prometheus/storage/local/storage_test.go

940 lines
27 KiB
Go

// Copyright 2014 The Prometheus Authors
// 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 (
"fmt"
"math/rand"
"testing"
"testing/quick"
"time"
"github.com/prometheus/log"
clientmodel "github.com/prometheus/client_golang/model"
"github.com/prometheus/prometheus/storage/metric"
"github.com/prometheus/prometheus/utility/test"
)
func TestGetFingerprintsForLabelMatchers(t *testing.T) {
storage, closer := NewTestStorage(t, 1)
defer closer.Close()
samples := make([]*clientmodel.Sample, 100)
fingerprints := make(clientmodel.Fingerprints, 100)
for i := range samples {
metric := clientmodel.Metric{
clientmodel.MetricNameLabel: clientmodel.LabelValue(fmt.Sprintf("test_metric_%d", i)),
"label1": clientmodel.LabelValue(fmt.Sprintf("test_%d", i/10)),
"label2": clientmodel.LabelValue(fmt.Sprintf("test_%d", (i+5)/10)),
}
samples[i] = &clientmodel.Sample{
Metric: metric,
Timestamp: clientmodel.Timestamp(i),
Value: clientmodel.SampleValue(i),
}
fingerprints[i] = metric.FastFingerprint()
}
for _, s := range samples {
storage.Append(s)
}
storage.WaitForIndexing()
newMatcher := func(matchType metric.MatchType, name clientmodel.LabelName, value clientmodel.LabelValue) *metric.LabelMatcher {
lm, err := metric.NewLabelMatcher(matchType, name, value)
if err != nil {
t.Fatalf("error creating label matcher: %s", err)
}
return lm
}
var matcherTests = []struct {
matchers metric.LabelMatchers
expected clientmodel.Fingerprints
}{
{
matchers: metric.LabelMatchers{newMatcher(metric.Equal, "label1", "x")},
expected: fingerprints[:0],
},
{
matchers: metric.LabelMatchers{newMatcher(metric.Equal, "label1", "test_0")},
expected: fingerprints[:10],
},
{
matchers: metric.LabelMatchers{
newMatcher(metric.Equal, "label1", "test_0"),
newMatcher(metric.Equal, "label2", "test_1"),
},
expected: fingerprints[5:10],
},
{
matchers: metric.LabelMatchers{newMatcher(metric.NotEqual, "label1", "x")},
expected: fingerprints,
},
{
matchers: metric.LabelMatchers{newMatcher(metric.NotEqual, "label1", "test_0")},
expected: fingerprints[10:],
},
{
matchers: metric.LabelMatchers{
newMatcher(metric.NotEqual, "label1", "test_0"),
newMatcher(metric.NotEqual, "label1", "test_1"),
newMatcher(metric.NotEqual, "label1", "test_2"),
},
expected: fingerprints[30:],
},
{
matchers: metric.LabelMatchers{newMatcher(metric.RegexMatch, "label1", `test_[3-5]`)},
expected: fingerprints[30:60],
},
{
matchers: metric.LabelMatchers{newMatcher(metric.RegexNoMatch, "label1", `test_[3-5]`)},
expected: append(append(clientmodel.Fingerprints{}, fingerprints[:30]...), fingerprints[60:]...),
},
{
matchers: metric.LabelMatchers{
newMatcher(metric.RegexMatch, "label1", `test_[3-5]`),
newMatcher(metric.RegexMatch, "label2", `test_[4-6]`),
},
expected: fingerprints[35:60],
},
{
matchers: metric.LabelMatchers{
newMatcher(metric.RegexMatch, "label1", `test_[3-5]`),
newMatcher(metric.NotEqual, "label2", `test_4`),
},
expected: append(append(clientmodel.Fingerprints{}, fingerprints[30:35]...), fingerprints[45:60]...),
},
}
for _, mt := range matcherTests {
resfps := storage.GetFingerprintsForLabelMatchers(mt.matchers)
if len(mt.expected) != len(resfps) {
t.Fatalf("expected %d matches for %q, found %d", len(mt.expected), mt.matchers, len(resfps))
}
for _, fp1 := range resfps {
found := false
for _, fp2 := range mt.expected {
if fp1 == fp2 {
found = true
break
}
}
if !found {
t.Errorf("expected fingerprint %s for %q not in result", fp1, mt.matchers)
}
}
}
}
// TestLoop is just a smoke test for the loop method, if we can switch it on and
// off without disaster.
func TestLoop(t *testing.T) {
if testing.Short() {
t.Skip("Skipping test in short mode.")
}
samples := make(clientmodel.Samples, 1000)
for i := range samples {
samples[i] = &clientmodel.Sample{
Timestamp: clientmodel.Timestamp(2 * i),
Value: clientmodel.SampleValue(float64(i) * 0.2),
}
}
directory := test.NewTemporaryDirectory("test_storage", t)
defer directory.Close()
o := &MemorySeriesStorageOptions{
MemoryChunks: 50,
MaxChunksToPersist: 1000000,
PersistenceRetentionPeriod: 24 * 7 * time.Hour,
PersistenceStoragePath: directory.Path(),
CheckpointInterval: 250 * time.Millisecond,
SyncStrategy: Adaptive,
}
storage := NewMemorySeriesStorage(o)
if err := storage.Start(); err != nil {
t.Fatalf("Error starting storage: %s", err)
}
for _, s := range samples {
storage.Append(s)
}
storage.WaitForIndexing()
series, _ := storage.(*memorySeriesStorage).fpToSeries.get(clientmodel.Metric{}.FastFingerprint())
cdsBefore := len(series.chunkDescs)
time.Sleep(fpMaxWaitDuration + time.Second) // TODO(beorn7): Ugh, need to wait for maintenance to kick in.
cdsAfter := len(series.chunkDescs)
storage.Stop()
if cdsBefore <= cdsAfter {
t.Errorf(
"Number of chunk descriptors should have gone down by now. Got before %d, after %d.",
cdsBefore, cdsAfter,
)
}
}
func testChunk(t *testing.T, encoding chunkEncoding) {
samples := make(clientmodel.Samples, 500000)
for i := range samples {
samples[i] = &clientmodel.Sample{
Timestamp: clientmodel.Timestamp(i),
Value: clientmodel.SampleValue(float64(i) * 0.2),
}
}
s, closer := NewTestStorage(t, encoding)
defer closer.Close()
for _, sample := range samples {
s.Append(sample)
}
s.WaitForIndexing()
for m := range s.fpToSeries.iter() {
s.fpLocker.Lock(m.fp)
var values metric.Values
for _, cd := range m.series.chunkDescs {
if cd.isEvicted() {
continue
}
for sample := range cd.chunk.values() {
values = append(values, *sample)
}
}
for i, v := range values {
if samples[i].Timestamp != v.Timestamp {
t.Errorf("%d. Got %v; want %v", i, v.Timestamp, samples[i].Timestamp)
}
if samples[i].Value != v.Value {
t.Errorf("%d. Got %v; want %v", i, v.Value, samples[i].Value)
}
}
s.fpLocker.Unlock(m.fp)
}
log.Info("test done, closing")
}
func TestChunkType0(t *testing.T) {
testChunk(t, 0)
}
func TestChunkType1(t *testing.T) {
testChunk(t, 1)
}
func testGetValueAtTime(t *testing.T, encoding chunkEncoding) {
samples := make(clientmodel.Samples, 1000)
for i := range samples {
samples[i] = &clientmodel.Sample{
Timestamp: clientmodel.Timestamp(2 * i),
Value: clientmodel.SampleValue(float64(i) * 0.2),
}
}
s, closer := NewTestStorage(t, encoding)
defer closer.Close()
for _, sample := range samples {
s.Append(sample)
}
s.WaitForIndexing()
fp := clientmodel.Metric{}.FastFingerprint()
it := s.NewIterator(fp)
// #1 Exactly on a sample.
for i, expected := range samples {
actual := it.GetValueAtTime(expected.Timestamp)
if len(actual) != 1 {
t.Fatalf("1.%d. Expected exactly one result, got %d.", i, len(actual))
}
if expected.Timestamp != actual[0].Timestamp {
t.Errorf("1.%d. Got %v; want %v", i, actual[0].Timestamp, expected.Timestamp)
}
if expected.Value != actual[0].Value {
t.Errorf("1.%d. Got %v; want %v", i, actual[0].Value, expected.Value)
}
}
// #2 Between samples.
for i, expected1 := range samples {
if i == len(samples)-1 {
continue
}
expected2 := samples[i+1]
actual := it.GetValueAtTime(expected1.Timestamp + 1)
if len(actual) != 2 {
t.Fatalf("2.%d. Expected exactly 2 results, got %d.", i, len(actual))
}
if expected1.Timestamp != actual[0].Timestamp {
t.Errorf("2.%d. Got %v; want %v", i, actual[0].Timestamp, expected1.Timestamp)
}
if expected1.Value != actual[0].Value {
t.Errorf("2.%d. Got %v; want %v", i, actual[0].Value, expected1.Value)
}
if expected2.Timestamp != actual[1].Timestamp {
t.Errorf("2.%d. Got %v; want %v", i, actual[1].Timestamp, expected1.Timestamp)
}
if expected2.Value != actual[1].Value {
t.Errorf("2.%d. Got %v; want %v", i, actual[1].Value, expected1.Value)
}
}
// #3 Corner cases: Just before the first sample, just after the last.
expected := samples[0]
actual := it.GetValueAtTime(expected.Timestamp - 1)
if len(actual) != 1 {
t.Fatalf("3.1. Expected exactly one result, got %d.", len(actual))
}
if expected.Timestamp != actual[0].Timestamp {
t.Errorf("3.1. Got %v; want %v", actual[0].Timestamp, expected.Timestamp)
}
if expected.Value != actual[0].Value {
t.Errorf("3.1. Got %v; want %v", actual[0].Value, expected.Value)
}
expected = samples[len(samples)-1]
actual = it.GetValueAtTime(expected.Timestamp + 1)
if len(actual) != 1 {
t.Fatalf("3.2. Expected exactly one result, got %d.", len(actual))
}
if expected.Timestamp != actual[0].Timestamp {
t.Errorf("3.2. Got %v; want %v", actual[0].Timestamp, expected.Timestamp)
}
if expected.Value != actual[0].Value {
t.Errorf("3.2. Got %v; want %v", actual[0].Value, expected.Value)
}
}
func TestGetValueAtTimeChunkType0(t *testing.T) {
testGetValueAtTime(t, 0)
}
func TestGetValueAtTimeChunkType1(t *testing.T) {
testGetValueAtTime(t, 1)
}
func testGetRangeValues(t *testing.T, encoding chunkEncoding) {
samples := make(clientmodel.Samples, 1000)
for i := range samples {
samples[i] = &clientmodel.Sample{
Timestamp: clientmodel.Timestamp(2 * i),
Value: clientmodel.SampleValue(float64(i) * 0.2),
}
}
s, closer := NewTestStorage(t, encoding)
defer closer.Close()
for _, sample := range samples {
s.Append(sample)
}
s.WaitForIndexing()
fp := clientmodel.Metric{}.FastFingerprint()
it := s.NewIterator(fp)
// #1 Zero length interval at sample.
for i, expected := range samples {
actual := it.GetRangeValues(metric.Interval{
OldestInclusive: expected.Timestamp,
NewestInclusive: expected.Timestamp,
})
if len(actual) != 1 {
t.Fatalf("1.%d. Expected exactly one result, got %d.", i, len(actual))
}
if expected.Timestamp != actual[0].Timestamp {
t.Errorf("1.%d. Got %v; want %v.", i, actual[0].Timestamp, expected.Timestamp)
}
if expected.Value != actual[0].Value {
t.Errorf("1.%d. Got %v; want %v.", i, actual[0].Value, expected.Value)
}
}
// #2 Zero length interval off sample.
for i, expected := range samples {
actual := it.GetRangeValues(metric.Interval{
OldestInclusive: expected.Timestamp + 1,
NewestInclusive: expected.Timestamp + 1,
})
if len(actual) != 0 {
t.Fatalf("2.%d. Expected no result, got %d.", i, len(actual))
}
}
// #3 2sec interval around sample.
for i, expected := range samples {
actual := it.GetRangeValues(metric.Interval{
OldestInclusive: expected.Timestamp - 1,
NewestInclusive: expected.Timestamp + 1,
})
if len(actual) != 1 {
t.Fatalf("3.%d. Expected exactly one result, got %d.", i, len(actual))
}
if expected.Timestamp != actual[0].Timestamp {
t.Errorf("3.%d. Got %v; want %v.", i, actual[0].Timestamp, expected.Timestamp)
}
if expected.Value != actual[0].Value {
t.Errorf("3.%d. Got %v; want %v.", i, actual[0].Value, expected.Value)
}
}
// #4 2sec interval sample to sample.
for i, expected1 := range samples {
if i == len(samples)-1 {
continue
}
expected2 := samples[i+1]
actual := it.GetRangeValues(metric.Interval{
OldestInclusive: expected1.Timestamp,
NewestInclusive: expected1.Timestamp + 2,
})
if len(actual) != 2 {
t.Fatalf("4.%d. Expected exactly 2 results, got %d.", i, len(actual))
}
if expected1.Timestamp != actual[0].Timestamp {
t.Errorf("4.%d. Got %v for 1st result; want %v.", i, actual[0].Timestamp, expected1.Timestamp)
}
if expected1.Value != actual[0].Value {
t.Errorf("4.%d. Got %v for 1st result; want %v.", i, actual[0].Value, expected1.Value)
}
if expected2.Timestamp != actual[1].Timestamp {
t.Errorf("4.%d. Got %v for 2nd result; want %v.", i, actual[1].Timestamp, expected2.Timestamp)
}
if expected2.Value != actual[1].Value {
t.Errorf("4.%d. Got %v for 2nd result; want %v.", i, actual[1].Value, expected2.Value)
}
}
// #5 corner cases: Interval ends at first sample, interval starts
// at last sample, interval entirely before/after samples.
expected := samples[0]
actual := it.GetRangeValues(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.GetRangeValues(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.GetRangeValues(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.GetRangeValues(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 TestGetRangeValuesChunkType0(t *testing.T) {
testGetRangeValues(t, 0)
}
func TestGetRangeValuesChunkType1(t *testing.T) {
testGetRangeValues(t, 1)
}
func testEvictAndPurgeSeries(t *testing.T, encoding chunkEncoding) {
samples := make(clientmodel.Samples, 1000)
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, 1000)
it := s.NewIterator(fp)
actual := it.GetBoundaryValues(metric.Interval{
OldestInclusive: 0,
NewestInclusive: 10000,
})
if len(actual) != 2 {
t.Fatal("expected two results after purging half of series")
}
if actual[0].Timestamp < 600 || actual[0].Timestamp > 1000 {
t.Errorf("1st timestamp out of expected range: %v", actual[0].Timestamp)
}
want := clientmodel.Timestamp(1998)
if actual[1].Timestamp != want {
t.Errorf("2nd timestamp: want %v, got %v", want, actual[1].Timestamp)
}
// Drop everything.
s.maintainMemorySeries(fp, 10000)
it = s.NewIterator(fp)
actual = it.GetBoundaryValues(metric.Interval{
OldestInclusive: 0,
NewestInclusive: 10000,
})
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, 1000)
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, 10000)
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, 1000)
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", 1000)
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).GetValueAtTime(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
}