2013-06-26 15:25:10 +04:00
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// Copyright 2013 Prometheus Team
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package extraction
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import (
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"fmt"
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"io"
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dto "github.com/prometheus/client_model/go"
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"github.com/matttproud/golang_protobuf_extensions/ext"
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"github.com/prometheus/client_golang/model"
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)
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type metricFamilyProcessor struct{}
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// MetricFamilyProcessor decodes varint encoded record length-delimited streams
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// of io.prometheus.client.MetricFamily.
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//
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// See http://godoc.org/github.com/matttproud/golang_protobuf_extensions/ext for
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// more details.
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var MetricFamilyProcessor = &metricFamilyProcessor{}
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func (m *metricFamilyProcessor) ProcessSingle(i io.Reader, out Ingester, o *ProcessOptions) error {
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family := &dto.MetricFamily{}
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for {
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family.Reset()
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if _, err := ext.ReadDelimited(i, family); err != nil {
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if err == io.EOF {
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return nil
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}
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return err
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}
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if err := extractMetricFamily(out, o, family); err != nil {
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return err
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}
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}
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}
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func extractMetricFamily(out Ingester, o *ProcessOptions, family *dto.MetricFamily) error {
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switch family.GetType() {
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case dto.MetricType_COUNTER:
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if err := extractCounter(out, o, family); err != nil {
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return err
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}
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case dto.MetricType_GAUGE:
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if err := extractGauge(out, o, family); err != nil {
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return err
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}
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case dto.MetricType_SUMMARY:
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if err := extractSummary(out, o, family); err != nil {
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return err
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}
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case dto.MetricType_UNTYPED:
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if err := extractUntyped(out, o, family); err != nil {
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return err
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}
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case dto.MetricType_HISTOGRAM:
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if err := extractHistogram(out, o, family); err != nil {
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return err
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}
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}
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return nil
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}
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func extractCounter(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
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samples := make(model.Samples, 0, len(f.Metric))
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for _, m := range f.Metric {
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if m.Counter == nil {
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continue
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}
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sample := new(model.Sample)
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samples = append(samples, sample)
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if m.TimestampMs != nil {
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sample.Timestamp = model.TimestampFromUnixNano(*m.TimestampMs * 1000000)
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} else {
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sample.Timestamp = o.Timestamp
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}
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sample.Metric = model.Metric{}
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metric := sample.Metric
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName())
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sample.Value = model.SampleValue(m.Counter.GetValue())
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}
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return out.Ingest(samples)
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}
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func extractGauge(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
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samples := make(model.Samples, 0, len(f.Metric))
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for _, m := range f.Metric {
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if m.Gauge == nil {
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continue
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}
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sample := new(model.Sample)
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samples = append(samples, sample)
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if m.TimestampMs != nil {
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sample.Timestamp = model.TimestampFromUnixNano(*m.TimestampMs * 1000000)
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} else {
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sample.Timestamp = o.Timestamp
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}
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sample.Metric = model.Metric{}
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metric := sample.Metric
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName())
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sample.Value = model.SampleValue(m.Gauge.GetValue())
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}
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return out.Ingest(samples)
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}
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func extractSummary(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
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samples := make(model.Samples, 0, len(f.Metric))
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for _, m := range f.Metric {
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if m.Summary == nil {
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continue
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}
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timestamp := o.Timestamp
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if m.TimestampMs != nil {
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timestamp = model.TimestampFromUnixNano(*m.TimestampMs * 1000000)
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}
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for _, q := range m.Summary.Quantile {
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sample := new(model.Sample)
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samples = append(samples, sample)
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sample.Timestamp = timestamp
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sample.Metric = model.Metric{}
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metric := sample.Metric
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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// BUG(matt): Update other names to "quantile".
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metric[model.LabelName("quantile")] = model.LabelValue(fmt.Sprint(q.GetQuantile()))
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName())
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sample.Value = model.SampleValue(q.GetValue())
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}
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if m.Summary.SampleSum != nil {
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sum := new(model.Sample)
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sum.Timestamp = timestamp
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metric := model.Metric{}
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_sum")
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sum.Metric = metric
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sum.Value = model.SampleValue(m.Summary.GetSampleSum())
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samples = append(samples, sum)
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}
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if m.Summary.SampleCount != nil {
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count := new(model.Sample)
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count.Timestamp = timestamp
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metric := model.Metric{}
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_count")
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count.Metric = metric
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count.Value = model.SampleValue(m.Summary.GetSampleCount())
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samples = append(samples, count)
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}
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}
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return out.Ingest(samples)
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}
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func extractUntyped(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
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samples := make(model.Samples, 0, len(f.Metric))
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for _, m := range f.Metric {
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if m.Untyped == nil {
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continue
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}
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sample := new(model.Sample)
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samples = append(samples, sample)
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if m.TimestampMs != nil {
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sample.Timestamp = model.TimestampFromUnixNano(*m.TimestampMs * 1000000)
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} else {
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sample.Timestamp = o.Timestamp
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}
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sample.Metric = model.Metric{}
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metric := sample.Metric
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName())
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sample.Value = model.SampleValue(m.Untyped.GetValue())
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}
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2014-12-31 15:53:17 +03:00
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return out.Ingest(samples)
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}
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func extractHistogram(out Ingester, o *ProcessOptions, f *dto.MetricFamily) error {
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samples := make(model.Samples, 0, len(f.Metric))
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for _, m := range f.Metric {
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if m.Histogram == nil {
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continue
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}
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timestamp := o.Timestamp
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if m.TimestampMs != nil {
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timestamp = model.TimestampFromUnixNano(*m.TimestampMs * 1000000)
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}
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for _, q := range m.Histogram.Bucket {
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sample := new(model.Sample)
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samples = append(samples, sample)
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sample.Timestamp = timestamp
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sample.Metric = model.Metric{}
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metric := sample.Metric
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.LabelName("le")] = model.LabelValue(fmt.Sprint(q.GetUpperBound()))
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_bucket")
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sample.Value = model.SampleValue(q.GetCumulativeCount())
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}
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// TODO: If +Inf bucket is missing, add it.
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if m.Histogram.SampleSum != nil {
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sum := new(model.Sample)
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sum.Timestamp = timestamp
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metric := model.Metric{}
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_sum")
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sum.Metric = metric
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sum.Value = model.SampleValue(m.Histogram.GetSampleSum())
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samples = append(samples, sum)
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}
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if m.Histogram.SampleCount != nil {
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count := new(model.Sample)
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count.Timestamp = timestamp
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metric := model.Metric{}
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for _, p := range m.Label {
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metric[model.LabelName(p.GetName())] = model.LabelValue(p.GetValue())
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}
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metric[model.MetricNameLabel] = model.LabelValue(f.GetName() + "_count")
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count.Metric = metric
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count.Value = model.SampleValue(m.Histogram.GetSampleCount())
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samples = append(samples, count)
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}
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}
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return out.Ingest(samples)
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}
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