// Blueflood will use the finest-grained resolution which doesn't exceed the slot limit. // Thus, if you request too many points, it will automatically reduce the resolution. func (b *Blueflood) ChooseResolution(requested api.Timerange, smallestResolution time.Duration) time.Duration { // In some cases, coarser-resolution data may have a shorter TTL. // To accomodate these cases, it must be verified that the requested timerange will // actually be present for the chosen resolution. // TODO: figure out how to make this work with moving averages and timeshifts requiredAge := b.timeSource().Sub(requested.StartTime()) for _, resolution := range Resolutions { survivesFor := b.config.oldestViableDataForResolution(resolution) if survivesFor < requiredAge { // The data probably won't be around for the earliest part of the timerange, // so don't use this resolution continue } if resolution.duration < requested.Resolution() { // Skip this timerange, it is finer than the one requested. continue } // Check that the timerange is large enough if resolution.duration >= smallestResolution { return resolution.duration } } // Leave it alone, since a better one can't be found return requested.Resolution() }
func addMetricPoint(metricPoint metricPoint, field func(metricPoint) float64, timerange api.Timerange, buckets [][]float64) bool { value := field(metricPoint) // The index to assign within the array is computed using the timestamp. // It floors to the nearest index. index := (metricPoint.Timestamp - timerange.Start()) / timerange.Resolution() if index < 0 || index >= int64(timerange.Slots()) { return false } buckets[index] = append(buckets[index], value) return true }
func (f FakeTimeseriesStorageAPI) ChooseResolution(requested api.Timerange, smallestResolution time.Duration) time.Duration { return requested.Resolution() }