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// 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 occurs 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
}
