Exemple #1
0
func newMetricFamily(dtoMF *dto.MetricFamily) *metricFamily {
	mf := &metricFamily{
		Name:    dtoMF.GetName(),
		Help:    dtoMF.GetHelp(),
		Type:    dtoMF.GetType().String(),
		Metrics: make([]interface{}, len(dtoMF.Metric)),
	}
	for i, m := range dtoMF.Metric {
		if dtoMF.GetType() == dto.MetricType_SUMMARY {
			mf.Metrics[i] = summary{
				Labels:    makeLabels(m),
				Quantiles: makeQuantiles(m),
				Count:     fmt.Sprint(m.GetSummary().GetSampleCount()),
				Sum:       fmt.Sprint(m.GetSummary().GetSampleSum()),
			}
		} else if dtoMF.GetType() == dto.MetricType_HISTOGRAM {
			mf.Metrics[i] = histogram{
				Labels:  makeLabels(m),
				Buckets: makeBuckets(m),
				Count:   fmt.Sprint(m.GetHistogram().GetSampleCount()),
				Sum:     fmt.Sprint(m.GetSummary().GetSampleSum()),
			}
		} else {
			mf.Metrics[i] = metric{
				Labels: makeLabels(m),
				Value:  fmt.Sprint(getValue(m)),
			}
		}
	}
	return mf
}
Exemple #2
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func scrapeMetrics(s *httptest.Server) ([]*prometheuspb.MetricFamily, error) {
	req, err := http.NewRequest("GET", s.URL+"/metrics", nil)
	if err != nil {
		return nil, fmt.Errorf("Unable to create http request: %v", err)
	}
	// Ask the prometheus exporter for its text protocol buffer format, since it's
	// much easier to parse than its plain-text format. Don't use the serialized
	// proto representation since it uses a non-standard varint delimiter between
	// metric families.
	req.Header.Add("Accept", scrapeRequestHeader)

	client := &http.Client{}
	resp, err := client.Do(req)
	if err != nil {
		return nil, fmt.Errorf("Unable to contact metrics endpoint of master: %v", err)
	}
	defer resp.Body.Close()
	if resp.StatusCode != 200 {
		return nil, fmt.Errorf("Non-200 response trying to scrape metrics from master: %v", resp)
	}

	// Each line in the response body should contain all the data for a single metric.
	var metrics []*prometheuspb.MetricFamily
	scanner := bufio.NewScanner(resp.Body)
	for scanner.Scan() {
		var metric prometheuspb.MetricFamily
		if err := proto.UnmarshalText(scanner.Text(), &metric); err != nil {
			return nil, fmt.Errorf("Failed to unmarshal line of metrics response: %v", err)
		}
		glog.Infof("Got metric %q", metric.GetName())
		metrics = append(metrics, &metric)
	}
	return metrics, nil
}
Exemple #3
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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
}
func extractUntyped(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
	samples := make(model.Samples, 0, len(f.Metric))

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

		sample := &model.Sample{
			Metric: model.Metric{},
			Value:  model.SampleValue(m.Untyped.GetValue()),
		}
		samples = append(samples, sample)

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

		metric := sample.Metric
		for _, p := range m.Label {
			metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
		}
		metric[model.MetricNameLabel] = model.LabelValue(f.GetName())
	}

	return out.Ingest(samples)
}
func extractCounter(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
	samples := make(model.Samples, 0, len(f.Metric))

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

		sample := new(model.Sample)
		samples = append(samples, sample)

		if m.TimestampMs != nil {
			sample.Timestamp = model.TimestampFromUnix(*m.TimestampMs / 1000)
		} else {
			sample.Timestamp = o.Timestamp
		}
		sample.Metric = model.Metric{}
		metric := sample.Metric

		for _, p := range m.Label {
			metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
		}

		metric[model.MetricNameLabel] = model.LabelValue(f.GetName())

		sample.Value = model.SampleValue(m.Counter.GetValue())
	}

	return out.Ingest(&Result{Samples: samples})
}
Exemple #6
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// Decode implements the Decoder interface.
func (d *protoDecoder) Decode(v *dto.MetricFamily) error {
	_, err := pbutil.ReadDelimited(d.r, v)
	if err != nil {
		return err
	}
	if !model.IsValidMetricName(model.LabelValue(v.GetName())) {
		return fmt.Errorf("invalid metric name %q", v.GetName())
	}
	for _, m := range v.GetMetric() {
		if m == nil {
			continue
		}
		for _, l := range m.GetLabel() {
			if l == nil {
				continue
			}
			if !model.LabelValue(l.GetValue()).IsValid() {
				return fmt.Errorf("invalid label value %q", l.GetValue())
			}
			if !model.LabelName(l.GetName()).IsValid() {
				return fmt.Errorf("invalid label name %q", l.GetName())
			}
		}
	}
	return nil
}
func (collector *PrometheusCollector) GetSpec() []v1.MetricSpec {

	response, err := collector.httpClient.Get(collector.configFile.Endpoint.URL)
	if err != nil {
		return nil
	}
	defer response.Body.Close()

	if response.StatusCode != http.StatusOK {
		return nil
	}

	dec := expfmt.NewDecoder(response.Body, expfmt.ResponseFormat(response.Header))

	var specs []v1.MetricSpec

	for {
		d := rawmodel.MetricFamily{}
		if err = dec.Decode(&d); err != nil {
			break
		}
		name := d.GetName()
		if len(name) == 0 {
			continue
		}
		// If metrics to collect is specified, skip any metrics not in the list to collect.
		if _, ok := collector.metricsSet[name]; collector.metricsSet != nil && !ok {
			continue
		}

		spec := v1.MetricSpec{
			Name:   name,
			Type:   metricType(d.GetType()),
			Format: v1.FloatType,
		}
		specs = append(specs, spec)
	}

	if err != nil && err != io.EOF {
		return nil
	}

	return specs
}
Exemple #8
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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 checkDescConsistency(
	metricFamily *dto.MetricFamily,
	dtoMetric *dto.Metric,
	desc *Desc,
) error {
	// Desc help consistency with metric family help.
	if metricFamily.GetHelp() != desc.help {
		return fmt.Errorf(
			"collected metric %s %s has help %q but should have %q",
			metricFamily.GetName(), dtoMetric, metricFamily.GetHelp(), desc.help,
		)
	}

	// Is the desc consistent with the content of the metric?
	lpsFromDesc := make([]*dto.LabelPair, 0, len(dtoMetric.Label))
	lpsFromDesc = append(lpsFromDesc, desc.constLabelPairs...)
	for _, l := range desc.variableLabels {
		lpsFromDesc = append(lpsFromDesc, &dto.LabelPair{
			Name: proto.String(l),
		})
	}
	if len(lpsFromDesc) != len(dtoMetric.Label) {
		return fmt.Errorf(
			"labels in collected metric %s %s are inconsistent with descriptor %s",
			metricFamily.GetName(), dtoMetric, desc,
		)
	}
	sort.Sort(LabelPairSorter(lpsFromDesc))
	for i, lpFromDesc := range lpsFromDesc {
		lpFromMetric := dtoMetric.Label[i]
		if lpFromDesc.GetName() != lpFromMetric.GetName() ||
			lpFromDesc.Value != nil && lpFromDesc.GetValue() != lpFromMetric.GetValue() {
			return fmt.Errorf(
				"labels in collected metric %s %s are inconsistent with descriptor %s",
				metricFamily.GetName(), dtoMetric, desc,
			)
		}
	}
	return nil
}
Exemple #10
0
func (r *registry) checkConsistency(metricFamily *dto.MetricFamily, dtoMetric *dto.Metric, desc *Desc, metricHashes map[uint64]struct{}) error {

	// Type consistency with metric family.
	if metricFamily.GetType() == dto.MetricType_GAUGE && dtoMetric.Gauge == nil ||
		metricFamily.GetType() == dto.MetricType_COUNTER && dtoMetric.Counter == nil ||
		metricFamily.GetType() == dto.MetricType_SUMMARY && dtoMetric.Summary == nil ||
		metricFamily.GetType() == dto.MetricType_HISTOGRAM && dtoMetric.Histogram == nil ||
		metricFamily.GetType() == dto.MetricType_UNTYPED && dtoMetric.Untyped == nil {
		return fmt.Errorf(
			"collected metric %s %s is not a %s",
			metricFamily.GetName(), dtoMetric, metricFamily.GetType(),
		)
	}

	// Is the metric unique (i.e. no other metric with the same name and the same label values)?
	h := fnv.New64a()
	var buf bytes.Buffer
	buf.WriteString(metricFamily.GetName())
	buf.WriteByte(separatorByte)
	h.Write(buf.Bytes())
	// Make sure label pairs are sorted. We depend on it for the consistency
	// check. Label pairs must be sorted by contract. But the point of this
	// method is to check for contract violations. So we better do the sort
	// now.
	sort.Sort(LabelPairSorter(dtoMetric.Label))
	for _, lp := range dtoMetric.Label {
		buf.Reset()
		buf.WriteString(lp.GetValue())
		buf.WriteByte(separatorByte)
		h.Write(buf.Bytes())
	}
	metricHash := h.Sum64()
	if _, exists := metricHashes[metricHash]; exists {
		return fmt.Errorf(
			"collected metric %s %s was collected before with the same name and label values",
			metricFamily.GetName(), dtoMetric,
		)
	}
	metricHashes[metricHash] = struct{}{}

	if desc == nil {
		return nil // Nothing left to check if we have no desc.
	}

	// Desc consistency with metric family.
	if metricFamily.GetName() != desc.fqName {
		return fmt.Errorf(
			"collected metric %s %s has name %q but should have %q",
			metricFamily.GetName(), dtoMetric, metricFamily.GetName(), desc.fqName,
		)
	}
	if metricFamily.GetHelp() != desc.help {
		return fmt.Errorf(
			"collected metric %s %s has help %q but should have %q",
			metricFamily.GetName(), dtoMetric, metricFamily.GetHelp(), desc.help,
		)
	}

	// Is the desc consistent with the content of the metric?
	lpsFromDesc := make([]*dto.LabelPair, 0, len(dtoMetric.Label))
	lpsFromDesc = append(lpsFromDesc, desc.constLabelPairs...)
	for _, l := range desc.variableLabels {
		lpsFromDesc = append(lpsFromDesc, &dto.LabelPair{
			Name: proto.String(l),
		})
	}
	if len(lpsFromDesc) != len(dtoMetric.Label) {
		return fmt.Errorf(
			"labels in collected metric %s %s are inconsistent with descriptor %s",
			metricFamily.GetName(), dtoMetric, desc,
		)
	}
	sort.Sort(LabelPairSorter(lpsFromDesc))
	for i, lpFromDesc := range lpsFromDesc {
		lpFromMetric := dtoMetric.Label[i]
		if lpFromDesc.GetName() != lpFromMetric.GetName() ||
			lpFromDesc.Value != nil && lpFromDesc.GetValue() != lpFromMetric.GetValue() {
			return fmt.Errorf(
				"labels in collected metric %s %s are inconsistent with descriptor %s",
				metricFamily.GetName(), dtoMetric, desc,
			)
		}
	}

	r.mtx.RLock() // Remaining checks need the read lock.
	defer r.mtx.RUnlock()

	// Is the desc registered?
	if _, exist := r.descIDs[desc.id]; !exist {
		return fmt.Errorf(
			"collected metric %s %s with unregistered descriptor %s",
			metricFamily.GetName(), dtoMetric, desc,
		)
	}

	return nil
}
// checkMetricConsistency checks if the provided Metric is consistent with the
// provided MetricFamily. It also hashed the Metric labels and the MetricFamily
// name. If the resulting hash is alread in the provided metricHashes, an error
// is returned. If not, it is added to metricHashes. The provided dimHashes maps
// MetricFamily names to their dimHash (hashed sorted label names). If dimHashes
// doesn't yet contain a hash for the provided MetricFamily, it is
// added. Otherwise, an error is returned if the existing dimHashes in not equal
// the calculated dimHash.
func checkMetricConsistency(
	metricFamily *dto.MetricFamily,
	dtoMetric *dto.Metric,
	metricHashes map[uint64]struct{},
	dimHashes map[string]uint64,
) error {
	// Type consistency with metric family.
	if metricFamily.GetType() == dto.MetricType_GAUGE && dtoMetric.Gauge == nil ||
		metricFamily.GetType() == dto.MetricType_COUNTER && dtoMetric.Counter == nil ||
		metricFamily.GetType() == dto.MetricType_SUMMARY && dtoMetric.Summary == nil ||
		metricFamily.GetType() == dto.MetricType_HISTOGRAM && dtoMetric.Histogram == nil ||
		metricFamily.GetType() == dto.MetricType_UNTYPED && dtoMetric.Untyped == nil {
		return fmt.Errorf(
			"collected metric %s %s is not a %s",
			metricFamily.GetName(), dtoMetric, metricFamily.GetType(),
		)
	}

	// Is the metric unique (i.e. no other metric with the same name and the same label values)?
	h := hashNew()
	h = hashAdd(h, metricFamily.GetName())
	h = hashAddByte(h, separatorByte)
	dh := hashNew()
	// Make sure label pairs are sorted. We depend on it for the consistency
	// check.
	sort.Sort(LabelPairSorter(dtoMetric.Label))
	for _, lp := range dtoMetric.Label {
		h = hashAdd(h, lp.GetValue())
		h = hashAddByte(h, separatorByte)
		dh = hashAdd(dh, lp.GetName())
		dh = hashAddByte(dh, separatorByte)
	}
	if _, exists := metricHashes[h]; exists {
		return fmt.Errorf(
			"collected metric %s %s was collected before with the same name and label values",
			metricFamily.GetName(), dtoMetric,
		)
	}
	if dimHash, ok := dimHashes[metricFamily.GetName()]; ok {
		if dimHash != dh {
			return fmt.Errorf(
				"collected metric %s %s has label dimensions inconsistent with previously collected metrics in the same metric family",
				metricFamily.GetName(), dtoMetric,
			)
		}
	} else {
		dimHashes[metricFamily.GetName()] = dh
	}
	metricHashes[h] = struct{}{}
	return nil
}
Exemple #12
0
// MetricFamilyToText converts a MetricFamily proto message into text format and
// writes the resulting lines to 'out'. It returns the number of bytes written
// and any error encountered.  This function does not perform checks on the
// content of the metric and label names, i.e. invalid metric or label names
// will result in invalid text format output.
// This method fulfills the type 'prometheus.encoder'.
func MetricFamilyToText(out io.Writer, in *dto.MetricFamily) (int, error) {
	var written int

	// Fail-fast checks.
	if len(in.Metric) == 0 {
		return written, fmt.Errorf("MetricFamily has no metrics: %s", in)
	}
	name := in.GetName()
	if name == "" {
		return written, fmt.Errorf("MetricFamily has no name: %s", in)
	}

	// Comments, first HELP, then TYPE.
	if in.Help != nil {
		n, err := fmt.Fprintf(
			out, "# HELP %s %s\n",
			name, escapeString(*in.Help, false),
		)
		written += n
		if err != nil {
			return written, err
		}
	}
	metricType := in.GetType()
	n, err := fmt.Fprintf(
		out, "# TYPE %s %s\n",
		name, strings.ToLower(metricType.String()),
	)
	written += n
	if err != nil {
		return written, err
	}

	// Finally the samples, one line for each.
	for _, metric := range in.Metric {
		switch metricType {
		case dto.MetricType_COUNTER:
			if metric.Counter == nil {
				return written, fmt.Errorf(
					"expected counter in metric %s %s", name, metric,
				)
			}
			n, err = writeSample(
				name, metric, "", "",
				metric.Counter.GetValue(),
				out,
			)
		case dto.MetricType_GAUGE:
			if metric.Gauge == nil {
				return written, fmt.Errorf(
					"expected gauge in metric %s %s", name, metric,
				)
			}
			n, err = writeSample(
				name, metric, "", "",
				metric.Gauge.GetValue(),
				out,
			)
		case dto.MetricType_UNTYPED:
			if metric.Untyped == nil {
				return written, fmt.Errorf(
					"expected untyped in metric %s %s", name, metric,
				)
			}
			n, err = writeSample(
				name, metric, "", "",
				metric.Untyped.GetValue(),
				out,
			)
		case dto.MetricType_SUMMARY:
			if metric.Summary == nil {
				return written, fmt.Errorf(
					"expected summary in metric %s %s", name, metric,
				)
			}
			for _, q := range metric.Summary.Quantile {
				n, err = writeSample(
					name, metric,
					model.QuantileLabel, fmt.Sprint(q.GetQuantile()),
					q.GetValue(),
					out,
				)
				written += n
				if err != nil {
					return written, err
				}
			}
			n, err = writeSample(
				name+"_sum", metric, "", "",
				metric.Summary.GetSampleSum(),
				out,
			)
			if err != nil {
				return written, err
			}
			written += n
			n, err = writeSample(
				name+"_count", metric, "", "",
				float64(metric.Summary.GetSampleCount()),
				out,
			)
		case dto.MetricType_HISTOGRAM:
			if metric.Histogram == nil {
				return written, fmt.Errorf(
					"expected histogram in metric %s %s", name, metric,
				)
			}
			infSeen := false
			for _, q := range metric.Histogram.Bucket {
				n, err = writeSample(
					name+"_bucket", metric,
					model.BucketLabel, fmt.Sprint(q.GetUpperBound()),
					float64(q.GetCumulativeCount()),
					out,
				)
				written += n
				if err != nil {
					return written, err
				}
				if math.IsInf(q.GetUpperBound(), +1) {
					infSeen = true
				}
			}
			if !infSeen {
				n, err = writeSample(
					name+"_bucket", metric,
					model.BucketLabel, "+Inf",
					float64(metric.Histogram.GetSampleCount()),
					out,
				)
				if err != nil {
					return written, err
				}
				written += n
			}
			n, err = writeSample(
				name+"_sum", metric, "", "",
				metric.Histogram.GetSampleSum(),
				out,
			)
			if err != nil {
				return written, err
			}
			written += n
			n, err = writeSample(
				name+"_count", metric, "", "",
				float64(metric.Histogram.GetSampleCount()),
				out,
			)
		default:
			return written, fmt.Errorf(
				"unexpected type in metric %s %s", name, metric,
			)
		}
		written += n
		if err != nil {
			return written, err
		}
	}
	return written, nil
}
Exemple #13
0
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 extractSummary(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
	samples := make(model.Samples, 0, len(f.Metric))

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

		timestamp := o.Timestamp
		if m.TimestampMs != nil {
			timestamp = model.TimestampFromUnix(*m.TimestampMs / 1000)
		}

		for _, q := range m.Summary.Quantile {
			sample := new(model.Sample)
			samples = append(samples, sample)

			sample.Timestamp = timestamp
			sample.Metric = model.Metric{}
			metric := sample.Metric

			for _, p := range m.Label {
				metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			// BUG(matt): Update other names to "quantile".
			metric[model.LabelName("quantile")] = model.LabelValue(fmt.Sprint(q.GetQuantile()))

			metric[model.MetricNameLabel] = model.LabelValue(f.GetName())

			sample.Value = model.SampleValue(q.GetValue())
		}

		if m.Summary.SampleSum != nil {
			sum := new(model.Sample)
			sum.Timestamp = timestamp
			metric := model.Metric{}
			for _, p := range m.Label {
				metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_sum")
			sum.Metric = metric
			sum.Value = model.SampleValue(m.Summary.GetSampleSum())
			samples = append(samples, sum)
		}

		if m.Summary.SampleCount != nil {
			count := new(model.Sample)
			count.Timestamp = timestamp
			metric := model.Metric{}
			for _, p := range m.Label {
				metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_count")
			count.Metric = metric
			count.Value = model.SampleValue(m.Summary.GetSampleCount())
			samples = append(samples, count)
		}
	}

	return out.Ingest(&Result{Samples: samples})
}
func extractHistogram(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
	samples := make(model.Samples, 0, len(f.Metric))

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

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

		infSeen := false

		for _, q := range m.Histogram.Bucket {
			sample := &model.Sample{
				Metric:    model.Metric{},
				Value:     model.SampleValue(q.GetCumulativeCount()),
				Timestamp: timestamp,
			}
			samples = append(samples, sample)

			metric := sample.Metric
			for _, p := range m.Label {
				metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			metric[model.LabelName(model.BucketLabel)] = model.LabelValue(fmt.Sprint(q.GetUpperBound()))
			metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_bucket")

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

		if m.Histogram.SampleSum != nil {
			sum := &model.Sample{
				Metric:    model.Metric{},
				Value:     model.SampleValue(m.Histogram.GetSampleSum()),
				Timestamp: timestamp,
			}
			samples = append(samples, sum)

			metric := sum.Metric
			for _, p := range m.Label {
				metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_sum")
		}

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

			metric := count.Metric
			for _, p := range m.Label {
				metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_count")

			if !infSeen {
				infBucket := &model.Sample{
					Metric:    model.Metric{},
					Value:     count.Value,
					Timestamp: timestamp,
				}
				samples = append(samples, infBucket)

				metric := infBucket.Metric
				for _, p := range m.Label {
					metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
				}
				metric[model.LabelName(model.BucketLabel)] = model.LabelValue("+Inf")
				metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_bucket")
			}
		}
	}

	return out.Ingest(samples)
}
func extractSummary(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
	samples := make(model.Samples, 0, len(f.Metric))

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

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

		for _, q := range m.Summary.Quantile {
			sample := &model.Sample{
				Metric:    model.Metric{},
				Value:     model.SampleValue(q.GetValue()),
				Timestamp: timestamp,
			}
			samples = append(samples, sample)

			metric := sample.Metric
			for _, p := range m.Label {
				metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			// BUG(matt): Update other names to "quantile".
			metric[model.LabelName(model.QuantileLabel)] = model.LabelValue(fmt.Sprint(q.GetQuantile()))
			metric[model.MetricNameLabel] = model.LabelValue(f.GetName())
		}

		if m.Summary.SampleSum != nil {
			sum := &model.Sample{
				Metric:    model.Metric{},
				Value:     model.SampleValue(m.Summary.GetSampleSum()),
				Timestamp: timestamp,
			}
			samples = append(samples, sum)

			metric := sum.Metric
			for _, p := range m.Label {
				metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_sum")
		}

		if m.Summary.SampleCount != nil {
			count := &model.Sample{
				Metric:    model.Metric{},
				Value:     model.SampleValue(m.Summary.GetSampleCount()),
				Timestamp: timestamp,
			}
			samples = append(samples, count)

			metric := count.Metric
			for _, p := range m.Label {
				metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
			}
			metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_count")
		}
	}

	return out.Ingest(samples)
}