prometheus/storage/local/persistence_test.go
beorn7 5bea942d8e Improve various things around chunk encoding.
A number of mostly minor things:

- Rename chunk type -> chunk encoding.

- After all, do not carry around the chunk encoding to all parts of
  the system, but just have one place where the encoding for new
  chunks is set based on the flag. The new approach has caveats as
  well, but the polution of so many method signatures is worse.

- Use the default chunk encoding for new chunks of existing
  series. (Previously, only new _series_ would get chunks with the
  default encoding.)

- Use an enum for chunk encoding. (But keep the version number for the
  flag, for reasons discussed previously.)

- Add encoding() to the chunk interface (so that a chunk knows its own
  encoding - no need to have that in a different top-level function).

- Got rid of newFollowUpChunk (which would keep the existing encoding
  for all chunks of a time series). Now only use newChunk(), which
  will create a chunk encoding according to the flag.

- Simplified transcodeAndAdd.

- Reordered methods of deltaEncodedChunk and doubleDeltaEncoded chunk
  to match the order in the chunk interface.

- Only transcode if the chunk is not yet half full. If more than half
  full, add a new chunk instead.
2015-03-14 19:03:20 +01:00

665 lines
17 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 (
"reflect"
"testing"
clientmodel "github.com/prometheus/client_golang/model"
"github.com/prometheus/prometheus/storage/local/codable"
"github.com/prometheus/prometheus/storage/local/index"
"github.com/prometheus/prometheus/storage/metric"
"github.com/prometheus/prometheus/utility/test"
)
var (
m1 = clientmodel.Metric{"label": "value1"}
m2 = clientmodel.Metric{"label": "value2"}
m3 = clientmodel.Metric{"label": "value3"}
)
func newTestPersistence(t *testing.T, encoding chunkEncoding) (*persistence, test.Closer) {
*defaultChunkEncoding = int(encoding)
dir := test.NewTemporaryDirectory("test_persistence", t)
p, err := newPersistence(dir.Path(), false)
if err != nil {
dir.Close()
t.Fatal(err)
}
return p, test.NewCallbackCloser(func() {
p.close()
dir.Close()
})
}
func buildTestChunks(encoding chunkEncoding) map[clientmodel.Fingerprint][]chunk {
fps := clientmodel.Fingerprints{
m1.Fingerprint(),
m2.Fingerprint(),
m3.Fingerprint(),
}
fpToChunks := map[clientmodel.Fingerprint][]chunk{}
for _, fp := range fps {
fpToChunks[fp] = make([]chunk, 0, 10)
for i := 0; i < 10; i++ {
fpToChunks[fp] = append(fpToChunks[fp], newChunkForEncoding(encoding).add(&metric.SamplePair{
Timestamp: clientmodel.Timestamp(i),
Value: clientmodel.SampleValue(fp),
})[0])
}
}
return fpToChunks
}
func chunksEqual(c1, c2 chunk) bool {
values2 := c2.values()
for v1 := range c1.values() {
v2 := <-values2
if !v1.Equal(v2) {
return false
}
}
return true
}
func testPersistLoadDropChunks(t *testing.T, encoding chunkEncoding) {
p, closer := newTestPersistence(t, encoding)
defer closer.Close()
fpToChunks := buildTestChunks(encoding)
for fp, chunks := range fpToChunks {
for i, c := range chunks {
index, err := p.persistChunks(fp, []chunk{c})
if err != nil {
t.Fatal(err)
}
if i != index {
t.Errorf("Want chunk index %d, got %d.", i, index)
}
}
}
for fp, expectedChunks := range fpToChunks {
indexes := make([]int, 0, len(expectedChunks))
for i := range expectedChunks {
indexes = append(indexes, i)
}
actualChunks, err := p.loadChunks(fp, indexes, 0)
if err != nil {
t.Fatal(err)
}
for _, i := range indexes {
if !chunksEqual(expectedChunks[i], actualChunks[i]) {
t.Errorf("%d. Chunks not equal.", i)
}
}
// Load all chunk descs.
actualChunkDescs, err := p.loadChunkDescs(fp, 10)
if len(actualChunkDescs) != 10 {
t.Errorf("Got %d chunkDescs, want %d.", len(actualChunkDescs), 10)
}
for i, cd := range actualChunkDescs {
if cd.firstTime() != clientmodel.Timestamp(i) || cd.lastTime() != clientmodel.Timestamp(i) {
t.Errorf(
"Want ts=%v, got firstTime=%v, lastTime=%v.",
i, cd.firstTime(), cd.lastTime(),
)
}
}
// Load chunk descs partially.
actualChunkDescs, err = p.loadChunkDescs(fp, 5)
if len(actualChunkDescs) != 5 {
t.Errorf("Got %d chunkDescs, want %d.", len(actualChunkDescs), 5)
}
for i, cd := range actualChunkDescs {
if cd.firstTime() != clientmodel.Timestamp(i) || cd.lastTime() != clientmodel.Timestamp(i) {
t.Errorf(
"Want ts=%v, got firstTime=%v, lastTime=%v.",
i, cd.firstTime(), cd.lastTime(),
)
}
}
}
// Drop half of the chunks.
for fp, expectedChunks := range fpToChunks {
firstTime, numDropped, allDropped, err := p.dropChunks(fp, 5)
if err != nil {
t.Fatal(err)
}
if firstTime != 5 {
t.Errorf("want first time 5, got %d", firstTime)
}
if numDropped != 5 {
t.Errorf("want 5 dropped chunks, got %v", numDropped)
}
if allDropped {
t.Error("all chunks dropped")
}
indexes := make([]int, 5)
for i := range indexes {
indexes[i] = i
}
actualChunks, err := p.loadChunks(fp, indexes, 0)
if err != nil {
t.Fatal(err)
}
for _, i := range indexes {
if !chunksEqual(expectedChunks[i+5], actualChunks[i]) {
t.Errorf("%d. Chunks not equal.", i)
}
}
}
// Drop all the chunks.
for fp := range fpToChunks {
firstTime, numDropped, allDropped, err := p.dropChunks(fp, 100)
if firstTime != 0 {
t.Errorf("want first time 0, got %d", firstTime)
}
if err != nil {
t.Fatal(err)
}
if numDropped != 5 {
t.Errorf("want 5 dropped chunks, got %v", numDropped)
}
if !allDropped {
t.Error("not all chunks dropped")
}
}
}
func TestPersistLoadDropChunksType0(t *testing.T) {
testPersistLoadDropChunks(t, 0)
}
func TestPersistLoadDropChunksType1(t *testing.T) {
testPersistLoadDropChunks(t, 1)
}
func testCheckpointAndLoadSeriesMapAndHeads(t *testing.T, encoding chunkEncoding) {
p, closer := newTestPersistence(t, encoding)
defer closer.Close()
fpLocker := newFingerprintLocker(10)
sm := newSeriesMap()
s1 := newMemorySeries(m1, true, 0)
s2 := newMemorySeries(m2, false, 0)
s3 := newMemorySeries(m3, false, 0)
s1.add(m1.Fingerprint(), &metric.SamplePair{Timestamp: 1, Value: 3.14})
s3.add(m1.Fingerprint(), &metric.SamplePair{Timestamp: 2, Value: 2.7})
s3.headChunkPersisted = true
sm.put(m1.Fingerprint(), s1)
sm.put(m2.Fingerprint(), s2)
sm.put(m3.Fingerprint(), s3)
if err := p.checkpointSeriesMapAndHeads(sm, fpLocker); err != nil {
t.Fatal(err)
}
loadedSM, err := p.loadSeriesMapAndHeads()
if err != nil {
t.Fatal(err)
}
if loadedSM.length() != 2 {
t.Errorf("want 2 series in map, got %d", loadedSM.length())
}
if loadedS1, ok := loadedSM.get(m1.Fingerprint()); ok {
if !reflect.DeepEqual(loadedS1.metric, m1) {
t.Errorf("want metric %v, got %v", m1, loadedS1.metric)
}
if !reflect.DeepEqual(loadedS1.head().chunk, s1.head().chunk) {
t.Error("head chunks differ")
}
if loadedS1.chunkDescsOffset != 0 {
t.Errorf("want chunkDescsOffset 0, got %d", loadedS1.chunkDescsOffset)
}
if loadedS1.headChunkPersisted {
t.Error("headChunkPersisted is true")
}
} else {
t.Errorf("couldn't find %v in loaded map", m1)
}
if loadedS3, ok := loadedSM.get(m3.Fingerprint()); ok {
if !reflect.DeepEqual(loadedS3.metric, m3) {
t.Errorf("want metric %v, got %v", m3, loadedS3.metric)
}
if loadedS3.head().chunk != nil {
t.Error("head chunk not evicted")
}
if loadedS3.chunkDescsOffset != -1 {
t.Errorf("want chunkDescsOffset -1, got %d", loadedS3.chunkDescsOffset)
}
if !loadedS3.headChunkPersisted {
t.Error("headChunkPersisted is false")
}
} else {
t.Errorf("couldn't find %v in loaded map", m1)
}
}
func TestCheckpointAndLoadSeriesMapAndHeadsChunkType0(t *testing.T) {
testCheckpointAndLoadSeriesMapAndHeads(t, 0)
}
func TestCheckpointAndLoadSeriesMapAndHeadsChunkType1(t *testing.T) {
testCheckpointAndLoadSeriesMapAndHeads(t, 1)
}
func testGetFingerprintsModifiedBefore(t *testing.T, encoding chunkEncoding) {
p, closer := newTestPersistence(t, encoding)
defer closer.Close()
m1 := clientmodel.Metric{"n1": "v1"}
m2 := clientmodel.Metric{"n2": "v2"}
m3 := clientmodel.Metric{"n1": "v2"}
p.archiveMetric(1, m1, 2, 4)
p.archiveMetric(2, m2, 1, 6)
p.archiveMetric(3, m3, 5, 5)
expectedFPs := map[clientmodel.Timestamp][]clientmodel.Fingerprint{
0: {},
1: {},
2: {2},
3: {1, 2},
4: {1, 2},
5: {1, 2},
6: {1, 2, 3},
}
for ts, want := range expectedFPs {
got, err := p.getFingerprintsModifiedBefore(ts)
if err != nil {
t.Fatal(err)
}
if !reflect.DeepEqual(want, got) {
t.Errorf("timestamp: %v, want FPs %v, got %v", ts, want, got)
}
}
unarchived, firstTime, err := p.unarchiveMetric(1)
if err != nil {
t.Fatal(err)
}
if !unarchived {
t.Fatal("expected actual unarchival")
}
if firstTime != 2 {
t.Errorf("expected first time 2, got %v", firstTime)
}
unarchived, firstTime, err = p.unarchiveMetric(1)
if err != nil {
t.Fatal(err)
}
if unarchived {
t.Fatal("expected no unarchival")
}
expectedFPs = map[clientmodel.Timestamp][]clientmodel.Fingerprint{
0: {},
1: {},
2: {2},
3: {2},
4: {2},
5: {2},
6: {2, 3},
}
for ts, want := range expectedFPs {
got, err := p.getFingerprintsModifiedBefore(ts)
if err != nil {
t.Fatal(err)
}
if !reflect.DeepEqual(want, got) {
t.Errorf("timestamp: %v, want FPs %v, got %v", ts, want, got)
}
}
}
func TestGetFingerprintsModifiedBeforeChunkType0(t *testing.T) {
testGetFingerprintsModifiedBefore(t, 0)
}
func TestGetFingerprintsModifiedBeforeChunkType1(t *testing.T) {
testGetFingerprintsModifiedBefore(t, 1)
}
func testDropArchivedMetric(t *testing.T, encoding chunkEncoding) {
p, closer := newTestPersistence(t, encoding)
defer closer.Close()
m1 := clientmodel.Metric{"n1": "v1"}
m2 := clientmodel.Metric{"n2": "v2"}
p.archiveMetric(1, m1, 2, 4)
p.archiveMetric(2, m2, 1, 6)
p.indexMetric(1, m1)
p.indexMetric(2, m2)
p.waitForIndexing()
outFPs, err := p.getFingerprintsForLabelPair(metric.LabelPair{Name: "n1", Value: "v1"})
if err != nil {
t.Fatal(err)
}
want := clientmodel.Fingerprints{1}
if !reflect.DeepEqual(outFPs, want) {
t.Errorf("want %#v, got %#v", want, outFPs)
}
outFPs, err = p.getFingerprintsForLabelPair(metric.LabelPair{Name: "n2", Value: "v2"})
if err != nil {
t.Fatal(err)
}
want = clientmodel.Fingerprints{2}
if !reflect.DeepEqual(outFPs, want) {
t.Errorf("want %#v, got %#v", want, outFPs)
}
if archived, _, _, err := p.hasArchivedMetric(1); err != nil || !archived {
t.Error("want FP 1 archived")
}
if archived, _, _, err := p.hasArchivedMetric(2); err != nil || !archived {
t.Error("want FP 2 archived")
}
if err != p.purgeArchivedMetric(1) {
t.Fatal(err)
}
if err != p.purgeArchivedMetric(3) {
// Purging something that has not beet archived is not an error.
t.Fatal(err)
}
p.waitForIndexing()
outFPs, err = p.getFingerprintsForLabelPair(metric.LabelPair{Name: "n1", Value: "v1"})
if err != nil {
t.Fatal(err)
}
want = nil
if !reflect.DeepEqual(outFPs, want) {
t.Errorf("want %#v, got %#v", want, outFPs)
}
outFPs, err = p.getFingerprintsForLabelPair(metric.LabelPair{Name: "n2", Value: "v2"})
if err != nil {
t.Fatal(err)
}
want = clientmodel.Fingerprints{2}
if !reflect.DeepEqual(outFPs, want) {
t.Errorf("want %#v, got %#v", want, outFPs)
}
if archived, _, _, err := p.hasArchivedMetric(1); err != nil || archived {
t.Error("want FP 1 not archived")
}
if archived, _, _, err := p.hasArchivedMetric(2); err != nil || !archived {
t.Error("want FP 2 archived")
}
}
func TestDropArchivedMetricChunkType0(t *testing.T) {
testDropArchivedMetric(t, 0)
}
func TestDropArchivedMetricChunkType1(t *testing.T) {
testDropArchivedMetric(t, 1)
}
type incrementalBatch struct {
fpToMetric index.FingerprintMetricMapping
expectedLnToLvs index.LabelNameLabelValuesMapping
expectedLpToFps index.LabelPairFingerprintsMapping
}
func testIndexing(t *testing.T, encoding chunkEncoding) {
batches := []incrementalBatch{
{
fpToMetric: index.FingerprintMetricMapping{
0: {
clientmodel.MetricNameLabel: "metric_0",
"label_1": "value_1",
},
1: {
clientmodel.MetricNameLabel: "metric_0",
"label_2": "value_2",
"label_3": "value_3",
},
2: {
clientmodel.MetricNameLabel: "metric_1",
"label_1": "value_2",
},
},
expectedLnToLvs: index.LabelNameLabelValuesMapping{
clientmodel.MetricNameLabel: codable.LabelValueSet{
"metric_0": struct{}{},
"metric_1": struct{}{},
},
"label_1": codable.LabelValueSet{
"value_1": struct{}{},
"value_2": struct{}{},
},
"label_2": codable.LabelValueSet{
"value_2": struct{}{},
},
"label_3": codable.LabelValueSet{
"value_3": struct{}{},
},
},
expectedLpToFps: index.LabelPairFingerprintsMapping{
metric.LabelPair{
Name: clientmodel.MetricNameLabel,
Value: "metric_0",
}: codable.FingerprintSet{0: struct{}{}, 1: struct{}{}},
metric.LabelPair{
Name: clientmodel.MetricNameLabel,
Value: "metric_1",
}: codable.FingerprintSet{2: struct{}{}},
metric.LabelPair{
Name: "label_1",
Value: "value_1",
}: codable.FingerprintSet{0: struct{}{}},
metric.LabelPair{
Name: "label_1",
Value: "value_2",
}: codable.FingerprintSet{2: struct{}{}},
metric.LabelPair{
Name: "label_2",
Value: "value_2",
}: codable.FingerprintSet{1: struct{}{}},
metric.LabelPair{
Name: "label_3",
Value: "value_3",
}: codable.FingerprintSet{1: struct{}{}},
},
}, {
fpToMetric: index.FingerprintMetricMapping{
3: {
clientmodel.MetricNameLabel: "metric_0",
"label_1": "value_3",
},
4: {
clientmodel.MetricNameLabel: "metric_2",
"label_2": "value_2",
"label_3": "value_1",
},
5: {
clientmodel.MetricNameLabel: "metric_1",
"label_1": "value_3",
},
},
expectedLnToLvs: index.LabelNameLabelValuesMapping{
clientmodel.MetricNameLabel: codable.LabelValueSet{
"metric_0": struct{}{},
"metric_1": struct{}{},
"metric_2": struct{}{},
},
"label_1": codable.LabelValueSet{
"value_1": struct{}{},
"value_2": struct{}{},
"value_3": struct{}{},
},
"label_2": codable.LabelValueSet{
"value_2": struct{}{},
},
"label_3": codable.LabelValueSet{
"value_1": struct{}{},
"value_3": struct{}{},
},
},
expectedLpToFps: index.LabelPairFingerprintsMapping{
metric.LabelPair{
Name: clientmodel.MetricNameLabel,
Value: "metric_0",
}: codable.FingerprintSet{0: struct{}{}, 1: struct{}{}, 3: struct{}{}},
metric.LabelPair{
Name: clientmodel.MetricNameLabel,
Value: "metric_1",
}: codable.FingerprintSet{2: struct{}{}, 5: struct{}{}},
metric.LabelPair{
Name: clientmodel.MetricNameLabel,
Value: "metric_2",
}: codable.FingerprintSet{4: struct{}{}},
metric.LabelPair{
Name: "label_1",
Value: "value_1",
}: codable.FingerprintSet{0: struct{}{}},
metric.LabelPair{
Name: "label_1",
Value: "value_2",
}: codable.FingerprintSet{2: struct{}{}},
metric.LabelPair{
Name: "label_1",
Value: "value_3",
}: codable.FingerprintSet{3: struct{}{}, 5: struct{}{}},
metric.LabelPair{
Name: "label_2",
Value: "value_2",
}: codable.FingerprintSet{1: struct{}{}, 4: struct{}{}},
metric.LabelPair{
Name: "label_3",
Value: "value_1",
}: codable.FingerprintSet{4: struct{}{}},
metric.LabelPair{
Name: "label_3",
Value: "value_3",
}: codable.FingerprintSet{1: struct{}{}},
},
},
}
p, closer := newTestPersistence(t, encoding)
defer closer.Close()
indexedFpsToMetrics := index.FingerprintMetricMapping{}
for i, b := range batches {
for fp, m := range b.fpToMetric {
p.indexMetric(fp, m)
if err := p.archiveMetric(fp, m, 1, 2); err != nil {
t.Fatal(err)
}
indexedFpsToMetrics[fp] = m
}
verifyIndexedState(i, t, b, indexedFpsToMetrics, p)
}
for i := len(batches) - 1; i >= 0; i-- {
b := batches[i]
verifyIndexedState(i, t, batches[i], indexedFpsToMetrics, p)
for fp, m := range b.fpToMetric {
p.unindexMetric(fp, m)
unarchived, firstTime, err := p.unarchiveMetric(fp)
if err != nil {
t.Fatal(err)
}
if !unarchived {
t.Errorf("%d. metric not unarchived", i)
}
if firstTime != 1 {
t.Errorf("%d. expected firstTime=1, got %v", i, firstTime)
}
delete(indexedFpsToMetrics, fp)
}
}
}
func TestIndexingChunkType0(t *testing.T) {
testIndexing(t, 0)
}
func TestIndexingChunkType1(t *testing.T) {
testIndexing(t, 1)
}
func verifyIndexedState(i int, t *testing.T, b incrementalBatch, indexedFpsToMetrics index.FingerprintMetricMapping, p *persistence) {
p.waitForIndexing()
for fp, m := range indexedFpsToMetrics {
// Compare archived metrics with input metrics.
mOut, err := p.getArchivedMetric(fp)
if err != nil {
t.Fatal(err)
}
if !mOut.Equal(m) {
t.Errorf("%d. %v: Got: %s; want %s", i, fp, mOut, m)
}
// Check that archived metrics are in membership index.
has, first, last, err := p.hasArchivedMetric(fp)
if err != nil {
t.Fatal(err)
}
if !has {
t.Errorf("%d. fingerprint %v not found", i, fp)
}
if first != 1 || last != 2 {
t.Errorf(
"%d. %v: Got first: %d, last %d; want first: %d, last %d",
i, fp, first, last, 1, 2,
)
}
}
// Compare label name -> label values mappings.
for ln, lvs := range b.expectedLnToLvs {
outLvs, err := p.getLabelValuesForLabelName(ln)
if err != nil {
t.Fatal(err)
}
outSet := codable.LabelValueSet{}
for _, lv := range outLvs {
outSet[lv] = struct{}{}
}
if !reflect.DeepEqual(lvs, outSet) {
t.Errorf("%d. label values don't match. Got: %v; want %v", i, outSet, lvs)
}
}
// Compare label pair -> fingerprints mappings.
for lp, fps := range b.expectedLpToFps {
outFPs, err := p.getFingerprintsForLabelPair(lp)
if err != nil {
t.Fatal(err)
}
outSet := codable.FingerprintSet{}
for _, fp := range outFPs {
outSet[fp] = struct{}{}
}
if !reflect.DeepEqual(fps, outSet) {
t.Errorf("%d. %v: fingerprints don't match. Got: %v; want %v", i, lp, outSet, fps)
}
}
}