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Merge pull request #9102 from prometheus/beorn7/protobuf

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Be more specific when identifying a sparse histogram
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Björn Rabenstein 2021-07-20 12:05:48 +02:00 committed by GitHub
parent 4fefd7520e c35f138a9a
commit 368940247f
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1 changed files with 17 additions and 1 deletions
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18
pkg/textparse/protobufparse.go
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@ -309,7 +309,7 @@ func (p *ProtobufParser) Next() (Entry, error) {
p.state = EntryType
case EntryType:
if p.mf.GetType() == dto.MetricType_HISTOGRAM &&
p.mf.GetMetric()[0].GetHistogram().GetSbZeroThreshold() != 0 {
isSparseHistogram(p.mf.GetMetric()[0].GetHistogram()) {
p.state = EntryHistogram
} else {
p.state = EntrySeries
@ -459,3 +459,19 @@ func formatOpenMetricsFloat(f float64) string {
}
return s + ".0"
}
// isSparseHistogram returns false iff the provided histograms has no
// SparseBuckets and a zero threshold of 0 and a zero count of 0. In principle,
// this could still be meant to be a sparse histgram (with a zero threshold of 0
// and no observations yet), but for now, we'll treat this case as a conventional
// histogram.
//
// TODO(beorn7): In the final format, there should be an unambiguous way of
// deciding if a histogram should be ingested as a conventional one or a sparse
// one.
func isSparseHistogram(h *dto.Histogram) bool {
return len(h.GetSbNegative().GetDelta()) > 0 ||
len(h.GetSbPositive().GetDelta()) > 0 ||
h.GetSbZeroCount() > 0 ||
h.GetSbZeroThreshold() > 0
}