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Use total.recursion.time.avg to reconstruct the histogram sum. 

Wouter Wijngaards mentioned in the NLnet bug tracker that this metric
provides exactly the value that we need.
This commit is contained in:
Ed Schouten 2017-12-04 09:30:59 +01:00
parent 01935206bc
commit 4f36729f55
1 changed files with 21 additions and 9 deletions
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30
unbound_exporter.go
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@ -254,10 +254,10 @@ func newUnboundMetric(name string, description string, valueType prometheus.Valu
func CollectFromReader(file io.Reader, ch chan<- prometheus.Metric) error { func CollectFromReader(file io.Reader, ch chan<- prometheus.Metric) error {
scanner := bufio.NewScanner(file) scanner := bufio.NewScanner(file)
scanner.Split(bufio.ScanLines) scanner.Split(bufio.ScanLines)
histogramPattern := regexp.MustCompile("^histogram\\.(\\d+\\.\\d+)\\.to\\.(\\d+\\.\\d+)$") histogramPattern := regexp.MustCompile("^histogram\\.\\d+\\.\\d+\\.to\\.(\\d+\\.\\d+)$")
histogramCount := uint64(0) histogramCount := uint64(0)
histogramSum := float64(0) histogramAvg := float64(0)
histogramBuckets := make(map[float64]uint64) histogramBuckets := make(map[float64]uint64)
for scanner.Scan() { for scanner.Scan() {
@ -286,8 +286,10 @@ func CollectFromReader(file io.Reader, ch chan<- prometheus.Metric) error {
} }
if matches := histogramPattern.FindStringSubmatch(fields[0]); matches != nil { if matches := histogramPattern.FindStringSubmatch(fields[0]); matches != nil {
begin, _ := strconv.ParseFloat(matches[1], 64) end, err := strconv.ParseFloat(matches[1], 64)
end, _ := strconv.ParseFloat(matches[2], 64) if err != nil {
return err
}
value, err := strconv.ParseUint(fields[1], 10, 64) value, err := strconv.ParseUint(fields[1], 10, 64)
if err != nil { if err != nil {
@ -295,13 +297,19 @@ func CollectFromReader(file io.Reader, ch chan<- prometheus.Metric) error {
} }
histogramBuckets[end] = value histogramBuckets[end] = value
histogramCount += value histogramCount += value
// There are no real data points to calculate the sum in the unbound stats } else if fields[0] == "total.recursion.time.avg" {
// Therefore the mean latency times the amount of samples is calculated and summed value, err := strconv.ParseFloat(fields[1], 64)
histogramSum += (end + begin) / 2 * float64(value) if err != nil {
return err
}
histogramAvg = value
} }
} }
// Convert the metrics to a cumulative prometheus histogram // Convert the metrics to a cumulative Prometheus histogram.
// Reconstruct the sum of all samples from the average value
// provided by Unbound. Hopefully this does not break
// monotonicity.
keys := []float64{} keys := []float64{}
for k := range histogramBuckets { for k := range histogramBuckets {
keys = append(keys, k) keys = append(keys, k)
@ -312,7 +320,11 @@ func CollectFromReader(file io.Reader, ch chan<- prometheus.Metric) error {
histogramBuckets[i] += prev histogramBuckets[i] += prev
prev = histogramBuckets[i] prev = histogramBuckets[i]
} }
ch <- prometheus.MustNewConstHistogram(unboundHistogram, histogramCount, histogramSum, histogramBuckets) ch <- prometheus.MustNewConstHistogram(
unboundHistogram,
histogramCount,
histogramAvg*float64(histogramCount),
histogramBuckets)
return scanner.Err() return scanner.Err()
} }