func()

in collector/receiver/prometheusreceiver/internal/metricfamily.go [169:216]

• 32 lines of code
• 8 McCabe index (conditional complexity)

func (mg *metricGroup) toSummaryPoint(dest pmetric.SummaryDataPointSlice) {
	// expecting count to be provided, however, in the following two cases, they can be missed.
	// 1. data is corrupted
	// 2. ignored by startValue evaluation
	if !mg.hasCount {
		return
	}

	mg.sortPoints()

	point := dest.AppendEmpty()
	pointIsStale := value.IsStaleNaN(mg.sum) || value.IsStaleNaN(mg.count)
	if pointIsStale {
		point.SetFlags(pmetric.DefaultDataPointFlags.WithNoRecordedValue(true))
	} else {
		if mg.hasSum {
			point.SetSum(mg.sum)
		}
		point.SetCount(uint64(mg.count))
	}

	quantileValues := point.QuantileValues()
	for _, p := range mg.complexValue {
		quantile := quantileValues.AppendEmpty()
		// Quantiles still need to be sent to know to set them as stale,
		// but a staleness NaN converted to uint64 would be an extremely large number.
		// By not setting the quantile value, it will default to 0.
		if !pointIsStale {
			quantile.SetValue(p.value)
		}
		quantile.SetQuantile(p.boundary)
	}

	// Based on the summary description from https://prometheus.io/docs/concepts/metric_types/#summary
	// the quantiles are calculated over a sliding time window, however, the count is the total count of
	// observations and the corresponding sum is a sum of all observed values, thus the sum and count used
	// at the global level of the metricspb.SummaryValue
	// The timestamp MUST be in retrieved from milliseconds and converted to nanoseconds.
	tsNanos := timestampFromMs(mg.ts)
	point.SetTimestamp(tsNanos)
	if mg.created != 0 {
		point.SetStartTimestamp(timestampFromFloat64(mg.created))
	} else {
		// metrics_adjuster adjusts the startTimestamp to the initial scrape timestamp
		point.SetStartTimestamp(tsNanos)
	}
	populateAttributes(pmetric.MetricTypeSummary, mg.ls, point.Attributes())
}