vendor/github.com/prometheus/common/expfmt/decode.go - cloudstack-kubernetes-provider - Git at Google

 // Copyright 2015 The Prometheus Authors
 // 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 expfmt

 import (
 	"fmt"
 	"io"
 	"math"
 	"mime"
 	"net/http"

 	dto "github.com/prometheus/client_model/go"

 	"github.com/matttproud/golang_protobuf_extensions/pbutil"
 	"github.com/prometheus/common/model"
 )

 // Decoder types decode an input stream into metric families.
 type Decoder interface {
 	Decode(*dto.MetricFamily) error
 }

 // DecodeOptions contains options used by the Decoder and in sample extraction.
 type DecodeOptions struct {
 	// Timestamp is added to each value from the stream that has no explicit timestamp set.
 	Timestamp model.Time
 }

 // ResponseFormat extracts the correct format from a HTTP response header.
 // If no matching format can be found FormatUnknown is returned.
 func ResponseFormat(h http.Header) Format {
 	ct := h.Get(hdrContentType)

 	mediatype, params, err := mime.ParseMediaType(ct)
 	if err != nil {
 		return FmtUnknown
 	}

 	const textType = "text/plain"

 	switch mediatype {
 	case ProtoType:
 		if p, ok := params["proto"]; ok && p != ProtoProtocol {
 			return FmtUnknown
 		}
 		if e, ok := params["encoding"]; ok && e != "delimited" {
 			return FmtUnknown
 		}
 		return FmtProtoDelim

 	case textType:
 		if v, ok := params["version"]; ok && v != TextVersion {
 			return FmtUnknown
 		}
 		return FmtText
 	}

 	return FmtUnknown
 }

 // NewDecoder returns a new decoder based on the given input format.
 // If the input format does not imply otherwise, a text format decoder is returned.
 func NewDecoder(r io.Reader, format Format) Decoder {
 	switch format {
 	case FmtProtoDelim:
 		return &protoDecoder{r: r}
 	}
 	return &textDecoder{r: r}
 }

 // protoDecoder implements the Decoder interface for protocol buffers.
 type protoDecoder struct {
 	r io.Reader
 }

 // 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
 }

 // textDecoder implements the Decoder interface for the text protocol.
 type textDecoder struct {
 	r    io.Reader
 	p    TextParser
 	fams []*dto.MetricFamily
 }

 // Decode implements the Decoder interface.
 func (d *textDecoder) Decode(v *dto.MetricFamily) error {
 	// TODO(fabxc): Wrap this as a line reader to make streaming safer.
 	if len(d.fams) == 0 {
 		// No cached metric families, read everything and parse metrics.
 		fams, err := d.p.TextToMetricFamilies(d.r)
 		if err != nil {
 			return err
 		}
 		if len(fams) == 0 {
 			return io.EOF
 		}
 		d.fams = make([]*dto.MetricFamily, 0, len(fams))
 		for _, f := range fams {
 			d.fams = append(d.fams, f)
 		}
 	}

 	*v = *d.fams[0]
 	d.fams = d.fams[1:]

 	return nil
 }

 // SampleDecoder wraps a Decoder to extract samples from the metric families
 // decoded by the wrapped Decoder.
 type SampleDecoder struct {
 	Dec  Decoder
 	Opts *DecodeOptions

 	f dto.MetricFamily
 }

 // Decode calls the Decode method of the wrapped Decoder and then extracts the
 // samples from the decoded MetricFamily into the provided model.Vector.
 func (sd *SampleDecoder) Decode(s *model.Vector) error {
 	err := sd.Dec.Decode(&sd.f)
 	if err != nil {
 		return err
 	}
 	*s, err = extractSamples(&sd.f, sd.Opts)
 	return err
 }

 // ExtractSamples builds a slice of samples from the provided metric
 // families. If an error occurrs during sample extraction, it continues to
 // extract from the remaining metric families. The returned error is the last
 // error that has occurred.
 func ExtractSamples(o *DecodeOptions, fams ...*dto.MetricFamily) (model.Vector, error) {
 	var (
 		all     model.Vector
 		lastErr error
 	)
 	for _, f := range fams {
 		some, err := extractSamples(f, o)
 		if err != nil {
 			lastErr = err
 			continue
 		}
 		all = append(all, some...)
 	}
 	return all, lastErr
 }

 func extractSamples(f *dto.MetricFamily, o *DecodeOptions) (model.Vector, error) {
 	switch f.GetType() {
 	case dto.MetricType_COUNTER:
 		return extractCounter(o, f), nil
 	case dto.MetricType_GAUGE:
 		return extractGauge(o, f), nil
 	case dto.MetricType_SUMMARY:
 		return extractSummary(o, f), nil
 	case dto.MetricType_UNTYPED:
 		return extractUntyped(o, f), nil
 	case dto.MetricType_HISTOGRAM:
 		return extractHistogram(o, f), nil
 	}
 	return nil, fmt.Errorf("expfmt.extractSamples: unknown metric family type %v", f.GetType())
 }

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

 	for _, m := range f.Metric {
 		if m.Counter == 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.Counter.GetValue()),
 		}

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

 		samples = append(samples, smpl)
 	}

 	return samples
 }

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

 	for _, m := range f.Metric {
 		if m.Gauge == 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.Gauge.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(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 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
 }

 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
 }
	// Copyright 2015 The Prometheus Authors
	// 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 expfmt

	import (
	"fmt"
	"io"
	"math"
	"mime"
	"net/http"

	dto "github.com/prometheus/client_model/go"

	"github.com/matttproud/golang_protobuf_extensions/pbutil"
	"github.com/prometheus/common/model"
	)

	// Decoder types decode an input stream into metric families.
	type Decoder interface {
	Decode(*dto.MetricFamily) error
	}

	// DecodeOptions contains options used by the Decoder and in sample extraction.
	type DecodeOptions struct {
	// Timestamp is added to each value from the stream that has no explicit timestamp set.
	Timestamp model.Time
	}

	// ResponseFormat extracts the correct format from a HTTP response header.
	// If no matching format can be found FormatUnknown is returned.
	func ResponseFormat(h http.Header) Format {
	ct := h.Get(hdrContentType)

	mediatype, params, err := mime.ParseMediaType(ct)
	if err != nil {
	return FmtUnknown
	}

	const textType = "text/plain"

	switch mediatype {
	case ProtoType:
	if p, ok := params["proto"]; ok && p != ProtoProtocol {
	return FmtUnknown
	}
	if e, ok := params["encoding"]; ok && e != "delimited" {
	return FmtUnknown
	}
	return FmtProtoDelim

	case textType:
	if v, ok := params["version"]; ok && v != TextVersion {
	return FmtUnknown
	}
	return FmtText
	}

	return FmtUnknown
	}

	// NewDecoder returns a new decoder based on the given input format.
	// If the input format does not imply otherwise, a text format decoder is returned.
	func NewDecoder(r io.Reader, format Format) Decoder {
	switch format {
	case FmtProtoDelim:
	return &protoDecoder{r: r}
	}
	return &textDecoder{r: r}
	}

	// protoDecoder implements the Decoder interface for protocol buffers.
	type protoDecoder struct {
	r io.Reader
	}

	// 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
	}

	// textDecoder implements the Decoder interface for the text protocol.
	type textDecoder struct {
	r io.Reader
	p TextParser
	fams []*dto.MetricFamily
	}

	// Decode implements the Decoder interface.
	func (d textDecoder) Decode(v dto.MetricFamily) error {
	// TODO(fabxc): Wrap this as a line reader to make streaming safer.
	if len(d.fams) == 0 {
	// No cached metric families, read everything and parse metrics.
	fams, err := d.p.TextToMetricFamilies(d.r)
	if err != nil {
	return err
	}
	if len(fams) == 0 {
	return io.EOF
	}
	d.fams = make([]*dto.MetricFamily, 0, len(fams))
	for _, f := range fams {
	d.fams = append(d.fams, f)
	}
	}

	v = d.fams[0]
	d.fams = d.fams[1:]

	return nil
	}

	// SampleDecoder wraps a Decoder to extract samples from the metric families
	// decoded by the wrapped Decoder.
	type SampleDecoder struct {
	Dec Decoder
	Opts *DecodeOptions

	f dto.MetricFamily
	}

	// Decode calls the Decode method of the wrapped Decoder and then extracts the
	// samples from the decoded MetricFamily into the provided model.Vector.
	func (sd SampleDecoder) Decode(s model.Vector) error {
	err := sd.Dec.Decode(&sd.f)
	if err != nil {
	return err
	}
	*s, err = extractSamples(&sd.f, sd.Opts)
	return err
	}

	// ExtractSamples builds a slice of samples from the provided metric
	// families. If an error occurrs during sample extraction, it continues to
	// extract from the remaining metric families. The returned error is the last
	// error that has occurred.
	func ExtractSamples(o DecodeOptions, fams ...dto.MetricFamily) (model.Vector, error) {
	var (
	all model.Vector
	lastErr error
	)
	for _, f := range fams {
	some, err := extractSamples(f, o)
	if err != nil {
	lastErr = err
	continue
	}
	all = append(all, some...)
	}
	return all, lastErr
	}

	func extractSamples(f dto.MetricFamily, o DecodeOptions) (model.Vector, error) {
	switch f.GetType() {
	case dto.MetricType_COUNTER:
	return extractCounter(o, f), nil
	case dto.MetricType_GAUGE:
	return extractGauge(o, f), nil
	case dto.MetricType_SUMMARY:
	return extractSummary(o, f), nil
	case dto.MetricType_UNTYPED:
	return extractUntyped(o, f), nil
	case dto.MetricType_HISTOGRAM:
	return extractHistogram(o, f), nil
	}
	return nil, fmt.Errorf("expfmt.extractSamples: unknown metric family type %v", f.GetType())
	}

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

	for _, m := range f.Metric {
	if m.Counter == 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.Counter.GetValue()),
	}

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

	samples = append(samples, smpl)
	}

	return samples
	}

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

	for _, m := range f.Metric {
	if m.Gauge == 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.Gauge.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(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 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
	}

	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
	}