client_golang/extraction/metricfamilyprocessor.go

296 lines
7.8 KiB
Go

// Copyright 2013 Prometheus Team
// 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 extraction
import (
"fmt"
"io"
dto "github.com/prometheus/client_model/go"
"github.com/matttproud/golang_protobuf_extensions/ext"
"github.com/prometheus/client_golang/model"
)
type metricFamilyProcessor struct{}
// MetricFamilyProcessor decodes varint encoded record length-delimited streams
// of io.prometheus.client.MetricFamily.
//
// See http://godoc.org/github.com/matttproud/golang_protobuf_extensions/ext for
// more details.
var MetricFamilyProcessor = &metricFamilyProcessor{}
func (m *metricFamilyProcessor) ProcessSingle(i io.Reader, out Ingester, o *ProcessOptions) error {
family := &dto.MetricFamily{}
for {
family.Reset()
if _, err := ext.ReadDelimited(i, family); err != nil {
if err == io.EOF {
return nil
}
return err
}
if err := extractMetricFamily(out, o, family); err != nil {
return err
}
}
}
func extractMetricFamily(out Ingester, o *ProcessOptions, family *dto.MetricFamily) error {
switch family.GetType() {
case dto.MetricType_COUNTER:
if err := extractCounter(out, o, family); err != nil {
return err
}
case dto.MetricType_GAUGE:
if err := extractGauge(out, o, family); err != nil {
return err
}
case dto.MetricType_SUMMARY:
if err := extractSummary(out, o, family); err != nil {
return err
}
case dto.MetricType_UNTYPED:
if err := extractUntyped(out, o, family); err != nil {
return err
}
case dto.MetricType_HISTOGRAM:
if err := extractHistogram(out, o, family); err != nil {
return err
}
}
return nil
}
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.TimestampFromUnixNano(*m.TimestampMs * 1000000)
} 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(samples)
}
func extractGauge(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
samples := make(model.Samples, 0, len(f.Metric))
for _, m := range f.Metric {
if m.Gauge == nil {
continue
}
sample := new(model.Sample)
samples = append(samples, sample)
if m.TimestampMs != nil {
sample.Timestamp = model.TimestampFromUnixNano(*m.TimestampMs * 1000000)
} 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.Gauge.GetValue())
}
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 := 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(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 := new(model.Sample)
samples = append(samples, sample)
if m.TimestampMs != nil {
sample.Timestamp = model.TimestampFromUnixNano(*m.TimestampMs * 1000000)
} 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.Untyped.GetValue())
}
return out.Ingest(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)
}
for _, q := range m.Histogram.Bucket {
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())
}
metric[model.LabelName("le")] = model.LabelValue(fmt.Sprint(q.GetUpperBound()))
metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_bucket")
sample.Value = model.SampleValue(q.GetCumulativeCount())
}
// TODO: If +Inf bucket is missing, add it.
if m.Histogram.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.Histogram.GetSampleSum())
samples = append(samples, sum)
}
if m.Histogram.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.Histogram.GetSampleCount())
samples = append(samples, count)
}
}
return out.Ingest(samples)
}