1058 lines
30 KiB
Go
1058 lines
30 KiB
Go
// Copyright 2014 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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package local
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import (
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"fmt"
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"math/rand"
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"testing"
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"testing/quick"
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"time"
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"github.com/prometheus/log"
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clientmodel "github.com/prometheus/client_golang/model"
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"github.com/prometheus/prometheus/storage/metric"
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"github.com/prometheus/prometheus/utility/test"
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)
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func TestFingerprintsForLabelMatchers(t *testing.T) {
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storage, closer := NewTestStorage(t, 1)
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defer closer.Close()
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samples := make([]*clientmodel.Sample, 100)
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fingerprints := make(clientmodel.Fingerprints, 100)
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for i := range samples {
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metric := clientmodel.Metric{
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clientmodel.MetricNameLabel: clientmodel.LabelValue(fmt.Sprintf("test_metric_%d", i)),
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"label1": clientmodel.LabelValue(fmt.Sprintf("test_%d", i/10)),
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"label2": clientmodel.LabelValue(fmt.Sprintf("test_%d", (i+5)/10)),
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}
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samples[i] = &clientmodel.Sample{
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Metric: metric,
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Timestamp: clientmodel.Timestamp(i),
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Value: clientmodel.SampleValue(i),
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}
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fingerprints[i] = metric.FastFingerprint()
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}
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for _, s := range samples {
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storage.Append(s)
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}
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storage.WaitForIndexing()
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newMatcher := func(matchType metric.MatchType, name clientmodel.LabelName, value clientmodel.LabelValue) *metric.LabelMatcher {
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lm, err := metric.NewLabelMatcher(matchType, name, value)
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if err != nil {
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t.Fatalf("error creating label matcher: %s", err)
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}
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return lm
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}
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var matcherTests = []struct {
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matchers metric.LabelMatchers
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expected clientmodel.Fingerprints
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}{
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{
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matchers: metric.LabelMatchers{newMatcher(metric.Equal, "label1", "x")},
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expected: fingerprints[:0],
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},
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{
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matchers: metric.LabelMatchers{newMatcher(metric.Equal, "label1", "test_0")},
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expected: fingerprints[:10],
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},
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{
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matchers: metric.LabelMatchers{
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newMatcher(metric.Equal, "label1", "test_0"),
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newMatcher(metric.Equal, "label2", "test_1"),
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},
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expected: fingerprints[5:10],
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},
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{
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matchers: metric.LabelMatchers{newMatcher(metric.NotEqual, "label1", "x")},
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expected: fingerprints,
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},
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{
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matchers: metric.LabelMatchers{newMatcher(metric.NotEqual, "label1", "test_0")},
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expected: fingerprints[10:],
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},
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{
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matchers: metric.LabelMatchers{
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newMatcher(metric.NotEqual, "label1", "test_0"),
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newMatcher(metric.NotEqual, "label1", "test_1"),
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newMatcher(metric.NotEqual, "label1", "test_2"),
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},
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expected: fingerprints[30:],
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},
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{
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matchers: metric.LabelMatchers{newMatcher(metric.RegexMatch, "label1", `test_[3-5]`)},
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expected: fingerprints[30:60],
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},
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{
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matchers: metric.LabelMatchers{newMatcher(metric.RegexNoMatch, "label1", `test_[3-5]`)},
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expected: append(append(clientmodel.Fingerprints{}, fingerprints[:30]...), fingerprints[60:]...),
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},
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{
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matchers: metric.LabelMatchers{
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newMatcher(metric.RegexMatch, "label1", `test_[3-5]`),
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newMatcher(metric.RegexMatch, "label2", `test_[4-6]`),
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},
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expected: fingerprints[35:60],
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},
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{
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matchers: metric.LabelMatchers{
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newMatcher(metric.RegexMatch, "label1", `test_[3-5]`),
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newMatcher(metric.NotEqual, "label2", `test_4`),
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},
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expected: append(append(clientmodel.Fingerprints{}, fingerprints[30:35]...), fingerprints[45:60]...),
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},
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}
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for _, mt := range matcherTests {
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resfps := storage.FingerprintsForLabelMatchers(mt.matchers)
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if len(mt.expected) != len(resfps) {
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t.Fatalf("expected %d matches for %q, found %d", len(mt.expected), mt.matchers, len(resfps))
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}
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for _, fp1 := range resfps {
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found := false
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for _, fp2 := range mt.expected {
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if fp1 == fp2 {
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found = true
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break
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}
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}
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if !found {
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t.Errorf("expected fingerprint %s for %q not in result", fp1, mt.matchers)
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}
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}
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}
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}
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// TestLoop is just a smoke test for the loop method, if we can switch it on and
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// off without disaster.
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func TestLoop(t *testing.T) {
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if testing.Short() {
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t.Skip("Skipping test in short mode.")
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}
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samples := make(clientmodel.Samples, 1000)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Timestamp: clientmodel.Timestamp(2 * i),
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Value: clientmodel.SampleValue(float64(i) * 0.2),
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}
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}
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directory := test.NewTemporaryDirectory("test_storage", t)
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defer directory.Close()
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o := &MemorySeriesStorageOptions{
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MemoryChunks: 50,
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MaxChunksToPersist: 1000000,
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PersistenceRetentionPeriod: 24 * 7 * time.Hour,
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PersistenceStoragePath: directory.Path(),
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CheckpointInterval: 250 * time.Millisecond,
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SyncStrategy: Adaptive,
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}
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storage := NewMemorySeriesStorage(o)
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if err := storage.Start(); err != nil {
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t.Fatalf("Error starting storage: %s", err)
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}
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for _, s := range samples {
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storage.Append(s)
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}
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storage.WaitForIndexing()
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series, _ := storage.(*memorySeriesStorage).fpToSeries.get(clientmodel.Metric{}.FastFingerprint())
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cdsBefore := len(series.chunkDescs)
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time.Sleep(fpMaxWaitDuration + time.Second) // TODO(beorn7): Ugh, need to wait for maintenance to kick in.
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cdsAfter := len(series.chunkDescs)
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storage.Stop()
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if cdsBefore <= cdsAfter {
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t.Errorf(
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"Number of chunk descriptors should have gone down by now. Got before %d, after %d.",
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cdsBefore, cdsAfter,
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)
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}
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}
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func testChunk(t *testing.T, encoding chunkEncoding) {
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samples := make(clientmodel.Samples, 500000)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Timestamp: clientmodel.Timestamp(i),
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Value: clientmodel.SampleValue(float64(i) * 0.2),
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}
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}
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s, closer := NewTestStorage(t, encoding)
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defer closer.Close()
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for _, sample := range samples {
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s.Append(sample)
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}
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s.WaitForIndexing()
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for m := range s.fpToSeries.iter() {
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s.fpLocker.Lock(m.fp)
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var values metric.Values
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for _, cd := range m.series.chunkDescs {
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if cd.isEvicted() {
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continue
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}
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for sample := range cd.c.newIterator().values() {
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values = append(values, *sample)
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}
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}
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for i, v := range values {
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if samples[i].Timestamp != v.Timestamp {
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t.Errorf("%d. Got %v; want %v", i, v.Timestamp, samples[i].Timestamp)
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}
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if samples[i].Value != v.Value {
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t.Errorf("%d. Got %v; want %v", i, v.Value, samples[i].Value)
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}
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}
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s.fpLocker.Unlock(m.fp)
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}
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log.Info("test done, closing")
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}
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func TestChunkType0(t *testing.T) {
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testChunk(t, 0)
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}
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func TestChunkType1(t *testing.T) {
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testChunk(t, 1)
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}
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func testValueAtTime(t *testing.T, encoding chunkEncoding) {
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samples := make(clientmodel.Samples, 10000)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Timestamp: clientmodel.Timestamp(2 * i),
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Value: clientmodel.SampleValue(float64(i) * 0.2),
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}
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}
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s, closer := NewTestStorage(t, encoding)
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defer closer.Close()
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for _, sample := range samples {
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s.Append(sample)
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}
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s.WaitForIndexing()
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fp := clientmodel.Metric{}.FastFingerprint()
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it := s.NewIterator(fp)
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// #1 Exactly on a sample.
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for i, expected := range samples {
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actual := it.ValueAtTime(expected.Timestamp)
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if len(actual) != 1 {
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t.Fatalf("1.%d. Expected exactly one result, got %d.", i, len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("1.%d. Got %v; want %v", i, actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("1.%d. Got %v; want %v", i, actual[0].Value, expected.Value)
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}
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}
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// #2 Between samples.
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for i, expected1 := range samples {
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if i == len(samples)-1 {
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continue
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}
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expected2 := samples[i+1]
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actual := it.ValueAtTime(expected1.Timestamp + 1)
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if len(actual) != 2 {
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t.Fatalf("2.%d. Expected exactly 2 results, got %d.", i, len(actual))
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}
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if expected1.Timestamp != actual[0].Timestamp {
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t.Errorf("2.%d. Got %v; want %v", i, actual[0].Timestamp, expected1.Timestamp)
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}
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if expected1.Value != actual[0].Value {
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t.Errorf("2.%d. Got %v; want %v", i, actual[0].Value, expected1.Value)
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}
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if expected2.Timestamp != actual[1].Timestamp {
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t.Errorf("2.%d. Got %v; want %v", i, actual[1].Timestamp, expected1.Timestamp)
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}
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if expected2.Value != actual[1].Value {
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t.Errorf("2.%d. Got %v; want %v", i, actual[1].Value, expected1.Value)
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}
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}
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// #3 Corner cases: Just before the first sample, just after the last.
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expected := samples[0]
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actual := it.ValueAtTime(expected.Timestamp - 1)
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if len(actual) != 1 {
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t.Fatalf("3.1. Expected exactly one result, got %d.", len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("3.1. Got %v; want %v", actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("3.1. Got %v; want %v", actual[0].Value, expected.Value)
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}
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expected = samples[len(samples)-1]
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actual = it.ValueAtTime(expected.Timestamp + 1)
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if len(actual) != 1 {
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t.Fatalf("3.2. Expected exactly one result, got %d.", len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("3.2. Got %v; want %v", actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("3.2. Got %v; want %v", actual[0].Value, expected.Value)
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}
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}
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func TestValueAtTimeChunkType0(t *testing.T) {
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testValueAtTime(t, 0)
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}
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func TestValueAtTimeChunkType1(t *testing.T) {
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testValueAtTime(t, 1)
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}
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func benchmarkValueAtTime(b *testing.B, encoding chunkEncoding) {
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samples := make(clientmodel.Samples, 10000)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Timestamp: clientmodel.Timestamp(2 * i),
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Value: clientmodel.SampleValue(float64(i) * 0.2),
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}
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}
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s, closer := NewTestStorage(b, encoding)
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defer closer.Close()
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for _, sample := range samples {
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s.Append(sample)
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}
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s.WaitForIndexing()
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fp := clientmodel.Metric{}.FastFingerprint()
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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it := s.NewIterator(fp)
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// #1 Exactly on a sample.
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for i, expected := range samples {
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actual := it.ValueAtTime(expected.Timestamp)
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if len(actual) != 1 {
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b.Fatalf("1.%d. Expected exactly one result, got %d.", i, len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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b.Errorf("1.%d. Got %v; want %v", i, actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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b.Errorf("1.%d. Got %v; want %v", i, actual[0].Value, expected.Value)
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}
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}
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// #2 Between samples.
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for i, expected1 := range samples {
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if i == len(samples)-1 {
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continue
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}
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expected2 := samples[i+1]
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actual := it.ValueAtTime(expected1.Timestamp + 1)
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if len(actual) != 2 {
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b.Fatalf("2.%d. Expected exactly 2 results, got %d.", i, len(actual))
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}
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if expected1.Timestamp != actual[0].Timestamp {
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b.Errorf("2.%d. Got %v; want %v", i, actual[0].Timestamp, expected1.Timestamp)
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}
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if expected1.Value != actual[0].Value {
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b.Errorf("2.%d. Got %v; want %v", i, actual[0].Value, expected1.Value)
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}
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if expected2.Timestamp != actual[1].Timestamp {
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b.Errorf("2.%d. Got %v; want %v", i, actual[1].Timestamp, expected1.Timestamp)
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}
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if expected2.Value != actual[1].Value {
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b.Errorf("2.%d. Got %v; want %v", i, actual[1].Value, expected1.Value)
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}
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}
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}
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}
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func BenchmarkValueAtTimeChunkType0(b *testing.B) {
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benchmarkValueAtTime(b, 0)
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}
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func BenchmarkValueAtTimeChunkType1(b *testing.B) {
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benchmarkValueAtTime(b, 1)
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}
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func testRangeValues(t *testing.T, encoding chunkEncoding) {
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samples := make(clientmodel.Samples, 10000)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Timestamp: clientmodel.Timestamp(2 * i),
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Value: clientmodel.SampleValue(float64(i) * 0.2),
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}
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}
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s, closer := NewTestStorage(t, encoding)
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defer closer.Close()
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for _, sample := range samples {
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s.Append(sample)
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}
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s.WaitForIndexing()
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fp := clientmodel.Metric{}.FastFingerprint()
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it := s.NewIterator(fp)
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// #1 Zero length interval at sample.
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for i, expected := range samples {
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actual := it.RangeValues(metric.Interval{
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OldestInclusive: expected.Timestamp,
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NewestInclusive: expected.Timestamp,
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})
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if len(actual) != 1 {
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t.Fatalf("1.%d. Expected exactly one result, got %d.", i, len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("1.%d. Got %v; want %v.", i, actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("1.%d. Got %v; want %v.", i, actual[0].Value, expected.Value)
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}
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}
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// #2 Zero length interval off sample.
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for i, expected := range samples {
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actual := it.RangeValues(metric.Interval{
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OldestInclusive: expected.Timestamp + 1,
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NewestInclusive: expected.Timestamp + 1,
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})
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if len(actual) != 0 {
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t.Fatalf("2.%d. Expected no result, got %d.", i, len(actual))
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}
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}
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// #3 2sec interval around sample.
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for i, expected := range samples {
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actual := it.RangeValues(metric.Interval{
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OldestInclusive: expected.Timestamp - 1,
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NewestInclusive: expected.Timestamp + 1,
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})
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if len(actual) != 1 {
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t.Fatalf("3.%d. Expected exactly one result, got %d.", i, len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("3.%d. Got %v; want %v.", i, actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("3.%d. Got %v; want %v.", i, actual[0].Value, expected.Value)
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}
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}
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// #4 2sec interval sample to sample.
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for i, expected1 := range samples {
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if i == len(samples)-1 {
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continue
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}
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expected2 := samples[i+1]
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actual := it.RangeValues(metric.Interval{
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OldestInclusive: expected1.Timestamp,
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NewestInclusive: expected1.Timestamp + 2,
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})
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|
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if len(actual) != 2 {
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t.Fatalf("4.%d. Expected exactly 2 results, got %d.", i, len(actual))
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}
|
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if expected1.Timestamp != actual[0].Timestamp {
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t.Errorf("4.%d. Got %v for 1st result; want %v.", i, actual[0].Timestamp, expected1.Timestamp)
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}
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if expected1.Value != actual[0].Value {
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t.Errorf("4.%d. Got %v for 1st result; want %v.", i, actual[0].Value, expected1.Value)
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}
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if expected2.Timestamp != actual[1].Timestamp {
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t.Errorf("4.%d. Got %v for 2nd result; want %v.", i, actual[1].Timestamp, expected2.Timestamp)
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}
|
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if expected2.Value != actual[1].Value {
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t.Errorf("4.%d. Got %v for 2nd result; want %v.", i, actual[1].Value, expected2.Value)
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}
|
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}
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// #5 corner cases: Interval ends at first sample, interval starts
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// at last sample, interval entirely before/after samples.
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expected := samples[0]
|
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actual := it.RangeValues(metric.Interval{
|
|
OldestInclusive: expected.Timestamp - 2,
|
|
NewestInclusive: expected.Timestamp,
|
|
})
|
|
if len(actual) != 1 {
|
|
t.Fatalf("5.1. Expected exactly one result, got %d.", len(actual))
|
|
}
|
|
if expected.Timestamp != actual[0].Timestamp {
|
|
t.Errorf("5.1. Got %v; want %v.", actual[0].Timestamp, expected.Timestamp)
|
|
}
|
|
if expected.Value != actual[0].Value {
|
|
t.Errorf("5.1. Got %v; want %v.", actual[0].Value, expected.Value)
|
|
}
|
|
expected = samples[len(samples)-1]
|
|
actual = it.RangeValues(metric.Interval{
|
|
OldestInclusive: expected.Timestamp,
|
|
NewestInclusive: expected.Timestamp + 2,
|
|
})
|
|
if len(actual) != 1 {
|
|
t.Fatalf("5.2. Expected exactly one result, got %d.", len(actual))
|
|
}
|
|
if expected.Timestamp != actual[0].Timestamp {
|
|
t.Errorf("5.2. Got %v; want %v.", actual[0].Timestamp, expected.Timestamp)
|
|
}
|
|
if expected.Value != actual[0].Value {
|
|
t.Errorf("5.2. Got %v; want %v.", actual[0].Value, expected.Value)
|
|
}
|
|
firstSample := samples[0]
|
|
actual = it.RangeValues(metric.Interval{
|
|
OldestInclusive: firstSample.Timestamp - 4,
|
|
NewestInclusive: firstSample.Timestamp - 2,
|
|
})
|
|
if len(actual) != 0 {
|
|
t.Fatalf("5.3. Expected no results, got %d.", len(actual))
|
|
}
|
|
lastSample := samples[len(samples)-1]
|
|
actual = it.RangeValues(metric.Interval{
|
|
OldestInclusive: lastSample.Timestamp + 2,
|
|
NewestInclusive: lastSample.Timestamp + 4,
|
|
})
|
|
if len(actual) != 0 {
|
|
t.Fatalf("5.3. Expected no results, got %d.", len(actual))
|
|
}
|
|
}
|
|
|
|
func TestRangeValuesChunkType0(t *testing.T) {
|
|
testRangeValues(t, 0)
|
|
}
|
|
|
|
func TestRangeValuesChunkType1(t *testing.T) {
|
|
testRangeValues(t, 1)
|
|
}
|
|
|
|
func benchmarkRangeValues(b *testing.B, encoding chunkEncoding) {
|
|
samples := make(clientmodel.Samples, 10000)
|
|
for i := range samples {
|
|
samples[i] = &clientmodel.Sample{
|
|
Timestamp: clientmodel.Timestamp(2 * i),
|
|
Value: clientmodel.SampleValue(float64(i) * 0.2),
|
|
}
|
|
}
|
|
s, closer := NewTestStorage(b, encoding)
|
|
defer closer.Close()
|
|
|
|
for _, sample := range samples {
|
|
s.Append(sample)
|
|
}
|
|
s.WaitForIndexing()
|
|
|
|
fp := clientmodel.Metric{}.FastFingerprint()
|
|
|
|
b.ResetTimer()
|
|
|
|
for i := 0; i < b.N; i++ {
|
|
|
|
it := s.NewIterator(fp)
|
|
|
|
for _, sample := range samples {
|
|
actual := it.RangeValues(metric.Interval{
|
|
OldestInclusive: sample.Timestamp - 20,
|
|
NewestInclusive: sample.Timestamp + 20,
|
|
})
|
|
|
|
if len(actual) < 10 {
|
|
b.Fatalf("not enough samples found")
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
func BenchmarkRangeValuesChunkType0(b *testing.B) {
|
|
benchmarkRangeValues(b, 0)
|
|
}
|
|
|
|
func BenchmarkRangeValuesChunkType1(b *testing.B) {
|
|
benchmarkRangeValues(b, 1)
|
|
}
|
|
|
|
func testEvictAndPurgeSeries(t *testing.T, encoding chunkEncoding) {
|
|
samples := make(clientmodel.Samples, 10000)
|
|
for i := range samples {
|
|
samples[i] = &clientmodel.Sample{
|
|
Timestamp: clientmodel.Timestamp(2 * i),
|
|
Value: clientmodel.SampleValue(float64(i * i)),
|
|
}
|
|
}
|
|
s, closer := NewTestStorage(t, encoding)
|
|
defer closer.Close()
|
|
|
|
for _, sample := range samples {
|
|
s.Append(sample)
|
|
}
|
|
s.WaitForIndexing()
|
|
|
|
fp := clientmodel.Metric{}.FastFingerprint()
|
|
|
|
// Drop ~half of the chunks.
|
|
s.maintainMemorySeries(fp, 10000)
|
|
it := s.NewIterator(fp)
|
|
actual := it.BoundaryValues(metric.Interval{
|
|
OldestInclusive: 0,
|
|
NewestInclusive: 100000,
|
|
})
|
|
if len(actual) != 2 {
|
|
t.Fatal("expected two results after purging half of series")
|
|
}
|
|
if actual[0].Timestamp < 6000 || actual[0].Timestamp > 10000 {
|
|
t.Errorf("1st timestamp out of expected range: %v", actual[0].Timestamp)
|
|
}
|
|
want := clientmodel.Timestamp(19998)
|
|
if actual[1].Timestamp != want {
|
|
t.Errorf("2nd timestamp: want %v, got %v", want, actual[1].Timestamp)
|
|
}
|
|
|
|
// Drop everything.
|
|
s.maintainMemorySeries(fp, 100000)
|
|
it = s.NewIterator(fp)
|
|
actual = it.BoundaryValues(metric.Interval{
|
|
OldestInclusive: 0,
|
|
NewestInclusive: 100000,
|
|
})
|
|
if len(actual) != 0 {
|
|
t.Fatal("expected zero results after purging the whole series")
|
|
}
|
|
|
|
// Recreate series.
|
|
for _, sample := range samples {
|
|
s.Append(sample)
|
|
}
|
|
s.WaitForIndexing()
|
|
|
|
series, ok := s.fpToSeries.get(fp)
|
|
if !ok {
|
|
t.Fatal("could not find series")
|
|
}
|
|
|
|
// Persist head chunk so we can safely archive.
|
|
series.headChunkClosed = true
|
|
s.maintainMemorySeries(fp, clientmodel.Earliest)
|
|
|
|
// Archive metrics.
|
|
s.fpToSeries.del(fp)
|
|
if err := s.persistence.archiveMetric(
|
|
fp, series.metric, series.firstTime(), series.head().lastTime(),
|
|
); err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
|
|
archived, _, _, err := s.persistence.hasArchivedMetric(fp)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
if !archived {
|
|
t.Fatal("not archived")
|
|
}
|
|
|
|
// Drop ~half of the chunks of an archived series.
|
|
s.maintainArchivedSeries(fp, 10000)
|
|
archived, _, _, err = s.persistence.hasArchivedMetric(fp)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
if !archived {
|
|
t.Fatal("archived series purged although only half of the chunks dropped")
|
|
}
|
|
|
|
// Drop everything.
|
|
s.maintainArchivedSeries(fp, 100000)
|
|
archived, _, _, err = s.persistence.hasArchivedMetric(fp)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
if archived {
|
|
t.Fatal("archived series not dropped")
|
|
}
|
|
|
|
// Recreate series.
|
|
for _, sample := range samples {
|
|
s.Append(sample)
|
|
}
|
|
s.WaitForIndexing()
|
|
|
|
series, ok = s.fpToSeries.get(fp)
|
|
if !ok {
|
|
t.Fatal("could not find series")
|
|
}
|
|
|
|
// Persist head chunk so we can safely archive.
|
|
series.headChunkClosed = true
|
|
s.maintainMemorySeries(fp, clientmodel.Earliest)
|
|
|
|
// Archive metrics.
|
|
s.fpToSeries.del(fp)
|
|
if err := s.persistence.archiveMetric(
|
|
fp, series.metric, series.firstTime(), series.head().lastTime(),
|
|
); err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
|
|
archived, _, _, err = s.persistence.hasArchivedMetric(fp)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
if !archived {
|
|
t.Fatal("not archived")
|
|
}
|
|
|
|
// Unarchive metrics.
|
|
s.getOrCreateSeries(fp, clientmodel.Metric{})
|
|
|
|
series, ok = s.fpToSeries.get(fp)
|
|
if !ok {
|
|
t.Fatal("could not find series")
|
|
}
|
|
archived, _, _, err = s.persistence.hasArchivedMetric(fp)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
if archived {
|
|
t.Fatal("archived")
|
|
}
|
|
|
|
// This will archive again, but must not drop it completely, despite the
|
|
// memorySeries being empty.
|
|
s.maintainMemorySeries(fp, 10000)
|
|
archived, _, _, err = s.persistence.hasArchivedMetric(fp)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
if !archived {
|
|
t.Fatal("series purged completely")
|
|
}
|
|
}
|
|
|
|
func TestEvictAndPurgeSeriesChunkType0(t *testing.T) {
|
|
testEvictAndPurgeSeries(t, 0)
|
|
}
|
|
|
|
func TestEvictAndPurgeSeriesChunkType1(t *testing.T) {
|
|
testEvictAndPurgeSeries(t, 1)
|
|
}
|
|
|
|
func benchmarkAppend(b *testing.B, encoding chunkEncoding) {
|
|
samples := make(clientmodel.Samples, b.N)
|
|
for i := range samples {
|
|
samples[i] = &clientmodel.Sample{
|
|
Metric: clientmodel.Metric{
|
|
clientmodel.MetricNameLabel: clientmodel.LabelValue(fmt.Sprintf("test_metric_%d", i%10)),
|
|
"label1": clientmodel.LabelValue(fmt.Sprintf("test_metric_%d", i%10)),
|
|
"label2": clientmodel.LabelValue(fmt.Sprintf("test_metric_%d", i%10)),
|
|
},
|
|
Timestamp: clientmodel.Timestamp(i),
|
|
Value: clientmodel.SampleValue(i),
|
|
}
|
|
}
|
|
b.ResetTimer()
|
|
s, closer := NewTestStorage(b, encoding)
|
|
defer closer.Close()
|
|
|
|
for _, sample := range samples {
|
|
s.Append(sample)
|
|
}
|
|
}
|
|
|
|
func BenchmarkAppendType0(b *testing.B) {
|
|
benchmarkAppend(b, 0)
|
|
}
|
|
|
|
func BenchmarkAppendType1(b *testing.B) {
|
|
benchmarkAppend(b, 1)
|
|
}
|
|
|
|
// Append a large number of random samples and then check if we can get them out
|
|
// of the storage alright.
|
|
func testFuzz(t *testing.T, encoding chunkEncoding) {
|
|
if testing.Short() {
|
|
t.Skip("Skipping test in short mode.")
|
|
}
|
|
|
|
check := func(seed int64) bool {
|
|
rand.Seed(seed)
|
|
s, c := NewTestStorage(t, encoding)
|
|
defer c.Close()
|
|
|
|
samples := createRandomSamples("test_fuzz", 10000)
|
|
for _, sample := range samples {
|
|
s.Append(sample)
|
|
}
|
|
return verifyStorage(t, s, samples, 24*7*time.Hour)
|
|
}
|
|
|
|
if err := quick.Check(check, nil); err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
}
|
|
|
|
func TestFuzzChunkType0(t *testing.T) {
|
|
testFuzz(t, 0)
|
|
}
|
|
|
|
func TestFuzzChunkType1(t *testing.T) {
|
|
testFuzz(t, 1)
|
|
}
|
|
|
|
// benchmarkFuzz is the benchmark version of testFuzz. The storage options are
|
|
// set such that evictions, checkpoints, and purging will happen concurrently,
|
|
// too. This benchmark will have a very long runtime (up to minutes). You can
|
|
// use it as an actual benchmark. Run it like this:
|
|
//
|
|
// go test -cpu 1,2,4,8 -run=NONE -bench BenchmarkFuzzChunkType -benchmem
|
|
//
|
|
// You can also use it as a test for races. In that case, run it like this (will
|
|
// make things even slower):
|
|
//
|
|
// go test -race -cpu 8 -short -bench BenchmarkFuzzChunkType
|
|
func benchmarkFuzz(b *testing.B, encoding chunkEncoding) {
|
|
*defaultChunkEncoding = int(encoding)
|
|
const samplesPerRun = 100000
|
|
rand.Seed(42)
|
|
directory := test.NewTemporaryDirectory("test_storage", b)
|
|
defer directory.Close()
|
|
o := &MemorySeriesStorageOptions{
|
|
MemoryChunks: 100,
|
|
MaxChunksToPersist: 1000000,
|
|
PersistenceRetentionPeriod: time.Hour,
|
|
PersistenceStoragePath: directory.Path(),
|
|
CheckpointInterval: time.Second,
|
|
SyncStrategy: Adaptive,
|
|
}
|
|
s := NewMemorySeriesStorage(o)
|
|
if err := s.Start(); err != nil {
|
|
b.Fatalf("Error starting storage: %s", err)
|
|
}
|
|
s.Start()
|
|
defer s.Stop()
|
|
|
|
samples := createRandomSamples("benchmark_fuzz", samplesPerRun*b.N)
|
|
|
|
b.ResetTimer()
|
|
|
|
for i := 0; i < b.N; i++ {
|
|
start := samplesPerRun * i
|
|
end := samplesPerRun * (i + 1)
|
|
middle := (start + end) / 2
|
|
for _, sample := range samples[start:middle] {
|
|
s.Append(sample)
|
|
}
|
|
verifyStorage(b, s.(*memorySeriesStorage), samples[:middle], o.PersistenceRetentionPeriod)
|
|
for _, sample := range samples[middle:end] {
|
|
s.Append(sample)
|
|
}
|
|
verifyStorage(b, s.(*memorySeriesStorage), samples[:end], o.PersistenceRetentionPeriod)
|
|
}
|
|
}
|
|
|
|
func BenchmarkFuzzChunkType0(b *testing.B) {
|
|
benchmarkFuzz(b, 0)
|
|
}
|
|
|
|
func BenchmarkFuzzChunkType1(b *testing.B) {
|
|
benchmarkFuzz(b, 1)
|
|
}
|
|
|
|
func createRandomSamples(metricName string, minLen int) clientmodel.Samples {
|
|
type valueCreator func() clientmodel.SampleValue
|
|
type deltaApplier func(clientmodel.SampleValue) clientmodel.SampleValue
|
|
|
|
var (
|
|
maxMetrics = 5
|
|
maxStreakLength = 500
|
|
maxTimeDelta = 10000
|
|
maxTimeDeltaFactor = 10
|
|
timestamp = clientmodel.Now() - clientmodel.Timestamp(maxTimeDelta*maxTimeDeltaFactor*minLen/4) // So that some timestamps are in the future.
|
|
generators = []struct {
|
|
createValue valueCreator
|
|
applyDelta []deltaApplier
|
|
}{
|
|
{ // "Boolean".
|
|
createValue: func() clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Intn(2))
|
|
},
|
|
applyDelta: []deltaApplier{
|
|
func(_ clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Intn(2))
|
|
},
|
|
},
|
|
},
|
|
{ // Integer with int deltas of various byte length.
|
|
createValue: func() clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Int63() - 1<<62)
|
|
},
|
|
applyDelta: []deltaApplier{
|
|
func(v clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Intn(1<<8) - 1<<7 + int(v))
|
|
},
|
|
func(v clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Intn(1<<16) - 1<<15 + int(v))
|
|
},
|
|
func(v clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Int63n(1<<32) - 1<<31 + int64(v))
|
|
},
|
|
},
|
|
},
|
|
{ // Float with float32 and float64 deltas.
|
|
createValue: func() clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.NormFloat64())
|
|
},
|
|
applyDelta: []deltaApplier{
|
|
func(v clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return v + clientmodel.SampleValue(float32(rand.NormFloat64()))
|
|
},
|
|
func(v clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return v + clientmodel.SampleValue(rand.NormFloat64())
|
|
},
|
|
},
|
|
},
|
|
}
|
|
)
|
|
|
|
// Prefill result with two samples with colliding metrics (to test fingerprint mapping).
|
|
result := clientmodel.Samples{
|
|
&clientmodel.Sample{
|
|
Metric: clientmodel.Metric{
|
|
"instance": "ip-10-33-84-73.l05.ams5.s-cloud.net:24483",
|
|
"status": "503",
|
|
},
|
|
Value: 42,
|
|
Timestamp: timestamp,
|
|
},
|
|
&clientmodel.Sample{
|
|
Metric: clientmodel.Metric{
|
|
"instance": "ip-10-33-84-73.l05.ams5.s-cloud.net:24480",
|
|
"status": "500",
|
|
},
|
|
Value: 2010,
|
|
Timestamp: timestamp + 1,
|
|
},
|
|
}
|
|
|
|
metrics := []clientmodel.Metric{}
|
|
for n := rand.Intn(maxMetrics); n >= 0; n-- {
|
|
metrics = append(metrics, clientmodel.Metric{
|
|
clientmodel.MetricNameLabel: clientmodel.LabelValue(metricName),
|
|
clientmodel.LabelName(fmt.Sprintf("labelname_%d", n+1)): clientmodel.LabelValue(fmt.Sprintf("labelvalue_%d", rand.Int())),
|
|
})
|
|
}
|
|
|
|
for len(result) < minLen {
|
|
// Pick a metric for this cycle.
|
|
metric := metrics[rand.Intn(len(metrics))]
|
|
timeDelta := rand.Intn(maxTimeDelta) + 1
|
|
generator := generators[rand.Intn(len(generators))]
|
|
createValue := generator.createValue
|
|
applyDelta := generator.applyDelta[rand.Intn(len(generator.applyDelta))]
|
|
incTimestamp := func() { timestamp += clientmodel.Timestamp(timeDelta * (rand.Intn(maxTimeDeltaFactor) + 1)) }
|
|
switch rand.Intn(4) {
|
|
case 0: // A single sample.
|
|
result = append(result, &clientmodel.Sample{
|
|
Metric: metric,
|
|
Value: createValue(),
|
|
Timestamp: timestamp,
|
|
})
|
|
incTimestamp()
|
|
case 1: // A streak of random sample values.
|
|
for n := rand.Intn(maxStreakLength); n >= 0; n-- {
|
|
result = append(result, &clientmodel.Sample{
|
|
Metric: metric,
|
|
Value: createValue(),
|
|
Timestamp: timestamp,
|
|
})
|
|
incTimestamp()
|
|
}
|
|
case 2: // A streak of sample values with incremental changes.
|
|
value := createValue()
|
|
for n := rand.Intn(maxStreakLength); n >= 0; n-- {
|
|
result = append(result, &clientmodel.Sample{
|
|
Metric: metric,
|
|
Value: value,
|
|
Timestamp: timestamp,
|
|
})
|
|
incTimestamp()
|
|
value = applyDelta(value)
|
|
}
|
|
case 3: // A streak of constant sample values.
|
|
value := createValue()
|
|
for n := rand.Intn(maxStreakLength); n >= 0; n-- {
|
|
result = append(result, &clientmodel.Sample{
|
|
Metric: metric,
|
|
Value: value,
|
|
Timestamp: timestamp,
|
|
})
|
|
incTimestamp()
|
|
}
|
|
}
|
|
}
|
|
|
|
return result
|
|
}
|
|
|
|
func verifyStorage(t testing.TB, s *memorySeriesStorage, samples clientmodel.Samples, maxAge time.Duration) bool {
|
|
s.WaitForIndexing()
|
|
result := true
|
|
for _, i := range rand.Perm(len(samples)) {
|
|
sample := samples[i]
|
|
if sample.Timestamp.Before(clientmodel.TimestampFromTime(time.Now().Add(-maxAge))) {
|
|
continue
|
|
// TODO: Once we have a guaranteed cutoff at the
|
|
// retention period, we can verify here that no results
|
|
// are returned.
|
|
}
|
|
fp, err := s.mapper.mapFP(sample.Metric.FastFingerprint(), sample.Metric)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
p := s.NewPreloader()
|
|
p.PreloadRange(fp, sample.Timestamp, sample.Timestamp, time.Hour)
|
|
found := s.NewIterator(fp).ValueAtTime(sample.Timestamp)
|
|
if len(found) != 1 {
|
|
t.Errorf("Sample %#v: Expected exactly one value, found %d.", sample, len(found))
|
|
result = false
|
|
p.Close()
|
|
continue
|
|
}
|
|
want := sample.Value
|
|
got := found[0].Value
|
|
if want != got || sample.Timestamp != found[0].Timestamp {
|
|
t.Errorf(
|
|
"Value (or timestamp) mismatch, want %f (at time %v), got %f (at time %v).",
|
|
want, sample.Timestamp, got, found[0].Timestamp,
|
|
)
|
|
result = false
|
|
}
|
|
p.Close()
|
|
}
|
|
return result
|
|
}
|