From bcc785fc7891adeea235d669cfc70d90871fad49 Mon Sep 17 00:00:00 2001
From: Etienne Perot <eperot@google.com>
Date: Mon, 1 Jul 2024 16:04:25 -0700
Subject: [PATCH] Metrics visualization: Show extrapolated rate for
 short-duration profiles.

All rate metrics currently show per-second rates, which cannot be computed
before we have at least 1 second's worth of profile data. However, it's
reasonable to want to run very short workloads (less than 1 second) and still
want to see how those rates evolved over this duration. So this change
computes an extrapolated per-second rate for the first second of execution.

PiperOrigin-RevId: 648513094
---
 test/metricsviz/metricsviz.go | 24 +++++++++++++++++++++++-
 1 file changed, 23 insertions(+), 1 deletion(-)

diff --git a/test/metricsviz/metricsviz.go b/test/metricsviz/metricsviz.go
index ba9b872c2..2c049e798 100644
--- a/test/metricsviz/metricsviz.go
+++ b/test/metricsviz/metricsviz.go
@@ -221,9 +221,13 @@ func (c *chart) getXAxis() ([]string, error) {
 
 // series returns a single line series of the chart.
 func (c *chart) series(ts *TimeSeries, isCumulative bool) ([]opts.LineData, error) {
-	const windowDuration = time.Second
+	const (
+		windowDuration  = time.Second
+		minTimeToReport = 10 * time.Millisecond
+	)
 	seriesData := make([]opts.LineData, len(ts.Data))
 	if isCumulative {
+		timeSeriesIsLongEnough := false
 		lastValidXIndex := 0
 		for i, p := range ts.Data {
 			baselineWhen := p.When.Add(-windowDuration)
@@ -263,12 +267,30 @@ func (c *chart) series(ts *TimeSeries, isCumulative bool) ([]opts.LineData, erro
 				baselineWhenFraction := float64(baselineWhen.Sub(whenBefore)) / float64(whenDelta)
 				baseline := baselineBefore + uint64(float64(baselineDelta)*baselineWhenFraction)
 				seriesData[i] = opts.LineData{Value: p.Value - baseline, YAxisIndex: 0, Symbol: "none"}
+				timeSeriesIsLongEnough = true
+			case p.When.Sub(ts.Data[0].When) >= minTimeToReport:
+				// We don't yet have enough points to get a full `windowDuration`'s
+				// worth of data, but we do have enough data to report something if
+				// we assume that the rate can be extrapolated from the first point
+				// until now.
+				baselineBefore := ts.Data[0].Value
+				baselineAfter := p.Value
+				baselineDelta := baselineAfter - baselineBefore
+				whenBefore := ts.Data[0].When
+				whenAfter := p.When
+				whenDelta := whenAfter.Sub(whenBefore)
+				interpolationMultiplier := float64(windowDuration.Nanoseconds()) / float64(whenDelta.Nanoseconds())
+				seriesData[i] = opts.LineData{Value: uint64(float64(baselineDelta) * interpolationMultiplier), YAxisIndex: 0, Symbol: "none"}
+				timeSeriesIsLongEnough = true
 			default:
 				// Happens naturally for points too early in the timeseries,
 				// set the point to nil.
 				seriesData[i] = opts.LineData{Value: nil, YAxisIndex: 0, Symbol: "none"}
 			}
 		}
+		if !timeSeriesIsLongEnough {
+			return nil, fmt.Errorf("metric %v is cumulative but timeseries data for it is smaller than minimum chartable duration (%v), please run the workload for longer for cumulative timeseries to become meaningful", ts.Metric.Name, minTimeToReport)
+		}
 	} else {
 		// Non-cumulative time series are more straightforward.
 		for i, p := range ts.Data {