emitskevich-blp commented on code in PR #15889:
URL: https://github.com/apache/kafka/pull/15889#discussion_r1602153395
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clients/src/main/java/org/apache/kafka/common/metrics/stats/Rate.java:
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@@ -63,33 +63,38 @@ public void record(MetricConfig config, double value, long
timeMs) {
@Override
public double measure(MetricConfig config, long now) {
+ long windowSizeMs = windowSize(config, now);
double value = stat.measure(config, now);
- return value / convert(windowSize(config, now), unit);
+ return value / convert(windowSizeMs, unit);
}
public long windowSize(MetricConfig config, long now) {
// purge old samples before we compute the window size
- stat.purgeObsoleteSamples(config, now);
+ long purgedUpToMs = stat.purgeObsoleteSamples(config, now);
/*
* Here we check the total amount of time elapsed since the oldest
non-obsolete window.
* This give the total windowSize of the batch which is the time used
for Rate computation.
- * However, there is an issue if we do not have sufficient data for
e.g. if only 1 second has elapsed in a 30 second
+ * However, there is an issue if we do not have sufficient data for
e.g. if only 1 second has elapsed in a 30-second
* window, the measured rate will be very high.
- * Hence we assume that the elapsed time is always N-1 complete
windows plus whatever fraction of the final window is complete.
+ * Hence, we assume that the elapsed time is always N-1 complete
windows plus whatever fraction of the final window is complete.
*
* Note that we could simply count the amount of time elapsed in the
current window and add n-1 windows to get the total time,
* but this approach does not account for sleeps. SampledStat only
creates samples whenever record is called,
* if no record is called for a period of time that time is not
accounted for in windowSize and produces incorrect results.
*/
- long totalElapsedTimeMs = now - stat.oldest(now).lastWindowMs;
+ long totalElapsedTimeMs = now - stat.oldest(now).startTimeMs;
// Check how many full windows of data we have currently retained
int numFullWindows = (int) (totalElapsedTimeMs /
config.timeWindowMs());
int minFullWindows = config.samples() - 1;
// If the available windows are less than the minimum required, add
the difference to the totalElapsedTime
- if (numFullWindows < minFullWindows)
+ if (numFullWindows < minFullWindows) {
totalElapsedTimeMs += (minFullWindows - numFullWindows) *
config.timeWindowMs();
+ }
+
+ // if some part of considered interval was just purged with its data,
exclude it
+ totalElapsedTimeMs = Math.min(totalElapsedTimeMs, now - purgedUpToMs);
Review Comment:
> if measure() is called a second time after a very short window, no samples
will be purged and we won't be compensating for the purgedUpToMs. Then, we will
fall back to use the larger window, which will result in a much lower measured
value.
Thank you, I missed it
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