106 lines
3.2 KiB
Go
106 lines
3.2 KiB
Go
package prometheusremotewrite
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import (
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"fmt"
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"math"
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"time"
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"github.com/prometheus/common/model"
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"github.com/prometheus/prometheus/prompb"
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"github.com/influxdata/telegraf"
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"github.com/influxdata/telegraf/metric"
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)
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func (p *Parser) extractMetricsV1(ts *prompb.TimeSeries) ([]telegraf.Metric, error) {
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t := time.Now()
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// Convert each prometheus metrics to the corresponding telegraf metrics.
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// You will get one telegraf metric with one field per prometheus metric
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// for "simple" types like Gauge and Counter.
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// However, since in prometheus remote write, a "complex" type is already
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// broken down into multiple "simple" types metrics, you will still get
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// multiple telegraf metrics per Histogram or Summary.
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// One bucket of a histogram could also be split into multiple remote
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// write requests, so we won't try to aggregate them here.
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// However, for Native Histogram, you will get one telegraf metric with
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// multiple fields.
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metrics := make([]telegraf.Metric, 0, len(ts.Samples)+len(ts.Histograms))
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tags := make(map[string]string, len(p.DefaultTags)+len(ts.Labels))
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for key, value := range p.DefaultTags {
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tags[key] = value
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}
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for _, l := range ts.Labels {
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tags[l.Name] = l.Value
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}
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metricName := tags[model.MetricNameLabel]
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if metricName == "" {
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return nil, fmt.Errorf("metric name %q not found in tag-set or empty", model.MetricNameLabel)
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}
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delete(tags, model.MetricNameLabel)
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for _, s := range ts.Samples {
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if math.IsNaN(s.Value) {
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continue
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}
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// In prometheus remote write,
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// You won't know if it's a counter or gauge or a sub-counter in a histogram
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fields := map[string]interface{}{"value": s.Value}
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if s.Timestamp > 0 {
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t = time.Unix(0, s.Timestamp*1000000)
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}
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m := metric.New(metricName, tags, fields, t)
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metrics = append(metrics, m)
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}
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for _, hp := range ts.Histograms {
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h := hp.ToFloatHistogram()
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if hp.Timestamp > 0 {
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t = time.Unix(0, hp.Timestamp*1000000)
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}
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fields := map[string]any{
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"counter_reset_hint": uint64(h.CounterResetHint),
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"schema": int64(h.Schema),
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"zero_threshold": h.ZeroThreshold,
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"zero_count": h.ZeroCount,
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"count": h.Count,
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"sum": h.Sum,
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}
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count := 0.0
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iter := h.AllBucketIterator()
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for iter.Next() {
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bucket := iter.At()
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count = count + bucket.Count
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fields[fmt.Sprintf("%g", bucket.Upper)] = count
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}
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// expand positiveSpans and negativeSpans into fields
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for i, span := range h.PositiveSpans {
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fields[fmt.Sprintf("positive_span_%d_offset", i)] = int64(span.Offset)
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fields[fmt.Sprintf("positive_span_%d_length", i)] = uint64(span.Length)
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}
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for i, span := range h.NegativeSpans {
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fields[fmt.Sprintf("negative_span_%d_offset", i)] = int64(span.Offset)
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fields[fmt.Sprintf("negative_span_%d_length", i)] = uint64(span.Length)
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}
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// expand positiveBuckets and negativeBuckets into fields
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for i, bucket := range h.PositiveBuckets {
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fields[fmt.Sprintf("positive_bucket_%d", i)] = bucket
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}
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for i, bucket := range h.NegativeBuckets {
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fields[fmt.Sprintf("negative_bucket_%d", i)] = bucket
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}
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m := metric.New(metricName, tags, fields, t, telegraf.Histogram)
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metrics = append(metrics, m)
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}
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return metrics, nil
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}
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