prometheus/storage/metric/leveldb.go
2013-06-06 23:56:31 +02:00

958 lines
26 KiB
Go

// Copyright 2013 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 metric
import (
"code.google.com/p/goprotobuf/proto"
"flag"
"fmt"
"github.com/prometheus/prometheus/coding"
"github.com/prometheus/prometheus/model"
dto "github.com/prometheus/prometheus/model/generated"
"github.com/prometheus/prometheus/storage"
index "github.com/prometheus/prometheus/storage/raw/index/leveldb"
"github.com/prometheus/prometheus/storage/raw/leveldb"
"github.com/prometheus/prometheus/utility"
"log"
"sort"
"sync"
"time"
)
const (
sortConcurrency = 2
)
type LevelDBMetricPersistence struct {
CurationRemarks *leveldb.LevelDBPersistence
fingerprintToMetrics *leveldb.LevelDBPersistence
labelNameToFingerprints *leveldb.LevelDBPersistence
labelSetToFingerprints *leveldb.LevelDBPersistence
MetricHighWatermarks *leveldb.LevelDBPersistence
metricMembershipIndex *index.LevelDBMembershipIndex
MetricSamples *leveldb.LevelDBPersistence
}
var (
leveldbChunkSize = flag.Int("leveldbChunkSize", 200, "Maximum number of samples stored under one key.")
// These flag values are back of the envelope, though they seem sensible.
// Please re-evaluate based on your own needs.
curationRemarksCacheSize = flag.Int("curationRemarksCacheSize", 50*1024*1024, "The size for the curation remarks cache (bytes).")
fingerprintsToLabelPairCacheSize = flag.Int("fingerprintsToLabelPairCacheSizeBytes", 100*1024*1024, "The size for the fingerprint to label pair index (bytes).")
highWatermarkCacheSize = flag.Int("highWatermarksByFingerprintSizeBytes", 50*1024*1024, "The size for the metric high watermarks (bytes).")
labelNameToFingerprintsCacheSize = flag.Int("labelNameToFingerprintsCacheSizeBytes", 100*1024*1024, "The size for the label name to metric fingerprint index (bytes).")
labelPairToFingerprintsCacheSize = flag.Int("labelPairToFingerprintsCacheSizeBytes", 100*1024*1024, "The size for the label pair to metric fingerprint index (bytes).")
metricMembershipIndexCacheSize = flag.Int("metricMembershipCacheSizeBytes", 50*1024*1024, "The size for the metric membership index (bytes).")
samplesByFingerprintCacheSize = flag.Int("samplesByFingerprintCacheSizeBytes", 500*1024*1024, "The size for the samples database (bytes).")
)
type leveldbOpener func()
type leveldbCloser interface {
Close()
}
func (l *LevelDBMetricPersistence) Close() {
var persistences = []leveldbCloser{
l.CurationRemarks,
l.fingerprintToMetrics,
l.labelNameToFingerprints,
l.labelSetToFingerprints,
l.MetricHighWatermarks,
l.metricMembershipIndex,
l.MetricSamples,
}
closerGroup := sync.WaitGroup{}
for _, closer := range persistences {
closerGroup.Add(1)
go func(closer leveldbCloser) {
if closer != nil {
closer.Close()
}
closerGroup.Done()
}(closer)
}
closerGroup.Wait()
}
func NewLevelDBMetricPersistence(baseDirectory string) (*LevelDBMetricPersistence, error) {
workers := utility.NewUncertaintyGroup(7)
emission := &LevelDBMetricPersistence{}
var subsystemOpeners = []struct {
name string
opener leveldbOpener
}{
{
"Label Names and Value Pairs by Fingerprint",
func() {
var err error
emission.fingerprintToMetrics, err = leveldb.NewLevelDBPersistence(baseDirectory+"/label_name_and_value_pairs_by_fingerprint", *fingerprintsToLabelPairCacheSize, 10)
workers.MayFail(err)
},
},
{
"Samples by Fingerprint",
func() {
var err error
emission.MetricSamples, err = leveldb.NewLevelDBPersistence(baseDirectory+"/samples_by_fingerprint", *samplesByFingerprintCacheSize, 10)
workers.MayFail(err)
},
},
{
"High Watermarks by Fingerprint",
func() {
var err error
emission.MetricHighWatermarks, err = leveldb.NewLevelDBPersistence(baseDirectory+"/high_watermarks_by_fingerprint", *highWatermarkCacheSize, 10)
workers.MayFail(err)
},
},
{
"Fingerprints by Label Name",
func() {
var err error
emission.labelNameToFingerprints, err = leveldb.NewLevelDBPersistence(baseDirectory+"/fingerprints_by_label_name", *labelNameToFingerprintsCacheSize, 10)
workers.MayFail(err)
},
},
{
"Fingerprints by Label Name and Value Pair",
func() {
var err error
emission.labelSetToFingerprints, err = leveldb.NewLevelDBPersistence(baseDirectory+"/fingerprints_by_label_name_and_value_pair", *labelPairToFingerprintsCacheSize, 10)
workers.MayFail(err)
},
},
{
"Metric Membership Index",
func() {
var err error
emission.metricMembershipIndex, err = index.NewLevelDBMembershipIndex(baseDirectory+"/metric_membership_index", *metricMembershipIndexCacheSize, 10)
workers.MayFail(err)
},
},
{
"Sample Curation Remarks",
func() {
var err error
emission.CurationRemarks, err = leveldb.NewLevelDBPersistence(baseDirectory+"/curation_remarks", *curationRemarksCacheSize, 10)
workers.MayFail(err)
},
},
}
for _, subsystem := range subsystemOpeners {
opener := subsystem.opener
go opener()
}
if !workers.Wait() {
for _, err := range workers.Errors() {
log.Printf("Could not open storage due to %s", err)
}
return nil, fmt.Errorf("Unable to open metric persistence.")
}
return emission, nil
}
func (l *LevelDBMetricPersistence) AppendSample(sample model.Sample) (err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: appendSample, result: success}, map[string]string{operation: appendSample, result: failure})
}(time.Now())
err = l.AppendSamples(model.Samples{sample})
return
}
// groupByFingerprint collects all of the provided samples, groups them
// together by their respective metric fingerprint, and finally sorts
// them chronologically.
func groupByFingerprint(samples model.Samples) map[model.Fingerprint]model.Samples {
fingerprintToSamples := map[model.Fingerprint]model.Samples{}
for _, sample := range samples {
fingerprint := *model.NewFingerprintFromMetric(sample.Metric)
samples := fingerprintToSamples[fingerprint]
samples = append(samples, sample)
fingerprintToSamples[fingerprint] = samples
}
sortingSemaphore := make(chan bool, sortConcurrency)
doneSorting := sync.WaitGroup{}
for i := 0; i < sortConcurrency; i++ {
sortingSemaphore <- true
}
for _, samples := range fingerprintToSamples {
doneSorting.Add(1)
<-sortingSemaphore
go func(samples model.Samples) {
sort.Sort(samples)
sortingSemaphore <- true
doneSorting.Done()
}(samples)
}
doneSorting.Wait()
return fingerprintToSamples
}
// findUnindexedMetrics scours the metric membership index for each given Metric
// in the keyspace and returns a map of Fingerprint-Metric pairs that are
// absent.
func (l *LevelDBMetricPersistence) findUnindexedMetrics(candidates map[model.Fingerprint]model.Metric) (unindexed map[model.Fingerprint]model.Metric, err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: findUnindexedMetrics, result: success}, map[string]string{operation: findUnindexedMetrics, result: failure})
}(time.Now())
unindexed = make(map[model.Fingerprint]model.Metric)
// Determine which metrics are unknown in the database.
for fingerprint, metric := range candidates {
dto := model.MetricToDTO(metric)
indexHas, err := l.hasIndexMetric(dto)
if err != nil {
return unindexed, err
}
if !indexHas {
unindexed[fingerprint] = metric
}
}
return
}
// indexLabelNames accumulates all label name to fingerprint index entries for
// the dirty metrics, appends the new dirtied metrics, sorts, and bulk updates
// the index to reflect the new state.
//
// This operation is idempotent.
func (l *LevelDBMetricPersistence) indexLabelNames(metrics map[model.Fingerprint]model.Metric) (err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: indexLabelNames, result: success}, map[string]string{operation: indexLabelNames, result: failure})
}(time.Now())
labelNameFingerprints := map[model.LabelName]utility.Set{}
for fingerprint, metric := range metrics {
for labelName := range metric {
fingerprintSet, ok := labelNameFingerprints[labelName]
if !ok {
fingerprintSet = utility.Set{}
fingerprints, err := l.GetFingerprintsForLabelName(labelName)
if err != nil {
return err
}
for _, fingerprint := range fingerprints {
fingerprintSet.Add(*fingerprint)
}
}
fingerprintSet.Add(fingerprint)
labelNameFingerprints[labelName] = fingerprintSet
}
}
batch := leveldb.NewBatch()
defer batch.Close()
for labelName, fingerprintSet := range labelNameFingerprints {
fingerprints := model.Fingerprints{}
for e := range fingerprintSet {
fingerprint := e.(model.Fingerprint)
fingerprints = append(fingerprints, &fingerprint)
}
sort.Sort(fingerprints)
key := &dto.LabelName{
Name: proto.String(string(labelName)),
}
value := &dto.FingerprintCollection{}
for _, fingerprint := range fingerprints {
value.Member = append(value.Member, fingerprint.ToDTO())
}
batch.Put(coding.NewPBEncoder(key), coding.NewPBEncoder(value))
}
err = l.labelNameToFingerprints.Commit(batch)
if err != nil {
return
}
return
}
// indexLabelPairs accumulates all label pair to fingerprint index entries for
// the dirty metrics, appends the new dirtied metrics, sorts, and bulk updates
// the index to reflect the new state.
//
// This operation is idempotent.
func (l *LevelDBMetricPersistence) indexLabelPairs(metrics map[model.Fingerprint]model.Metric) (err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: indexLabelPairs, result: success}, map[string]string{operation: indexLabelPairs, result: failure})
}(time.Now())
labelPairFingerprints := map[model.LabelPair]utility.Set{}
for fingerprint, metric := range metrics {
for labelName, labelValue := range metric {
labelPair := model.LabelPair{
Name: labelName,
Value: labelValue,
}
fingerprintSet, ok := labelPairFingerprints[labelPair]
if !ok {
fingerprintSet = utility.Set{}
fingerprints, err := l.GetFingerprintsForLabelSet(model.LabelSet{
labelName: labelValue,
})
if err != nil {
return err
}
for _, fingerprint := range fingerprints {
fingerprintSet.Add(*fingerprint)
}
}
fingerprintSet.Add(fingerprint)
labelPairFingerprints[labelPair] = fingerprintSet
}
}
batch := leveldb.NewBatch()
defer batch.Close()
for labelPair, fingerprintSet := range labelPairFingerprints {
fingerprints := model.Fingerprints{}
for e := range fingerprintSet {
fingerprint := e.(model.Fingerprint)
fingerprints = append(fingerprints, &fingerprint)
}
sort.Sort(fingerprints)
key := &dto.LabelPair{
Name: proto.String(string(labelPair.Name)),
Value: proto.String(string(labelPair.Value)),
}
value := &dto.FingerprintCollection{}
for _, fingerprint := range fingerprints {
value.Member = append(value.Member, fingerprint.ToDTO())
}
batch.Put(coding.NewPBEncoder(key), coding.NewPBEncoder(value))
}
err = l.labelSetToFingerprints.Commit(batch)
if err != nil {
return
}
return
}
// indexFingerprints updates all of the Fingerprint to Metric reverse lookups
// in the index and then bulk updates.
//
// This operation is idempotent.
func (l *LevelDBMetricPersistence) indexFingerprints(metrics map[model.Fingerprint]model.Metric) (err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: indexFingerprints, result: success}, map[string]string{operation: indexFingerprints, result: failure})
}(time.Now())
batch := leveldb.NewBatch()
defer batch.Close()
for fingerprint, metric := range metrics {
key := coding.NewPBEncoder(fingerprint.ToDTO())
value := coding.NewPBEncoder(model.MetricToDTO(metric))
batch.Put(key, value)
}
err = l.fingerprintToMetrics.Commit(batch)
if err != nil {
return
}
return
}
// indexMetrics takes groups of samples, determines which ones contain metrics
// that are unknown to the storage stack, and then proceeds to update all
// affected indices.
func (l *LevelDBMetricPersistence) indexMetrics(fingerprints map[model.Fingerprint]model.Metric) (err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: indexMetrics, result: success}, map[string]string{operation: indexMetrics, result: failure})
}(time.Now())
var (
absentMetrics map[model.Fingerprint]model.Metric
)
absentMetrics, err = l.findUnindexedMetrics(fingerprints)
if err != nil {
return
}
if len(absentMetrics) == 0 {
return
}
// TODO: For the missing fingerprints, determine what label names and pairs
// are absent and act accordingly and append fingerprints.
workers := utility.NewUncertaintyGroup(3)
go func() {
workers.MayFail(l.indexLabelNames(absentMetrics))
}()
go func() {
workers.MayFail(l.indexLabelPairs(absentMetrics))
}()
go func() {
workers.MayFail(l.indexFingerprints(absentMetrics))
}()
if !workers.Wait() {
return fmt.Errorf("Could not index due to %s", workers.Errors())
}
// If any of the preceding operations failed, we will have inconsistent
// indices. Thusly, the Metric membership index should NOT be updated, as
// its state is used to determine whether to bulk update the other indices.
// Given that those operations are idempotent, it is OK to repeat them;
// however, it will consume considerable amounts of time.
batch := leveldb.NewBatch()
defer batch.Close()
// WART: We should probably encode simple fingerprints.
for _, metric := range absentMetrics {
key := coding.NewPBEncoder(model.MetricToDTO(metric))
batch.Put(key, key)
}
err = l.metricMembershipIndex.Commit(batch)
if err != nil {
// Not critical but undesirable.
log.Println(err)
}
return
}
func (l *LevelDBMetricPersistence) refreshHighWatermarks(groups map[model.Fingerprint]model.Samples) (err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: refreshHighWatermarks, result: success}, map[string]string{operation: refreshHighWatermarks, result: failure})
}(time.Now())
batch := leveldb.NewBatch()
defer batch.Close()
mutationCount := 0
for fingerprint, samples := range groups {
keyEncoded := coding.NewPBEncoder(fingerprint.ToDTO())
value := &dto.MetricHighWatermark{}
newestSampleTimestamp := samples[len(samples)-1].Timestamp
raw, err := l.MetricHighWatermarks.Get(keyEncoded)
if err != nil {
return err
}
if raw != nil {
err = proto.Unmarshal(raw, value)
if err != nil {
return err
}
if newestSampleTimestamp.Before(time.Unix(*value.Timestamp, 0)) {
continue
}
}
value.Timestamp = proto.Int64(newestSampleTimestamp.Unix())
batch.Put(keyEncoded, coding.NewPBEncoder(value))
mutationCount++
}
err = l.MetricHighWatermarks.Commit(batch)
if err != nil {
return err
}
return nil
}
func (l *LevelDBMetricPersistence) AppendSamples(samples model.Samples) (err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: appendSamples, result: success}, map[string]string{operation: appendSamples, result: failure})
}(time.Now())
fingerprintToSamples := groupByFingerprint(samples)
indexErrChan := make(chan error, 1)
watermarkErrChan := make(chan error, 1)
go func(groups map[model.Fingerprint]model.Samples) {
metrics := map[model.Fingerprint]model.Metric{}
for fingerprint, samples := range groups {
metrics[fingerprint] = samples[0].Metric
}
indexErrChan <- l.indexMetrics(metrics)
}(fingerprintToSamples)
go func(groups map[model.Fingerprint]model.Samples) {
watermarkErrChan <- l.refreshHighWatermarks(groups)
}(fingerprintToSamples)
samplesBatch := leveldb.NewBatch()
defer samplesBatch.Close()
for fingerprint, group := range fingerprintToSamples {
for {
lengthOfGroup := len(group)
if lengthOfGroup == 0 {
break
}
take := *leveldbChunkSize
if lengthOfGroup < take {
take = lengthOfGroup
}
chunk := group[0:take]
group = group[take:lengthOfGroup]
key := model.SampleKey{
Fingerprint: &fingerprint,
FirstTimestamp: chunk[0].Timestamp,
LastTimestamp: chunk[take-1].Timestamp,
SampleCount: uint32(take),
}.ToDTO()
value := &dto.SampleValueSeries{}
for _, sample := range chunk {
value.Value = append(value.Value, &dto.SampleValueSeries_Value{
Timestamp: proto.Int64(sample.Timestamp.Unix()),
Value: sample.Value.ToDTO(),
})
}
samplesBatch.Put(coding.NewPBEncoder(key), coding.NewPBEncoder(value))
}
}
err = l.MetricSamples.Commit(samplesBatch)
if err != nil {
return
}
err = <-indexErrChan
if err != nil {
return
}
err = <-watermarkErrChan
if err != nil {
return
}
return
}
func extractSampleKey(i leveldb.Iterator) (key model.SampleKey, err error) {
k := &dto.SampleKey{}
err = proto.Unmarshal(i.Key(), k)
if err != nil {
return
}
key = model.NewSampleKeyFromDTO(k)
return
}
func extractSampleValues(i leveldb.Iterator) (values model.Values, err error) {
v := &dto.SampleValueSeries{}
err = proto.Unmarshal(i.Value(), v)
if err != nil {
return
}
values = model.NewValuesFromDTO(v)
return
}
func fingerprintsEqual(l *dto.Fingerprint, r *dto.Fingerprint) bool {
if l == r {
return true
}
if l == nil && r == nil {
return true
}
if r.Signature == l.Signature {
return true
}
if *r.Signature == *l.Signature {
return true
}
return false
}
func (l *LevelDBMetricPersistence) hasIndexMetric(dto *dto.Metric) (value bool, err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: hasIndexMetric, result: success}, map[string]string{operation: hasIndexMetric, result: failure})
}(time.Now())
dtoKey := coding.NewPBEncoder(dto)
value, err = l.metricMembershipIndex.Has(dtoKey)
return
}
func (l *LevelDBMetricPersistence) HasLabelPair(dto *dto.LabelPair) (value bool, err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: hasLabelPair, result: success}, map[string]string{operation: hasLabelPair, result: failure})
}(time.Now())
dtoKey := coding.NewPBEncoder(dto)
value, err = l.labelSetToFingerprints.Has(dtoKey)
return
}
func (l *LevelDBMetricPersistence) HasLabelName(dto *dto.LabelName) (value bool, err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: hasLabelName, result: success}, map[string]string{operation: hasLabelName, result: failure})
}(time.Now())
dtoKey := coding.NewPBEncoder(dto)
value, err = l.labelNameToFingerprints.Has(dtoKey)
return
}
func (l *LevelDBMetricPersistence) GetFingerprintsForLabelSet(labelSet model.LabelSet) (fps model.Fingerprints, err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: getFingerprintsForLabelSet, result: success}, map[string]string{operation: getFingerprintsForLabelSet, result: failure})
}(time.Now())
sets := []utility.Set{}
for _, labelSetDTO := range model.LabelSetToDTOs(&labelSet) {
f, err := l.labelSetToFingerprints.Get(coding.NewPBEncoder(labelSetDTO))
if err != nil {
return fps, err
}
unmarshaled := &dto.FingerprintCollection{}
err = proto.Unmarshal(f, unmarshaled)
if err != nil {
return fps, err
}
set := utility.Set{}
for _, m := range unmarshaled.Member {
fp := model.NewFingerprintFromRowKey(*m.Signature)
set.Add(*fp)
}
sets = append(sets, set)
}
numberOfSets := len(sets)
if numberOfSets == 0 {
return
}
base := sets[0]
for i := 1; i < numberOfSets; i++ {
base = base.Intersection(sets[i])
}
for _, e := range base.Elements() {
fingerprint := e.(model.Fingerprint)
fps = append(fps, &fingerprint)
}
return
}
func (l *LevelDBMetricPersistence) GetFingerprintsForLabelName(labelName model.LabelName) (fps model.Fingerprints, err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: getFingerprintsForLabelName, result: success}, map[string]string{operation: getFingerprintsForLabelName, result: failure})
}(time.Now())
raw, err := l.labelNameToFingerprints.Get(coding.NewPBEncoder(model.LabelNameToDTO(&labelName)))
if err != nil {
return
}
unmarshaled := &dto.FingerprintCollection{}
err = proto.Unmarshal(raw, unmarshaled)
if err != nil {
return
}
for _, m := range unmarshaled.Member {
fp := model.NewFingerprintFromRowKey(*m.Signature)
fps = append(fps, fp)
}
return
}
func (l *LevelDBMetricPersistence) GetMetricForFingerprint(f *model.Fingerprint) (m model.Metric, err error) {
defer func(begin time.Time) {
duration := time.Since(begin)
recordOutcome(duration, err, map[string]string{operation: getMetricForFingerprint, result: success}, map[string]string{operation: getMetricForFingerprint, result: failure})
}(time.Now())
raw, err := l.fingerprintToMetrics.Get(coding.NewPBEncoder(model.FingerprintToDTO(f)))
if err != nil {
return
}
unmarshaled := &dto.Metric{}
err = proto.Unmarshal(raw, unmarshaled)
if err != nil {
return
}
m = model.Metric{}
for _, v := range unmarshaled.LabelPair {
m[model.LabelName(*v.Name)] = model.LabelValue(*v.Value)
}
return
}
func (l LevelDBMetricPersistence) GetValueAtTime(f *model.Fingerprint, t time.Time) model.Values {
panic("Not implemented")
}
func (l LevelDBMetricPersistence) GetBoundaryValues(f *model.Fingerprint, i model.Interval) model.Values {
panic("Not implemented")
}
func (l *LevelDBMetricPersistence) GetRangeValues(f *model.Fingerprint, i model.Interval) model.Values {
panic("Not implemented")
}
type MetricKeyDecoder struct{}
func (d *MetricKeyDecoder) DecodeKey(in interface{}) (out interface{}, err error) {
unmarshaled := dto.LabelPair{}
err = proto.Unmarshal(in.([]byte), &unmarshaled)
if err != nil {
return
}
out = model.LabelPair{
Name: model.LabelName(*unmarshaled.Name),
Value: model.LabelValue(*unmarshaled.Value),
}
return
}
func (d *MetricKeyDecoder) DecodeValue(in interface{}) (out interface{}, err error) {
return
}
type LabelNameFilter struct {
labelName model.LabelName
}
func (f LabelNameFilter) Filter(key, value interface{}) (filterResult storage.FilterResult) {
labelPair, ok := key.(model.LabelPair)
if ok && labelPair.Name == f.labelName {
return storage.ACCEPT
}
return storage.SKIP
}
type CollectLabelValuesOp struct {
labelValues []model.LabelValue
}
func (op *CollectLabelValuesOp) Operate(key, value interface{}) (err *storage.OperatorError) {
labelPair := key.(model.LabelPair)
op.labelValues = append(op.labelValues, model.LabelValue(labelPair.Value))
return
}
func (l *LevelDBMetricPersistence) GetAllValuesForLabel(labelName model.LabelName) (values model.LabelValues, err error) {
filter := &LabelNameFilter{
labelName: labelName,
}
labelValuesOp := &CollectLabelValuesOp{}
_, err = l.labelSetToFingerprints.ForEach(&MetricKeyDecoder{}, filter, labelValuesOp)
if err != nil {
return
}
values = labelValuesOp.labelValues
return
}
// CompactKeyspace compacts each database's keyspace serially.
//
// Beware that it would probably be imprudent to run this on a live user-facing
// server due to latency implications.
func (l *LevelDBMetricPersistence) CompactKeyspaces() {
l.CurationRemarks.CompactKeyspace()
l.fingerprintToMetrics.CompactKeyspace()
l.labelNameToFingerprints.CompactKeyspace()
l.labelSetToFingerprints.CompactKeyspace()
l.MetricHighWatermarks.CompactKeyspace()
l.metricMembershipIndex.CompactKeyspace()
l.MetricSamples.CompactKeyspace()
}
func (l *LevelDBMetricPersistence) ApproximateSizes() (total uint64, err error) {
size := uint64(0)
if size, err = l.CurationRemarks.ApproximateSize(); err != nil {
return 0, err
}
total += size
if size, err = l.fingerprintToMetrics.ApproximateSize(); err != nil {
return 0, err
}
total += size
if size, err = l.labelNameToFingerprints.ApproximateSize(); err != nil {
return 0, err
}
total += size
if size, err = l.labelSetToFingerprints.ApproximateSize(); err != nil {
return 0, err
}
total += size
if size, err = l.MetricHighWatermarks.ApproximateSize(); err != nil {
return 0, err
}
total += size
if size, err = l.metricMembershipIndex.ApproximateSize(); err != nil {
return 0, err
}
total += size
if size, err = l.MetricSamples.ApproximateSize(); err != nil {
return 0, err
}
total += size
return total, nil
}
func (l *LevelDBMetricPersistence) States() []leveldb.DatabaseState {
states := []leveldb.DatabaseState{}
state := l.CurationRemarks.State()
state.Name = "Curation Remarks"
state.Type = "Watermark"
states = append(states, state)
state = l.fingerprintToMetrics.State()
state.Name = "Fingerprints to Metrics"
state.Type = "Index"
states = append(states, state)
state = l.labelNameToFingerprints.State()
state.Name = "Label Name to Fingerprints"
state.Type = "Inverted Index"
states = append(states, state)
state = l.labelSetToFingerprints.State()
state.Name = "Label Pair to Fingerprints"
state.Type = "Inverted Index"
states = append(states, state)
state = l.MetricHighWatermarks.State()
state.Name = "Metric Last Write"
state.Type = "Watermark"
states = append(states, state)
state = l.metricMembershipIndex.State()
state.Name = "Metric Membership"
state.Type = "Index"
states = append(states, state)
state = l.MetricSamples.State()
state.Name = "Samples"
state.Type = "Time Series"
states = append(states, state)
return states
}