예제 #1
0
파일: decode.go 프로젝트: algoadv/etcd
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
}
예제 #2
0
파일: registry.go 프로젝트: algoadv/etcd
func (r *registry) giveMetricFamily(mf *dto.MetricFamily) {
	mf.Reset()
	select {
	case r.metricFamilyPool <- mf:
	default:
	}
}
예제 #3
0
파일: decode.go 프로젝트: algoadv/etcd
func extractSamples(f *dto.MetricFamily, o *DecodeOptions) model.Vector {
	switch f.GetType() {
	case dto.MetricType_COUNTER:
		return extractCounter(o, f)
	case dto.MetricType_GAUGE:
		return extractGauge(o, f)
	case dto.MetricType_SUMMARY:
		return extractSummary(o, f)
	case dto.MetricType_UNTYPED:
		return extractUntyped(o, f)
	case dto.MetricType_HISTOGRAM:
		return extractHistogram(o, f)
	}
	panic("expfmt.extractSamples: unknown metric family type")
}
예제 #4
0
파일: decode.go 프로젝트: algoadv/etcd
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,
			})
		}

		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,
		})

		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
}
예제 #5
0
파일: registry.go 프로젝트: algoadv/etcd
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
}
예제 #6
0
파일: text_create.go 프로젝트: algoadv/etcd
// 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
}
예제 #7
0
파일: decode.go 프로젝트: algoadv/etcd
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,
			})
		}

		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,
		})

		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 an 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
}