prometheus/storage/local/persistence_test.go

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// Copyright 2014 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 local
import (
"reflect"
"testing"
clientmodel "github.com/prometheus/client_golang/model"
"github.com/prometheus/prometheus/storage/local/codable"
"github.com/prometheus/prometheus/storage/local/index"
"github.com/prometheus/prometheus/storage/metric"
"github.com/prometheus/prometheus/utility/test"
)
func newTestPersistence(t *testing.T) (*persistence, test.Closer) {
dir := test.NewTemporaryDirectory("test_persistence", t)
p, err := newPersistence(dir.Path(), 1024)
if err != nil {
dir.Close()
t.Fatal(err)
}
return p, test.NewCallbackCloser(func() {
p.close()
dir.Close()
})
}
func buildTestChunks() map[clientmodel.Fingerprint][]chunk {
fps := clientmodel.Fingerprints{
clientmodel.Metric{
"label": "value1",
}.Fingerprint(),
clientmodel.Metric{
"label": "value2",
}.Fingerprint(),
clientmodel.Metric{
"label": "value3",
}.Fingerprint(),
}
fpToChunks := map[clientmodel.Fingerprint][]chunk{}
for _, fp := range fps {
fpToChunks[fp] = make([]chunk, 0, 10)
for i := 0; i < 10; i++ {
fpToChunks[fp] = append(fpToChunks[fp], newDeltaEncodedChunk(d1, d1, true).add(&metric.SamplePair{
Timestamp: clientmodel.Timestamp(i),
Value: clientmodel.SampleValue(fp),
})[0])
}
}
return fpToChunks
}
func chunksEqual(c1, c2 chunk) bool {
values2 := c2.values()
for v1 := range c1.values() {
v2 := <-values2
if !v1.Equal(v2) {
return false
}
}
return true
}
func TestPersistChunk(t *testing.T) {
p, closer := newTestPersistence(t)
defer closer.Close()
fpToChunks := buildTestChunks()
for fp, chunks := range fpToChunks {
for _, c := range chunks {
if err := p.persistChunk(fp, c); err != nil {
t.Fatal(err)
}
}
}
for fp, expectedChunks := range fpToChunks {
indexes := make([]int, 0, len(expectedChunks))
for i := range expectedChunks {
indexes = append(indexes, i)
}
actualChunks, err := p.loadChunks(fp, indexes)
if err != nil {
t.Fatal(err)
}
for _, i := range indexes {
if !chunksEqual(expectedChunks[i], actualChunks[i]) {
t.Fatalf("%d. Chunks not equal.", i)
}
}
}
}
type incrementalBatch struct {
fpToMetric index.FingerprintMetricMapping
expectedLnToLvs index.LabelNameLabelValuesMapping
expectedLpToFps index.LabelPairFingerprintsMapping
}
func TestIndexing(t *testing.T) {
batches := []incrementalBatch{
{
fpToMetric: index.FingerprintMetricMapping{
0: {
clientmodel.MetricNameLabel: "metric_0",
"label_1": "value_1",
},
1: {
clientmodel.MetricNameLabel: "metric_0",
"label_2": "value_2",
"label_3": "value_3",
},
2: {
clientmodel.MetricNameLabel: "metric_1",
"label_1": "value_2",
},
},
expectedLnToLvs: index.LabelNameLabelValuesMapping{
clientmodel.MetricNameLabel: codable.LabelValueSet{
"metric_0": struct{}{},
"metric_1": struct{}{},
},
"label_1": codable.LabelValueSet{
"value_1": struct{}{},
"value_2": struct{}{},
},
"label_2": codable.LabelValueSet{
"value_2": struct{}{},
},
"label_3": codable.LabelValueSet{
"value_3": struct{}{},
},
},
expectedLpToFps: index.LabelPairFingerprintsMapping{
metric.LabelPair{
Name: clientmodel.MetricNameLabel,
Value: "metric_0",
}: codable.FingerprintSet{0: struct{}{}, 1: struct{}{}},
metric.LabelPair{
Name: clientmodel.MetricNameLabel,
Value: "metric_1",
}: codable.FingerprintSet{2: struct{}{}},
metric.LabelPair{
Name: "label_1",
Value: "value_1",
}: codable.FingerprintSet{0: struct{}{}},
metric.LabelPair{
Name: "label_1",
Value: "value_2",
}: codable.FingerprintSet{2: struct{}{}},
metric.LabelPair{
Name: "label_2",
Value: "value_2",
}: codable.FingerprintSet{1: struct{}{}},
metric.LabelPair{
Name: "label_3",
Value: "value_3",
}: codable.FingerprintSet{1: struct{}{}},
},
}, {
fpToMetric: index.FingerprintMetricMapping{
3: {
clientmodel.MetricNameLabel: "metric_0",
"label_1": "value_3",
},
4: {
clientmodel.MetricNameLabel: "metric_2",
"label_2": "value_2",
"label_3": "value_1",
},
5: {
clientmodel.MetricNameLabel: "metric_1",
"label_1": "value_3",
},
},
expectedLnToLvs: index.LabelNameLabelValuesMapping{
clientmodel.MetricNameLabel: codable.LabelValueSet{
"metric_0": struct{}{},
"metric_1": struct{}{},
"metric_2": struct{}{},
},
"label_1": codable.LabelValueSet{
"value_1": struct{}{},
"value_2": struct{}{},
"value_3": struct{}{},
},
"label_2": codable.LabelValueSet{
"value_2": struct{}{},
},
"label_3": codable.LabelValueSet{
"value_1": struct{}{},
"value_3": struct{}{},
},
},
expectedLpToFps: index.LabelPairFingerprintsMapping{
metric.LabelPair{
Name: clientmodel.MetricNameLabel,
Value: "metric_0",
}: codable.FingerprintSet{0: struct{}{}, 1: struct{}{}, 3: struct{}{}},
metric.LabelPair{
Name: clientmodel.MetricNameLabel,
Value: "metric_1",
}: codable.FingerprintSet{2: struct{}{}, 5: struct{}{}},
metric.LabelPair{
Name: clientmodel.MetricNameLabel,
Value: "metric_2",
}: codable.FingerprintSet{4: struct{}{}},
metric.LabelPair{
Name: "label_1",
Value: "value_1",
}: codable.FingerprintSet{0: struct{}{}},
metric.LabelPair{
Name: "label_1",
Value: "value_2",
}: codable.FingerprintSet{2: struct{}{}},
metric.LabelPair{
Name: "label_1",
Value: "value_3",
}: codable.FingerprintSet{3: struct{}{}, 5: struct{}{}},
metric.LabelPair{
Name: "label_2",
Value: "value_2",
}: codable.FingerprintSet{1: struct{}{}, 4: struct{}{}},
metric.LabelPair{
Name: "label_3",
Value: "value_1",
}: codable.FingerprintSet{4: struct{}{}},
metric.LabelPair{
Name: "label_3",
Value: "value_3",
}: codable.FingerprintSet{1: struct{}{}},
},
},
}
p, closer := newTestPersistence(t)
defer closer.Close()
indexedFpsToMetrics := index.FingerprintMetricMapping{}
for i, b := range batches {
for fp, m := range b.fpToMetric {
p.indexMetric(m, fp)
if err := p.archiveMetric(fp, m, 1, 2); err != nil {
t.Fatal(err)
}
indexedFpsToMetrics[fp] = m
}
verifyIndexedState(i, t, b, indexedFpsToMetrics, p)
}
for i := len(batches) - 1; i >= 0; i-- {
b := batches[i]
verifyIndexedState(i, t, batches[i], indexedFpsToMetrics, p)
for fp, m := range b.fpToMetric {
p.unindexMetric(m, fp)
unarchived, err := p.unarchiveMetric(fp)
if err != nil {
t.Fatal(err)
}
if !unarchived {
t.Errorf("%d. metric not unarchived", i)
}
delete(indexedFpsToMetrics, fp)
}
}
}
func verifyIndexedState(i int, t *testing.T, b incrementalBatch, indexedFpsToMetrics index.FingerprintMetricMapping, p *persistence) {
p.waitForIndexing()
for fp, m := range indexedFpsToMetrics {
// Compare archived metrics with input metrics.
mOut, err := p.getArchivedMetric(fp)
if err != nil {
t.Fatal(err)
}
if !mOut.Equal(m) {
t.Errorf("%d. %v: Got: %s; want %s", i, fp, mOut, m)
}
// Check that archived metrics are in membership index.
has, first, last, err := p.hasArchivedMetric(fp)
if err != nil {
t.Fatal(err)
}
if !has {
t.Errorf("%d. fingerprint %v not found", i, fp)
}
if first != 1 || last != 2 {
t.Errorf(
"%d. %v: Got first: %d, last %d; want first: %d, last %d",
i, fp, first, last, 1, 2,
)
}
}
// Compare label name -> label values mappings.
for ln, lvs := range b.expectedLnToLvs {
outLvs, err := p.getLabelValuesForLabelName(ln)
if err != nil {
t.Fatal(err)
}
outSet := codable.LabelValueSet{}
for _, lv := range outLvs {
outSet[lv] = struct{}{}
}
if !reflect.DeepEqual(lvs, outSet) {
t.Errorf("%d. label values don't match. Got: %v; want %v", i, outSet, lvs)
}
}
// Compare label pair -> fingerprints mappings.
for lp, fps := range b.expectedLpToFps {
outFps, err := p.getFingerprintsForLabelPair(lp)
if err != nil {
t.Fatal(err)
}
outSet := codable.FingerprintSet{}
for _, fp := range outFps {
outSet[fp] = struct{}{}
}
if !reflect.DeepEqual(fps, outSet) {
t.Errorf("%d. %v: fingerprints don't match. Got: %v; want %v", i, lp, outSet, fps)
}
}
}