prometheus/storage/metric/regressions_test.go
Julius Volz c7c0b33d0b Add regex-matching support for labels.
There are four label-matching ops for selecting timeseries now:

- Equal: =
- NotEqual: !=
- RegexMatch: =~
- RegexNoMatch: !~

Instead of looking up labels by a simple clientmodel.LabelSet (basically
an equals op for every key/value pair in the set), timeseries
fingerprint selection is now done via a list of metric.LabelMatchers.

Change-Id: I510a83f761198e80946146770ebb64e4abc3bb96
2014-04-01 14:24:53 +02:00

87 lines
3.4 KiB
Go

// Copyright 2013 Prometheus Team
// 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 metric
import (
"testing"
clientmodel "github.com/prometheus/client_golang/model"
"github.com/prometheus/prometheus/utility/test"
)
func GetFingerprintsForLabelSetUsesAndForLabelMatchingTests(p MetricPersistence, t test.Tester) {
metrics := []clientmodel.LabelSet{
{clientmodel.MetricNameLabel: "request_metrics_latency_equal_tallying_microseconds", "instance": "http://localhost:9090/metrics.json", "percentile": "0.010000"},
{clientmodel.MetricNameLabel: "requests_metrics_latency_equal_accumulating_microseconds", "instance": "http://localhost:9090/metrics.json", "percentile": "0.010000"},
{clientmodel.MetricNameLabel: "requests_metrics_latency_logarithmic_accumulating_microseconds", "instance": "http://localhost:9090/metrics.json", "percentile": "0.010000"},
{clientmodel.MetricNameLabel: "requests_metrics_latency_logarithmic_tallying_microseconds", "instance": "http://localhost:9090/metrics.json", "percentile": "0.010000"},
{clientmodel.MetricNameLabel: "targets_healthy_scrape_latency_ms", "instance": "http://localhost:9090/metrics.json", "percentile": "0.010000"},
}
for _, metric := range metrics {
m := clientmodel.Metric{}
for k, v := range metric {
m[clientmodel.LabelName(k)] = clientmodel.LabelValue(v)
}
testAppendSamples(p, &clientmodel.Sample{
Value: clientmodel.SampleValue(0.0),
Timestamp: clientmodel.Now(),
Metric: m,
}, t)
}
labelSet := clientmodel.LabelSet{
clientmodel.MetricNameLabel: "targets_healthy_scrape_latency_ms",
"percentile": "0.010000",
}
fingerprints, err := p.GetFingerprintsForLabelMatchers(labelMatchersFromLabelSet(labelSet))
if err != nil {
t.Errorf("could not get labels: %s", err)
}
if len(fingerprints) != 1 {
t.Errorf("did not get a single metric as is expected, got %s", fingerprints)
}
}
// Test Definitions Below
var testLevelDBGetFingerprintsForLabelSetUsesAndForLabelMatching = buildLevelDBTestPersistence("get_fingerprints_for_labelset_uses_and_for_label_matching", GetFingerprintsForLabelSetUsesAndForLabelMatchingTests)
func TestLevelDBGetFingerprintsForLabelSetUsesAndForLabelMatching(t *testing.T) {
testLevelDBGetFingerprintsForLabelSetUsesAndForLabelMatching(t)
}
func BenchmarkLevelDBGetFingerprintsForLabelSetUsesAndForLabelMatching(b *testing.B) {
for i := 0; i < b.N; i++ {
testLevelDBGetFingerprintsForLabelSetUsesAndForLabelMatching(b)
}
}
var testMemoryGetFingerprintsForLabelSetUsesAndForLabelMatching = buildMemoryTestPersistence(GetFingerprintsForLabelSetUsesAndForLabelMatchingTests)
func TestMemoryGetFingerprintsForLabelSetUsesAndForLabelMatching(t *testing.T) {
testMemoryGetFingerprintsForLabelSetUsesAndForLabelMatching(t)
}
func BenchmarkMemoryGetFingerprintsForLabelSetUsesAndLabelMatching(b *testing.B) {
for i := 0; i < b.N; i++ {
testMemoryGetFingerprintsForLabelSetUsesAndForLabelMatching(b)
}
}