Adding upstream version 1.34.4.

Signed-off-by: Daniel Baumann <daniel@debian.org>

plugins/parsers/prometheusremotewrite/metric_v1.go

@@ -0,0 +1,106 @@
+package prometheusremotewrite
+
+import (
+	"fmt"
+	"math"
+	"time"
+
+	"github.com/prometheus/common/model"
+	"github.com/prometheus/prometheus/prompb"
+
+	"github.com/influxdata/telegraf"
+	"github.com/influxdata/telegraf/metric"
+)
+
+func (p *Parser) extractMetricsV1(ts *prompb.TimeSeries) ([]telegraf.Metric, error) {
+	t := time.Now()
+
+	// Convert each prometheus metrics to the corresponding telegraf metrics.
+	// You will get one telegraf metric with one field per prometheus metric
+	// for "simple" types like Gauge and Counter.
+	// However, since in prometheus remote write, a "complex" type is already
+	// broken down into multiple "simple" types metrics, you will still get
+	// multiple telegraf metrics per Histogram or Summary.
+	// One bucket of a histogram could also be split into multiple remote
+	// write requests, so we won't try to aggregate them here.
+	// However, for Native Histogram, you will get one telegraf metric with
+	// multiple fields.
+	metrics := make([]telegraf.Metric, 0, len(ts.Samples)+len(ts.Histograms))
+
+	tags := make(map[string]string, len(p.DefaultTags)+len(ts.Labels))
+	for key, value := range p.DefaultTags {
+		tags[key] = value
+	}
+	for _, l := range ts.Labels {
+		tags[l.Name] = l.Value
+	}
+
+	metricName := tags[model.MetricNameLabel]
+	if metricName == "" {
+		return nil, fmt.Errorf("metric name %q not found in tag-set or empty", model.MetricNameLabel)
+	}
+	delete(tags, model.MetricNameLabel)
+
+	for _, s := range ts.Samples {
+		if math.IsNaN(s.Value) {
+			continue
+		}
+		// In prometheus remote write,
+		// You won't know if it's a counter or gauge or a sub-counter in a histogram
+		fields := map[string]interface{}{"value": s.Value}
+		if s.Timestamp > 0 {
+			t = time.Unix(0, s.Timestamp*1000000)
+		}
+		m := metric.New(metricName, tags, fields, t)
+		metrics = append(metrics, m)
+	}
+
+	for _, hp := range ts.Histograms {
+		h := hp.ToFloatHistogram()
+
+		if hp.Timestamp > 0 {
+			t = time.Unix(0, hp.Timestamp*1000000)
+		}
+
+		fields := map[string]any{
+			"counter_reset_hint": uint64(h.CounterResetHint),
+			"schema":             int64(h.Schema),
+			"zero_threshold":     h.ZeroThreshold,
+			"zero_count":         h.ZeroCount,
+			"count":              h.Count,
+			"sum":                h.Sum,
+		}
+
+		count := 0.0
+		iter := h.AllBucketIterator()
+		for iter.Next() {
+			bucket := iter.At()
+			count = count + bucket.Count
+			fields[fmt.Sprintf("%g", bucket.Upper)] = count
+		}
+
+		// expand positiveSpans and negativeSpans into fields
+		for i, span := range h.PositiveSpans {
+			fields[fmt.Sprintf("positive_span_%d_offset", i)] = int64(span.Offset)
+			fields[fmt.Sprintf("positive_span_%d_length", i)] = uint64(span.Length)
+		}
+
+		for i, span := range h.NegativeSpans {
+			fields[fmt.Sprintf("negative_span_%d_offset", i)] = int64(span.Offset)
+			fields[fmt.Sprintf("negative_span_%d_length", i)] = uint64(span.Length)
+		}
+		// expand positiveBuckets and negativeBuckets into fields
+		for i, bucket := range h.PositiveBuckets {
+			fields[fmt.Sprintf("positive_bucket_%d", i)] = bucket
+		}
+
+		for i, bucket := range h.NegativeBuckets {
+			fields[fmt.Sprintf("negative_bucket_%d", i)] = bucket
+		}
+
+		m := metric.New(metricName, tags, fields, t, telegraf.Histogram)
+		metrics = append(metrics, m)
+	}
+
+	return metrics, nil
+}