prometheus/storage/local/storage_test.go
Bjoern Rabenstein 622e8350cd Fix a bug handling freshly unarchived series.
Usually, if you unarchive a series, it is to add something to it,
which will create a new head chunk. However, if a series in
unarchived, and before anything is added to it, it is handled by the
maintenance loop, it will be archived again. In that case, we have to
load the chunkDescs to know the lastTime of the series to be
archived. Usually, this case will happen only rarely (as a race, has
never happened so far, possibly because the locking around unarchiving
and the subsequent sample append is smart enough). However, during
crash recovery, we sometimes treat series as "freshly unarchived"
without directly appending a sample. We might add more cases of that
type later, so better deal with archiving properly and load chunkDescs
if required.
2015-01-08 16:25:50 +01:00

659 lines
20 KiB
Go

// 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 (
"fmt"
"math/rand"
"testing"
"testing/quick"
"time"
"github.com/golang/glog"
clientmodel "github.com/prometheus/client_golang/model"
"github.com/prometheus/prometheus/storage/metric"
"github.com/prometheus/prometheus/utility/test"
)
func TestGetFingerprintsForLabelMatchers(t *testing.T) {
}
// 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) {
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,
PersistenceRetentionPeriod: 24 * 7 * time.Hour,
PersistenceStoragePath: directory.Path(),
CheckpointInterval: 250 * time.Millisecond,
}
storage, err := NewMemorySeriesStorage(o)
if err != nil {
t.Fatalf("Error creating storage: %s", err)
}
storage.Start()
storage.AppendSamples(samples)
time.Sleep(time.Second)
storage.Stop()
}
func TestChunk(t *testing.T) {
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)
defer closer.Close()
s.AppendSamples(samples)
for m := range s.(*memorySeriesStorage).fpToSeries.iter() {
s.(*memorySeriesStorage).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.(*memorySeriesStorage).fpLocker.Unlock(m.fp)
}
glog.Info("test done, closing")
}
func TestGetValueAtTime(t *testing.T) {
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)
defer closer.Close()
s.AppendSamples(samples)
fp := clientmodel.Metric{}.Fingerprint()
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 TestGetRangeValues(t *testing.T) {
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)
defer closer.Close()
s.AppendSamples(samples)
fp := clientmodel.Metric{}.Fingerprint()
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 TestEvictAndPurgeSeries(t *testing.T) {
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)
defer closer.Close()
ms := s.(*memorySeriesStorage) // Going to test the internal purgeSeries method.
s.AppendSamples(samples)
fp := clientmodel.Metric{}.Fingerprint()
// Purge ~half of the chunks.
ms.purgeSeries(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 < 800 || 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)
}
// Purge everything.
ms.purgeSeries(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.
s.AppendSamples(samples)
series, ok := ms.fpToSeries.get(fp)
if !ok {
t.Fatal("could not find series")
}
// Persist head chunk so we can safely archive.
series.headChunkPersisted = true
ms.persistQueue <- persistRequest{fp, series.head()}
time.Sleep(time.Second) // Give time for persisting to happen.
// Archive metrics.
ms.fpToSeries.del(fp)
if err := ms.persistence.archiveMetric(
fp, series.metric, series.firstTime(), series.head().lastTime(),
); err != nil {
t.Fatal(err)
}
archived, _, _, err := ms.persistence.hasArchivedMetric(fp)
if err != nil {
t.Fatal(err)
}
if !archived {
t.Fatal("not archived")
}
// Purge ~half of the chunks of an archived series.
ms.purgeSeries(fp, 1000)
archived, _, _, err = ms.persistence.hasArchivedMetric(fp)
if err != nil {
t.Fatal(err)
}
if !archived {
t.Fatal("archived series dropped although only half of the chunks purged")
}
// Purge everything.
ms.purgeSeries(fp, 10000)
archived, _, _, err = ms.persistence.hasArchivedMetric(fp)
if err != nil {
t.Fatal(err)
}
if archived {
t.Fatal("archived series not dropped")
}
}
func BenchmarkAppend(b *testing.B) {
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)
defer closer.Close()
s.AppendSamples(samples)
}
// 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) {
if testing.Short() {
t.Skip("Skipping test in short mode.")
}
check := func(seed int64) bool {
rand.Seed(seed)
s, c := NewTestStorage(t)
defer c.Close()
samples := createRandomSamples()
s.AppendSamples(samples)
return verifyStorage(t, s, samples, 24*7*time.Hour)
}
if err := quick.Check(check, nil); err != nil {
t.Fatal(err)
}
}
// BenchmarkFuzz is the benchmark version of TestFuzz. However, it will run
// several append and verify operations in parallel, if GOMAXPROC is set
// accordingly. Also, 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 -short -bench BenchmarkFuzz -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 BenchmarkFuzz
func BenchmarkFuzz(b *testing.B) {
b.StopTimer()
rand.Seed(42)
directory := test.NewTemporaryDirectory("test_storage", b)
defer directory.Close()
o := &MemorySeriesStorageOptions{
MemoryChunks: 100,
PersistenceRetentionPeriod: time.Hour,
PersistenceStoragePath: directory.Path(),
CheckpointInterval: 3 * time.Second,
}
s, err := NewMemorySeriesStorage(o)
if err != nil {
b.Fatalf("Error creating storage: %s", err)
}
s.Start()
defer s.Stop()
b.StartTimer()
b.RunParallel(func(pb *testing.PB) {
var allSamples clientmodel.Samples
for pb.Next() {
newSamples := createRandomSamples()
allSamples = append(allSamples, newSamples[:len(newSamples)/2]...)
s.AppendSamples(newSamples[:len(newSamples)/2])
verifyStorage(b, s, allSamples, o.PersistenceRetentionPeriod)
allSamples = append(allSamples, newSamples[len(newSamples)/2:]...)
s.AppendSamples(newSamples[len(newSamples)/2:])
verifyStorage(b, s, allSamples, o.PersistenceRetentionPeriod)
}
})
}
func createRandomSamples() clientmodel.Samples {
type valueCreator func() clientmodel.SampleValue
type deltaApplier func(clientmodel.SampleValue) clientmodel.SampleValue
var (
maxMetrics = 5
maxCycles = 500
maxStreakLength = 500
maxTimeDelta = 1000
maxTimeDeltaFactor = 10
timestamp = clientmodel.Now() - clientmodel.Timestamp(maxTimeDelta*maxTimeDeltaFactor*maxCycles*maxStreakLength/16) // 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.Intn(1<<32) - 1<<31 + int(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())
},
},
},
}
)
result := clientmodel.Samples{}
metrics := []clientmodel.Metric{}
for n := rand.Intn(maxMetrics); n >= 0; n-- {
metrics = append(metrics, clientmodel.Metric{
clientmodel.LabelName(fmt.Sprintf("labelname_%d", n+1)): clientmodel.LabelValue(fmt.Sprintf("labelvalue_%d", rand.Int())),
})
}
for n := rand.Intn(maxCycles); n >= 0; n-- {
// 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 Storage, samples clientmodel.Samples, maxAge time.Duration) bool {
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 := sample.Metric.Fingerprint()
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 := float64(sample.Value)
got := float64(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
}