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dcfd09c801
If the metrics exported by a process already contain any of a target's base labels (such as "job" or "instance", but also any manually assigned target-group label), don't overwrite that label, but instead add a new label consisting of the original label name prepended with "exporter_". This is to accomodate intermediate exporter jobs, which might indicate e.g. the jobs and instances for which they are exporting data.
217 lines
6.7 KiB
Go
217 lines
6.7 KiB
Go
// Copyright 2013 Prometheus Team
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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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package format
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import (
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"container/list"
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"fmt"
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"github.com/prometheus/prometheus/model"
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"github.com/prometheus/prometheus/utility/test"
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"os"
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"path"
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"testing"
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"time"
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)
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func testProcessor002Process(t test.Tester) {
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var scenarios = []struct {
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in string
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baseLabels model.LabelSet
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out model.Samples
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err error
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}{
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{
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in: "empty.json",
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err: fmt.Errorf("EOF"),
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},
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{
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in: "test0_0_1-0_0_2.json",
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baseLabels: model.LabelSet{
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model.JobLabel: "batch_exporter",
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},
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out: model.Samples{
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model.Sample{
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Metric: model.Metric{"service": "zed", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job", "exporter_job": "batch_exporter"},
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Value: 25,
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},
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model.Sample{
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Metric: model.Metric{"service": "bar", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job", "exporter_job": "batch_exporter"},
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Value: 25,
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},
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model.Sample{
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Metric: model.Metric{"service": "foo", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job", "exporter_job": "batch_exporter"},
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Value: 25,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
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Value: 0.0459814091918713,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
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Value: 78.48563317257356,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
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Value: 15.890724674774395,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
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Value: 0.0459814091918713,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
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Value: 78.48563317257356,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
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Value: 15.890724674774395,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
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Value: 0.6120456642749681,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
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Value: 97.31798360385088,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
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Value: 84.63044031436561,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
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Value: 1.355915069887731,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
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Value: 109.89202084295582,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
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Value: 160.21100853053224,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
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Value: 1.772733213161236,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
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Value: 109.99626121011262,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
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Value: 172.49828748957728,
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},
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},
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},
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}
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for i, scenario := range scenarios {
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inputChannel := make(chan Result, 1024)
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defer func(c chan Result) {
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close(c)
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}(inputChannel)
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reader, err := os.Open(path.Join("fixtures", scenario.in))
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if err != nil {
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t.Fatalf("%d. couldn't open scenario input file %s: %s", scenario.in, err)
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}
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err = Processor002.Process(reader, time.Now(), scenario.baseLabels, inputChannel)
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if !test.ErrorEqual(scenario.err, err) {
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t.Errorf("%d. expected err of %s, got %s", i, scenario.err, err)
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continue
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}
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delivered := model.Samples{}
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for len(inputChannel) != 0 {
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result := <-inputChannel
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if result.Err != nil {
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t.Fatalf("%d. expected no error, got: %s", i, result.Err)
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}
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delivered = append(delivered, result.Samples...)
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}
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if len(delivered) != len(scenario.out) {
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t.Errorf("%d. expected output length of %d, got %d", i, len(scenario.out), len(delivered))
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continue
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}
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expectedElements := list.New()
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for _, j := range scenario.out {
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expectedElements.PushBack(j)
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}
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for j := 0; j < len(delivered); j++ {
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actual := delivered[j]
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found := false
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for element := expectedElements.Front(); element != nil && found == false; element = element.Next() {
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candidate := element.Value.(model.Sample)
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if candidate.Value != actual.Value {
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continue
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}
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if len(candidate.Metric) != len(actual.Metric) {
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continue
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}
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labelsMatch := false
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for key, value := range candidate.Metric {
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actualValue, ok := actual.Metric[key]
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if !ok {
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break
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}
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if actualValue == value {
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labelsMatch = true
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break
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}
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}
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if !labelsMatch {
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continue
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}
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// XXX: Test time.
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found = true
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expectedElements.Remove(element)
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}
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if !found {
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t.Errorf("%d.%d. expected to find %s among candidate, absent", i, j, actual)
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}
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}
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}
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}
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func TestProcessor002Process(t *testing.T) {
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testProcessor002Process(t)
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}
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func BenchmarkProcessor002Process(b *testing.B) {
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for i := 0; i < b.N; i++ {
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testProcessor002Process(b)
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}
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}
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