prometheus/storage/metric/leveldb.go
Matt T. Proud 8f4c7ece92 Destroy naked returns in half of corpus.
The use of naked return values is frowned upon.  This is the first
of two bulk updates to remove them.
2013-05-16 10:53:25 +03:00

971 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"
)
var (
leveldbChunkSize = flag.Int("leveldbChunkSize", 200, "Maximum number of samples stored under one key.")
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 (
// 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 {
var (
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
}
var (
sortingSemaphore = make(chan bool, sortConcurrency)
doneSorting sync.WaitGroup
)
for i := 0; i < sortConcurrency; i++ {
sortingSemaphore <- true
}
for _, samples := range fingerprintToSamples {
doneSorting.Add(1)
go func(samples model.Samples) {
<-sortingSemaphore
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 fingerprint := range fingerprintSet {
fingerprints = append(fingerprints, fingerprint.(model.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 fingerprint := range fingerprintSet {
fingerprints = append(fingerprints, fingerprint.(model.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 {
key := &dto.Fingerprint{}
value := &dto.MetricHighWatermark{}
raw := []byte{}
newestSampleTimestamp := samples[len(samples)-1].Timestamp
keyEncoded := coding.NewPBEncoder(key)
key.Signature = proto.String(fingerprint.ToRowKey())
raw, err = l.MetricHighWatermarks.Get(keyEncoded)
if err != nil {
return
}
if raw != nil {
err = proto.Unmarshal(raw, value)
if err != nil {
return
}
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
}
return
}
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())
var (
fingerprintToSamples = groupByFingerprint(samples)
indexErrChan = make(chan error, 1)
watermarkErrChan = make(chan error, 1)
)
go func(groups map[model.Fingerprint]model.Samples) {
var (
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) (samples model.Values) {
panic("Not implemented")
}
func (l LevelDBMetricPersistence) GetBoundaryValues(f model.Fingerprint, i model.Interval) (first model.Values, second model.Values) {
panic("Not implemented")
}
func (l *LevelDBMetricPersistence) GetRangeValues(f model.Fingerprint, i model.Interval) (samples 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
}
func (l *LevelDBMetricPersistence) ForEachSample(builder IteratorsForFingerprintBuilder) (err error) {
panic("not implemented")
}
// 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
}