Golang model.Metric函数代码示例

func extractSummary(o *DecodeOptions, f *dto.MetricFamily) model.Vector {
	samples := make(model.Vector, 0, len(f.Metric))

	for _, m := range f.Metric {
		if m.Summary == nil {
			continue
		}

		timestamp := o.Timestamp
		if m.TimestampMs != nil {
			timestamp = model.TimeFromUnixNano(*m.TimestampMs * 1000000)
		}

		for _, q := range m.Summary.Quantile {
			lset := make(model.LabelSet, len(m.Label)+2)
			for _, p := range m.Label {
				lset[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			// BUG(matt): Update other names to "quantile".
			lset[model.LabelName(model.QuantileLabel)] = model.LabelValue(fmt.Sprint(q.GetQuantile()))
			lset[model.MetricNameLabel] = model.LabelValue(f.GetName())

			samples = append(samples, &model.Sample{
				Metric:    model.Metric(lset),
				Value:     model.SampleValue(q.GetValue()),
				Timestamp: timestamp,
			})
		}

		if m.Summary.SampleSum != nil {
			lset := make(model.LabelSet, len(m.Label)+1)
			for _, p := range m.Label {
				lset[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			lset[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_sum")

			samples = append(samples, &model.Sample{
				Metric:    model.Metric(lset),
				Value:     model.SampleValue(m.Summary.GetSampleSum()),
				Timestamp: timestamp,
			})
		}

		if m.Summary.SampleCount != nil {
			lset := make(model.LabelSet, len(m.Label)+1)
			for _, p := range m.Label {
				lset[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			lset[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_count")

			samples = append(samples, &model.Sample{
				Metric:    model.Metric(lset),
				Value:     model.SampleValue(m.Summary.GetSampleCount()),
				Timestamp: timestamp,
			})
		}
	}

	return samples
}

func (p *persistence) rebuildLabelIndexes(
	fpToSeries map[model.Fingerprint]*memorySeries,
) error {
	count := 0
	log.Info("Rebuilding label indexes.")
	log.Info("Indexing metrics in memory.")
	for fp, s := range fpToSeries {
		p.indexMetric(fp, s.metric)
		count++
		if count%10000 == 0 {
			log.Infof("%d metrics queued for indexing.", count)
		}
	}
	log.Info("Indexing archived metrics.")
	var fp codable.Fingerprint
	var m codable.Metric
	if err := p.archivedFingerprintToMetrics.ForEach(func(kv index.KeyValueAccessor) error {
		if err := kv.Key(&fp); err != nil {
			return err
		}
		if err := kv.Value(&m); err != nil {
			return err
		}
		p.indexMetric(model.Fingerprint(fp), model.Metric(m))
		count++
		if count%10000 == 0 {
			log.Infof("%d metrics queued for indexing.", count)
		}
		return nil
	}); err != nil {
		return err
	}
	log.Info("All requests for rebuilding the label indexes queued. (Actual processing may lag behind.)")
	return nil
}

func extractUntyped(o *DecodeOptions, f *dto.MetricFamily) model.Vector {
	samples := make(model.Vector, 0, len(f.Metric))

	for _, m := range f.Metric {
		if m.Untyped == nil {
			continue
		}

		lset := make(model.LabelSet, len(m.Label)+1)
		for _, p := range m.Label {
			lset[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
		}
		lset[model.MetricNameLabel] = model.LabelValue(f.GetName())

		smpl := &model.Sample{
			Metric: model.Metric(lset),
			Value:  model.SampleValue(m.Untyped.GetValue()),
		}

		if m.TimestampMs != nil {
			smpl.Timestamp = model.TimeFromUnixNano(*m.TimestampMs * 1000000)
		} else {
			smpl.Timestamp = o.Timestamp
		}

		samples = append(samples, smpl)
	}

	return samples
}

// Append implements storage.SampleAppender. Always returns nil.
func (s *ReloadableStorage) Append(smpl *model.Sample) error {
	s.mtx.RLock()
	defer s.mtx.RUnlock()

	if s.queue == nil {
		return nil
	}

	var snew model.Sample
	snew = *smpl
	snew.Metric = smpl.Metric.Clone()

	for ln, lv := range s.externalLabels {
		if _, ok := smpl.Metric[ln]; !ok {
			snew.Metric[ln] = lv
		}
	}
	snew.Metric = model.Metric(
		relabel.Process(model.LabelSet(snew.Metric), s.conf.WriteRelabelConfigs...))

	if snew.Metric == nil {
		return nil
	}
	s.queue.Append(&snew)
	return nil
}

// Append implements storage.SampleAppender. Always returns nil.
func (s *Storage) Append(smpl *model.Sample) error {
	s.mtx.RLock()

	var snew model.Sample
	snew = *smpl
	snew.Metric = smpl.Metric.Clone()

	for ln, lv := range s.externalLabels {
		if _, ok := smpl.Metric[ln]; !ok {
			snew.Metric[ln] = lv
		}
	}
	snew.Metric = model.Metric(
		relabel.Process(model.LabelSet(snew.Metric), s.relabelConfigs...))
	s.mtx.RUnlock()

	if snew.Metric == nil {
		return nil
	}

	for _, q := range s.queues {
		q.Append(&snew)
	}
	return nil
}

func (app relabelAppender) Append(s *model.Sample) error {
	labels := relabel.Process(model.LabelSet(s.Metric), app.relabelings...)

	// Check if the timeseries was dropped.
	if labels == nil {
		return nil
	}
	s.Metric = model.Metric(labels)

	return app.SampleAppender.Append(s)
}

func (app relabelAppender) Append(s *model.Sample) error {
	labels, err := Relabel(model.LabelSet(s.Metric), app.relabelings...)
	if err != nil {
		return fmt.Errorf("metric relabeling error %s: %s", s.Metric, err)
	}
	// Check if the timeseries was dropped.
	if labels == nil {
		return nil
	}
	s.Metric = model.Metric(labels)

	return app.SampleAppender.Append(s)
}

func (app relabelAppender) Append(s *model.Sample) {
	labels, err := Relabel(model.LabelSet(s.Metric), app.relabelings...)
	if err != nil {
		log.Errorf("Error while relabeling metric %s: %s", s.Metric, err)
		return
	}
	// Check if the timeseries was dropped.
	if labels == nil {
		return
	}
	s.Metric = model.Metric(labels)

	app.app.Append(s)
}

// metric parses a metric.
//
//		<label_set>
//		<metric_identifier> [<label_set>]
//
func (p *parser) metric() model.Metric {
	name := ""
	m := model.Metric{}

	t := p.peek().typ
	if t == itemIdentifier || t == itemMetricIdentifier {
		name = p.next().val
		t = p.peek().typ
	}
	if t != itemLeftBrace && name == "" {
		p.errorf("missing metric name or metric selector")
	}
	if t == itemLeftBrace {
		m = model.Metric(p.labelSet())
	}
	if name != "" {
		m[model.MetricNameLabel] = model.LabelValue(name)
	}
	return m
}

func (r *AlertingRule) sample(alert *Alert, ts model.Time, set bool) *model.Sample {
	metric := model.Metric(r.labels.Clone())

	for ln, lv := range alert.Labels {
		metric[ln] = lv
	}

	metric[model.MetricNameLabel] = alertMetricName
	metric[model.AlertNameLabel] = model.LabelValue(r.name)
	metric[alertStateLabel] = model.LabelValue(alert.State.String())

	s := &model.Sample{
		Metric:    metric,
		Timestamp: ts,
		Value:     0,
	}
	if set {
		s.Value = 1
	}
	return s
}

// scan works like bufio.Scanner.Scan.
func (hs *headsScanner) scan() bool {
	if hs.seriesCurrent == hs.seriesTotal || hs.err != nil {
		return false
	}

	var (
		seriesFlags      byte
		fpAsInt          uint64
		metric           codable.Metric
		persistWatermark int64
		modTimeNano      int64
		modTime          time.Time
		chunkDescsOffset int64
		savedFirstTime   int64
		numChunkDescs    int64
		firstTime        int64
		lastTime         int64
		encoding         byte
		ch               chunk.Chunk
		lastTimeHead     model.Time
	)
	if seriesFlags, hs.err = hs.r.ReadByte(); hs.err != nil {
		return false
	}
	headChunkPersisted := seriesFlags&flagHeadChunkPersisted != 0
	if fpAsInt, hs.err = codable.DecodeUint64(hs.r); hs.err != nil {
		return false
	}
	hs.fp = model.Fingerprint(fpAsInt)

	if hs.err = metric.UnmarshalFromReader(hs.r); hs.err != nil {
		return false
	}
	if hs.version != headsFormatLegacyVersion {
		// persistWatermark only present in v2.
		persistWatermark, hs.err = binary.ReadVarint(hs.r)
		if hs.err != nil {
			return false
		}
		modTimeNano, hs.err = binary.ReadVarint(hs.r)
		if hs.err != nil {
			return false
		}
		if modTimeNano != -1 {
			modTime = time.Unix(0, modTimeNano)
		}
	}
	if chunkDescsOffset, hs.err = binary.ReadVarint(hs.r); hs.err != nil {
		return false
	}
	if savedFirstTime, hs.err = binary.ReadVarint(hs.r); hs.err != nil {
		return false
	}

	if numChunkDescs, hs.err = binary.ReadVarint(hs.r); hs.err != nil {
		return false
	}
	chunkDescs := make([]*chunk.Desc, numChunkDescs)
	if hs.version == headsFormatLegacyVersion {
		if headChunkPersisted {
			persistWatermark = numChunkDescs
		} else {
			persistWatermark = numChunkDescs - 1
		}
	}
	headChunkClosed := true // Initial assumption.
	for i := int64(0); i < numChunkDescs; i++ {
		if i < persistWatermark {
			if firstTime, hs.err = binary.ReadVarint(hs.r); hs.err != nil {
				return false
			}
			if lastTime, hs.err = binary.ReadVarint(hs.r); hs.err != nil {
				return false
			}
			chunkDescs[i] = &chunk.Desc{
				ChunkFirstTime: model.Time(firstTime),
				ChunkLastTime:  model.Time(lastTime),
			}
			chunk.NumMemDescs.Inc()
		} else {
			// Non-persisted chunk.
			// If there are non-persisted chunks at all, we consider
			// the head chunk not to be closed yet.
			headChunkClosed = false
			if encoding, hs.err = hs.r.ReadByte(); hs.err != nil {
				return false
			}
			if ch, hs.err = chunk.NewForEncoding(chunk.Encoding(encoding)); hs.err != nil {
				return false
			}
			if hs.err = ch.Unmarshal(hs.r); hs.err != nil {
				return false
			}
			cd := chunk.NewDesc(ch, ch.FirstTime())
			if i < numChunkDescs-1 {
				// This is NOT the head chunk. So it's a chunk
				// to be persisted, and we need to populate lastTime.
				hs.chunksToPersistTotal++
				cd.MaybePopulateLastTime()
//.........这里部分代码省略.........

func extractHistogram(o *DecodeOptions, f *dto.MetricFamily) model.Vector {
	samples := make(model.Vector, 0, len(f.Metric))

	for _, m := range f.Metric {
		if m.Histogram == nil {
			continue
		}

		timestamp := o.Timestamp
		if m.TimestampMs != nil {
			timestamp = model.TimeFromUnixNano(*m.TimestampMs * 1000000)
		}

		infSeen := false

		for _, q := range m.Histogram.Bucket {
			lset := make(model.LabelSet, len(m.Label)+2)
			for _, p := range m.Label {
				lset[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			lset[model.LabelName(model.BucketLabel)] = model.LabelValue(fmt.Sprint(q.GetUpperBound()))
			lset[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_bucket")

			if math.IsInf(q.GetUpperBound(), +1) {
				infSeen = true
			}

			samples = append(samples, &model.Sample{
				Metric:    model.Metric(lset),
				Value:     model.SampleValue(q.GetCumulativeCount()),
				Timestamp: timestamp,
			})
		}

		if m.Histogram.SampleSum != nil {
			lset := make(model.LabelSet, len(m.Label)+1)
			for _, p := range m.Label {
				lset[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			lset[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_sum")

			samples = append(samples, &model.Sample{
				Metric:    model.Metric(lset),
				Value:     model.SampleValue(m.Histogram.GetSampleSum()),
				Timestamp: timestamp,
			})
		}

		if m.Histogram.SampleCount != nil {
			lset := make(model.LabelSet, len(m.Label)+1)
			for _, p := range m.Label {
				lset[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			lset[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_count")

			count := &model.Sample{
				Metric:    model.Metric(lset),
				Value:     model.SampleValue(m.Histogram.GetSampleCount()),
				Timestamp: timestamp,
			}
			samples = append(samples, count)

			if !infSeen {
				// Append a infinity bucket sample.
				lset := make(model.LabelSet, len(m.Label)+2)
				for _, p := range m.Label {
					lset[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
				}
				lset[model.LabelName(model.BucketLabel)] = model.LabelValue("+Inf")
				lset[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_bucket")

				samples = append(samples, &model.Sample{
					Metric:    model.Metric(lset),
					Value:     count.Value,
					Timestamp: timestamp,
				})
			}
		}
	}

	return samples
}

func (p *persistence) cleanUpArchiveIndexes(
	fpToSeries map[model.Fingerprint]*memorySeries,
	fpsSeen map[model.Fingerprint]struct{},
	fpm fpMappings,
) error {
	log.Info("Cleaning up archive indexes.")
	var fp codable.Fingerprint
	var m codable.Metric
	count := 0
	if err := p.archivedFingerprintToMetrics.ForEach(func(kv index.KeyValueAccessor) error {
		count++
		if count%10000 == 0 {
			log.Infof("%d archived metrics checked.", count)
		}
		if err := kv.Key(&fp); err != nil {
			return err
		}
		_, fpSeen := fpsSeen[model.Fingerprint(fp)]
		inMemory := false
		if fpSeen {
			_, inMemory = fpToSeries[model.Fingerprint(fp)]
		}
		if !fpSeen || inMemory {
			if inMemory {
				log.Warnf("Archive clean-up: Fingerprint %v is not archived. Purging from archive indexes.", model.Fingerprint(fp))
			}
			if !fpSeen {
				log.Warnf("Archive clean-up: Fingerprint %v is unknown. Purging from archive indexes.", model.Fingerprint(fp))
			}
			// It's fine if the fp is not in the archive indexes.
			if _, err := p.archivedFingerprintToMetrics.Delete(fp); err != nil {
				return err
			}
			// Delete from timerange index, too.
			_, err := p.archivedFingerprintToTimeRange.Delete(fp)
			return err
		}
		// fp is legitimately archived. Now we need the metric to check for a mapped fingerprint.
		if err := kv.Value(&m); err != nil {
			return err
		}
		maybeAddMapping(model.Fingerprint(fp), model.Metric(m), fpm)
		// Make sure it is in timerange index, too.
		has, err := p.archivedFingerprintToTimeRange.Has(fp)
		if err != nil {
			return err
		}
		if has {
			return nil // All good.
		}
		log.Warnf("Archive clean-up: Fingerprint %v is not in time-range index. Unarchiving it for recovery.")
		// Again, it's fine if fp is not in the archive index.
		if _, err := p.archivedFingerprintToMetrics.Delete(fp); err != nil {
			return err
		}
		cds, err := p.loadChunkDescs(model.Fingerprint(fp), 0)
		if err != nil {
			return err
		}
		series, err := newMemorySeries(model.Metric(m), cds, p.seriesFileModTime(model.Fingerprint(fp)))
		if err != nil {
			return err
		}
		fpToSeries[model.Fingerprint(fp)] = series
		return nil
	}); err != nil {
		return err
	}
	count = 0
	if err := p.archivedFingerprintToTimeRange.ForEach(func(kv index.KeyValueAccessor) error {
		count++
		if count%10000 == 0 {
			log.Infof("%d archived time ranges checked.", count)
		}
		if err := kv.Key(&fp); err != nil {
			return err
		}
		has, err := p.archivedFingerprintToMetrics.Has(fp)
		if err != nil {
			return err
		}
		if has {
			return nil // All good.
		}
		log.Warnf("Archive clean-up: Purging unknown fingerprint %v in time-range index.", fp)
		deleted, err := p.archivedFingerprintToTimeRange.Delete(fp)
		if err != nil {
			return err
		}
		if !deleted {
			log.Errorf("Fingerprint %v to be deleted from archivedFingerprintToTimeRange not found. This should never happen.", fp)
		}
		return nil
	}); err != nil {
		return err
	}
	log.Info("Clean-up of archive indexes complete.")
	return nil
}

// loadSeriesMapAndHeads loads the fingerprint to memory-series mapping and all
// the chunks contained in the checkpoint (and thus not yet persisted to series
// files). The method is capable of loading the checkpoint format v1 and v2. If
// recoverable corruption is detected, or if the dirty flag was set from the
// beginning, crash recovery is run, which might take a while. If an
// unrecoverable error is encountered, it is returned. Call this method during
// start-up while nothing else is running in storage land. This method is
// utterly goroutine-unsafe.
func (p *persistence) loadSeriesMapAndHeads() (sm *seriesMap, chunksToPersist int64, err error) {
	var chunkDescsTotal int64
	fingerprintToSeries := make(map[model.Fingerprint]*memorySeries)
	sm = &seriesMap{m: fingerprintToSeries}

	defer func() {
		if sm != nil && p.dirty {
			log.Warn("Persistence layer appears dirty.")
			err = p.recoverFromCrash(fingerprintToSeries)
			if err != nil {
				sm = nil
			}
		}
		if err == nil {
			numMemChunkDescs.Add(float64(chunkDescsTotal))
		}
	}()

	f, err := os.Open(p.headsFileName())
	if os.IsNotExist(err) {
		return sm, 0, nil
	}
	if err != nil {
		log.Warn("Could not open heads file:", err)
		p.dirty = true
		return
	}
	defer f.Close()
	r := bufio.NewReaderSize(f, fileBufSize)

	buf := make([]byte, len(headsMagicString))
	if _, err := io.ReadFull(r, buf); err != nil {
		log.Warn("Could not read from heads file:", err)
		p.dirty = true
		return sm, 0, nil
	}
	magic := string(buf)
	if magic != headsMagicString {
		log.Warnf(
			"unexpected magic string, want %q, got %q",
			headsMagicString, magic,
		)
		p.dirty = true
		return
	}
	version, err := binary.ReadVarint(r)
	if (version != headsFormatVersion && version != headsFormatLegacyVersion) || err != nil {
		log.Warnf("unknown heads format version, want %d", headsFormatVersion)
		p.dirty = true
		return sm, 0, nil
	}
	numSeries, err := codable.DecodeUint64(r)
	if err != nil {
		log.Warn("Could not decode number of series:", err)
		p.dirty = true
		return sm, 0, nil
	}

	for ; numSeries > 0; numSeries-- {
		seriesFlags, err := r.ReadByte()
		if err != nil {
			log.Warn("Could not read series flags:", err)
			p.dirty = true
			return sm, chunksToPersist, nil
		}
		headChunkPersisted := seriesFlags&flagHeadChunkPersisted != 0
		fp, err := codable.DecodeUint64(r)
		if err != nil {
			log.Warn("Could not decode fingerprint:", err)
			p.dirty = true
			return sm, chunksToPersist, nil
		}
		var metric codable.Metric
		if err := metric.UnmarshalFromReader(r); err != nil {
			log.Warn("Could not decode metric:", err)
			p.dirty = true
			return sm, chunksToPersist, nil
		}
		var persistWatermark int64
		var modTime time.Time
		if version != headsFormatLegacyVersion {
			// persistWatermark only present in v2.
			persistWatermark, err = binary.ReadVarint(r)
			if err != nil {
				log.Warn("Could not decode persist watermark:", err)
				p.dirty = true
				return sm, chunksToPersist, nil
			}
			modTimeNano, err := binary.ReadVarint(r)
			if err != nil {
				log.Warn("Could not decode modification time:", err)
				p.dirty = true
//.........这里部分代码省略.........

func (t *Target) scrape(sampleAppender storage.SampleAppender) (err error) {
	start := time.Now()
	baseLabels := t.BaseLabels()

	t.RLock()
	var (
		honorLabels          = t.honorLabels
		httpClient           = t.httpClient
		metricRelabelConfigs = t.metricRelabelConfigs
	)
	t.RUnlock()

	defer func() {
		t.status.setLastError(err)
		recordScrapeHealth(sampleAppender, start, baseLabels, t.status.Health(), time.Since(start))
	}()

	req, err := http.NewRequest("GET", t.URL().String(), nil)
	if err != nil {
		panic(err)
	}
	req.Header.Add("Accept", acceptHeader)

	resp, err := httpClient.Do(req)
	if err != nil {
		return err
	}
	if resp.StatusCode != http.StatusOK {
		return fmt.Errorf("server returned HTTP status %s", resp.Status)
	}

	dec, err := expfmt.NewDecoder(resp.Body, resp.Header)
	if err != nil {
		return err
	}
	defer resp.Body.Close()

	sdec := expfmt.SampleDecoder{
		Dec: dec,
		Opts: &expfmt.DecodeOptions{
			Timestamp: model.TimeFromUnixNano(start.UnixNano()),
		},
	}

	t.ingestedSamples = make(chan model.Vector, ingestedSamplesCap)

	go func() {
		for {
			// TODO(fabxc): Changex the SampleAppender interface to return an error
			// so we can proceed based on the status and don't leak goroutines trying
			// to append a single sample after dropping all the other ones.
			//
			// This will also allow use to reuse this vector and save allocations.
			var samples model.Vector
			if err = sdec.Decode(&samples); err != nil {
				break
			}
			if err = t.ingest(samples); err != nil {
				break
			}
		}
		close(t.ingestedSamples)
	}()

	for samples := range t.ingestedSamples {
		for _, s := range samples {
			if honorLabels {
				// Merge the metric with the baseLabels for labels not already set in the
				// metric. This also considers labels explicitly set to the empty string.
				for ln, lv := range baseLabels {
					if _, ok := s.Metric[ln]; !ok {
						s.Metric[ln] = lv
					}
				}
			} else {
				// Merge the ingested metric with the base label set. On a collision the
				// value of the label is stored in a label prefixed with the exported prefix.
				for ln, lv := range baseLabels {
					if v, ok := s.Metric[ln]; ok && v != "" {
						s.Metric[model.ExportedLabelPrefix+ln] = v
					}
					s.Metric[ln] = lv
				}
			}
			// Avoid the copy in Relabel if there are no configs.
			if len(metricRelabelConfigs) > 0 {
				labels, err := Relabel(model.LabelSet(s.Metric), metricRelabelConfigs...)
				if err != nil {
					log.Errorf("Error while relabeling metric %s of instance %s: %s", s.Metric, req.URL, err)
					continue
				}
				// Check if the timeseries was dropped.
				if labels == nil {
					continue
				}
				s.Metric = model.Metric(labels)
			}
			sampleAppender.Append(s)
		}
	}
//.........这里部分代码省略.........