts)},
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},
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},
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timeSeriesSignature(labels): {
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Labels: labels,
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Samples: []prompb.Sample{
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{Value: 0, Timestamp: convertTimeStamp(ts)},
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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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for _, tt := range tests {
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t.Run(tt.name, func(t *testing.T) {
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metric := tt.metric()
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converter := NewPrometheusConverter()
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converter.addHistogramDataPoints(
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context.Background(),
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metric.Histogram().DataPoints(),
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pcommon.NewResource(),
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Settings{
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ExportCreatedMetric: true,
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},
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metric.Name(),
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)
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assert.Equal(t, tt.want(), converter.unique)
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assert.Empty(t, converter.conflicts)
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})
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}
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}
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func TestGetPromExemplars(t *testing.T) {
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ctx := context.Background()
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everyN := &everyNTimes{n: 1}
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t.Run("Exemplars with int value", func(t *testing.T) {
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pt := pmetric.NewNumberDataPoint()
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exemplar := pt.Exemplars().AppendEmpty()
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exemplar.SetTimestamp(pcommon.Timestamp(time.Now().UnixNano()))
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exemplar.SetIntValue(42)
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exemplars, err := getPromExemplars(ctx, everyN, pt)
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assert.NoError(t, err)
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assert.Len(t, exemplars, 1)
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assert.Equal(t, float64(42), exemplars[0].Value)
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})
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t.Run("Exemplars with double value", func(t *testing.T) {
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pt := pmetric.NewNumberDataPoint()
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exemplar := pt.Exemplars().AppendEmpty()
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exemplar.SetTimestamp(pcommon.Timestamp(time.Now().UnixNano()))
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exemplar.SetDoubleValue(69.420)
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exemplars, err := getPromExemplars(ctx, everyN, pt)
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assert.NoError(t, err)
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assert.Len(t, exemplars, 1)
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assert.Equal(t, 69.420, exemplars[0].Value)
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})
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t.Run("Exemplars with unsupported value type", func(t *testing.T) {
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pt := pmetric.NewNumberDataPoint()
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exemplar := pt.Exemplars().AppendEmpty()
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exemplar.SetTimestamp(pcommon.Timestamp(time.Now().UnixNano()))
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_, err := getPromExemplars(ctx, everyN, pt)
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assert.Error(t, err)
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})
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}
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