Exemplo n.º 1
0
// div3Sigma sets given metric score and average via 3-sigma.
//	states that nearly all values (99.7%) lie within the 3 standard deviations
//	of the mean in a normal distribution.
func (d *Detector) div3Sigma(m *models.Metric, vals []float64) {
	if len(vals) == 0 {
		m.Score = 0
		m.Average = m.Value
		return
	}
	// Values average and standard deviation.
	avg := mathutil.Average(vals)
	std := mathutil.StdDev(vals, avg)
	// Set metric average
	m.Average = avg
	// Set metric score
	if len(vals) <= int(d.cfg.Detector.LeastCount) { // Number of values not enough
		m.Score = 0
		return
	}
	last := m.Value
	if std == 0 { // Eadger
		switch {
		case last == avg:
			m.Score = 0
		case last > avg:
			m.Score = 1
		case last < avg:
			m.Score = -1
		}
		return
	}
	m.Score = (last - avg) / (3 * std) // 3-sigma
}
Exemplo n.º 2
0
// Aggregate QueryCost.
func aggregationQueryCost() {
	h.info.lock.Lock()
	defer h.info.lock.Unlock()
	h.queryCostsLock.Lock()
	defer h.queryCostsLock.Unlock()
	h.info.QueryCost = mathutil.Average(h.queryCosts)
	h.queryCosts = h.queryCosts[:0]
}
Exemplo n.º 3
0
// Aggregate FilterCost.
func aggregationFilterCost() {
	h.info.lock.Lock()
	defer h.info.lock.Unlock()
	h.filterCostsLock.Lock()
	defer h.filterCostsLock.Unlock()
	h.info.FilterCost = mathutil.Average(h.filterCosts)
	h.filterCosts = h.filterCosts[:0]
}
Exemplo n.º 4
0
// Aggregate DetectionCost.
func aggregateDetectionCost() {
	h.info.lock.Lock()
	defer h.info.lock.Unlock()
	h.detectionCostsLock.Lock()
	defer h.detectionCostsLock.Unlock()
	h.info.DetectionCost = mathutil.Average(h.detectionCosts)
	h.detectionCosts = h.detectionCosts[:0]
}