mirror of https://github.com/grafana/grafana
feat(instrumentation): added meter, histogram and new timer, timer now send p25, p75, p90, p99 percentiles in 1000 sample exp decaying sample
parent
86f0007768
commit
eee49a4995
@ -0,0 +1,122 @@ |
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// includes code from
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// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
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// Copyright 2012 Richard Crowley. All rights reserved.
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package metrics |
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import ( |
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"math" |
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"sync" |
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"sync/atomic" |
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) |
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// EWMAs continuously calculate an exponentially-weighted moving average
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// based on an outside source of clock ticks.
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type EWMA interface { |
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Rate() float64 |
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Snapshot() EWMA |
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Tick() |
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Update(int64) |
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} |
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// NewEWMA constructs a new EWMA with the given alpha.
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func NewEWMA(alpha float64) EWMA { |
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if UseNilMetrics { |
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return NilEWMA{} |
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} |
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return &StandardEWMA{alpha: alpha} |
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} |
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// NewEWMA1 constructs a new EWMA for a one-minute moving average.
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func NewEWMA1() EWMA { |
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return NewEWMA(1 - math.Exp(-5.0/60.0/1)) |
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} |
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// NewEWMA5 constructs a new EWMA for a five-minute moving average.
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func NewEWMA5() EWMA { |
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return NewEWMA(1 - math.Exp(-5.0/60.0/5)) |
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} |
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// NewEWMA15 constructs a new EWMA for a fifteen-minute moving average.
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func NewEWMA15() EWMA { |
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return NewEWMA(1 - math.Exp(-5.0/60.0/15)) |
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} |
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// EWMASnapshot is a read-only copy of another EWMA.
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type EWMASnapshot float64 |
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// Rate returns the rate of events per second at the time the snapshot was
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// taken.
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func (a EWMASnapshot) Rate() float64 { return float64(a) } |
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// Snapshot returns the snapshot.
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func (a EWMASnapshot) Snapshot() EWMA { return a } |
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// Tick panics.
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func (EWMASnapshot) Tick() { |
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panic("Tick called on an EWMASnapshot") |
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} |
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// Update panics.
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func (EWMASnapshot) Update(int64) { |
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panic("Update called on an EWMASnapshot") |
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} |
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// NilEWMA is a no-op EWMA.
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type NilEWMA struct{} |
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// Rate is a no-op.
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func (NilEWMA) Rate() float64 { return 0.0 } |
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// Snapshot is a no-op.
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func (NilEWMA) Snapshot() EWMA { return NilEWMA{} } |
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// Tick is a no-op.
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func (NilEWMA) Tick() {} |
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// Update is a no-op.
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func (NilEWMA) Update(n int64) {} |
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// StandardEWMA is the standard implementation of an EWMA and tracks the number
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// of uncounted events and processes them on each tick. It uses the
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// sync/atomic package to manage uncounted events.
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type StandardEWMA struct { |
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uncounted int64 // /!\ this should be the first member to ensure 64-bit alignment
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alpha float64 |
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rate float64 |
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init bool |
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mutex sync.Mutex |
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} |
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// Rate returns the moving average rate of events per second.
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func (a *StandardEWMA) Rate() float64 { |
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a.mutex.Lock() |
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defer a.mutex.Unlock() |
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return a.rate * float64(1e9) |
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} |
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// Snapshot returns a read-only copy of the EWMA.
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func (a *StandardEWMA) Snapshot() EWMA { |
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return EWMASnapshot(a.Rate()) |
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} |
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// Tick ticks the clock to update the moving average. It assumes it is called
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// every five seconds.
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func (a *StandardEWMA) Tick() { |
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count := atomic.LoadInt64(&a.uncounted) |
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atomic.AddInt64(&a.uncounted, -count) |
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instantRate := float64(count) / float64(5e9) |
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a.mutex.Lock() |
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defer a.mutex.Unlock() |
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if a.init { |
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a.rate += a.alpha * (instantRate - a.rate) |
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} else { |
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a.init = true |
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a.rate = instantRate |
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} |
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} |
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// Update adds n uncounted events.
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func (a *StandardEWMA) Update(n int64) { |
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atomic.AddInt64(&a.uncounted, n) |
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} |
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package metrics |
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// type comboCounterRef struct {
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// *MetricMeta
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// usageCounter Counter
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// metricCounter Counter
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// }
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//
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// func RegComboCounter(name string, tagStrings ...string) Counter {
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// meta := NewMetricMeta(name, tagStrings)
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// cr := &comboCounterRef{
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// MetricMeta: meta,
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// usageCounter: NewCounter(meta),
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// metricCounter: NewCounter(meta),
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// }
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//
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// UsageStats.Register(cr.usageCounter)
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// MetricStats.Register(cr.metricCounter)
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//
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// return cr
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// }
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//
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// func (c comboCounterRef) Clear() {
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// c.usageCounter.Clear()
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// c.metricCounter.Clear()
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// }
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//
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// func (c comboCounterRef) Count() int64 {
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// panic("Count called on a combocounter ref")
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// }
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//
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// // Dec panics.
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// func (c comboCounterRef) Dec(i int64) {
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// c.usageCounter.Dec(i)
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// c.metricCounter.Dec(i)
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// }
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//
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// // Inc panics.
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// func (c comboCounterRef) Inc(i int64) {
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// c.usageCounter.Inc(i)
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// c.metricCounter.Inc(i)
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// }
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//
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// func (c comboCounterRef) Snapshot() Metric {
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// return c.metricCounter.Snapshot()
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// }
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@ -0,0 +1,189 @@ |
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// includes code from
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// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
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// Copyright 2012 Richard Crowley. All rights reserved.
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package metrics |
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// Histograms calculate distribution statistics from a series of int64 values.
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type Histogram interface { |
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Metric |
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Clear() |
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Count() int64 |
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Max() int64 |
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Mean() float64 |
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Min() int64 |
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Percentile(float64) float64 |
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Percentiles([]float64) []float64 |
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StdDev() float64 |
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Sum() int64 |
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Update(int64) |
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Variance() float64 |
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} |
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func NewHistogram(meta *MetricMeta, s Sample) Histogram { |
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return &StandardHistogram{ |
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MetricMeta: meta, |
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sample: s, |
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} |
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} |
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// HistogramSnapshot is a read-only copy of another Histogram.
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type HistogramSnapshot struct { |
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*MetricMeta |
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sample *SampleSnapshot |
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} |
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// Clear panics.
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func (*HistogramSnapshot) Clear() { |
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panic("Clear called on a HistogramSnapshot") |
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} |
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// Count returns the number of samples recorded at the time the snapshot was
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// taken.
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func (h *HistogramSnapshot) Count() int64 { return h.sample.Count() } |
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// Max returns the maximum value in the sample at the time the snapshot was
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// taken.
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func (h *HistogramSnapshot) Max() int64 { return h.sample.Max() } |
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// Mean returns the mean of the values in the sample at the time the snapshot
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// was taken.
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func (h *HistogramSnapshot) Mean() float64 { return h.sample.Mean() } |
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// Min returns the minimum value in the sample at the time the snapshot was
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// taken.
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func (h *HistogramSnapshot) Min() int64 { return h.sample.Min() } |
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// Percentile returns an arbitrary percentile of values in the sample at the
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// time the snapshot was taken.
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func (h *HistogramSnapshot) Percentile(p float64) float64 { |
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return h.sample.Percentile(p) |
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} |
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// Percentiles returns a slice of arbitrary percentiles of values in the sample
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// at the time the snapshot was taken.
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func (h *HistogramSnapshot) Percentiles(ps []float64) []float64 { |
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return h.sample.Percentiles(ps) |
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} |
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// Sample returns the Sample underlying the histogram.
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func (h *HistogramSnapshot) Sample() Sample { return h.sample } |
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// Snapshot returns the snapshot.
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func (h *HistogramSnapshot) Snapshot() Metric { return h } |
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// StdDev returns the standard deviation of the values in the sample at the
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// time the snapshot was taken.
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func (h *HistogramSnapshot) StdDev() float64 { return h.sample.StdDev() } |
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// Sum returns the sum in the sample at the time the snapshot was taken.
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func (h *HistogramSnapshot) Sum() int64 { return h.sample.Sum() } |
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// Update panics.
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func (*HistogramSnapshot) Update(int64) { |
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panic("Update called on a HistogramSnapshot") |
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} |
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// Variance returns the variance of inputs at the time the snapshot was taken.
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func (h *HistogramSnapshot) Variance() float64 { return h.sample.Variance() } |
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// NilHistogram is a no-op Histogram.
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type NilHistogram struct { |
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*MetricMeta |
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} |
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// Clear is a no-op.
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func (NilHistogram) Clear() {} |
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// Count is a no-op.
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func (NilHistogram) Count() int64 { return 0 } |
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// Max is a no-op.
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func (NilHistogram) Max() int64 { return 0 } |
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// Mean is a no-op.
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func (NilHistogram) Mean() float64 { return 0.0 } |
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// Min is a no-op.
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func (NilHistogram) Min() int64 { return 0 } |
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// Percentile is a no-op.
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func (NilHistogram) Percentile(p float64) float64 { return 0.0 } |
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// Percentiles is a no-op.
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func (NilHistogram) Percentiles(ps []float64) []float64 { |
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return make([]float64, len(ps)) |
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} |
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// Sample is a no-op.
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func (NilHistogram) Sample() Sample { return NilSample{} } |
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// Snapshot is a no-op.
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func (n NilHistogram) Snapshot() Metric { return n } |
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// StdDev is a no-op.
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func (NilHistogram) StdDev() float64 { return 0.0 } |
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// Sum is a no-op.
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func (NilHistogram) Sum() int64 { return 0 } |
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// Update is a no-op.
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func (NilHistogram) Update(v int64) {} |
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// Variance is a no-op.
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func (NilHistogram) Variance() float64 { return 0.0 } |
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// StandardHistogram is the standard implementation of a Histogram and uses a
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// Sample to bound its memory use.
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type StandardHistogram struct { |
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*MetricMeta |
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sample Sample |
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} |
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// Clear clears the histogram and its sample.
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func (h *StandardHistogram) Clear() { h.sample.Clear() } |
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// Count returns the number of samples recorded since the histogram was last
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// cleared.
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func (h *StandardHistogram) Count() int64 { return h.sample.Count() } |
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// Max returns the maximum value in the sample.
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func (h *StandardHistogram) Max() int64 { return h.sample.Max() } |
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// Mean returns the mean of the values in the sample.
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func (h *StandardHistogram) Mean() float64 { return h.sample.Mean() } |
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// Min returns the minimum value in the sample.
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func (h *StandardHistogram) Min() int64 { return h.sample.Min() } |
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// Percentile returns an arbitrary percentile of the values in the sample.
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func (h *StandardHistogram) Percentile(p float64) float64 { |
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return h.sample.Percentile(p) |
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} |
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// Percentiles returns a slice of arbitrary percentiles of the values in the
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// sample.
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func (h *StandardHistogram) Percentiles(ps []float64) []float64 { |
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return h.sample.Percentiles(ps) |
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} |
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// Sample returns the Sample underlying the histogram.
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func (h *StandardHistogram) Sample() Sample { return h.sample } |
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// Snapshot returns a read-only copy of the histogram.
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func (h *StandardHistogram) Snapshot() Metric { |
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return &HistogramSnapshot{sample: h.sample.Snapshot().(*SampleSnapshot)} |
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} |
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// StdDev returns the standard deviation of the values in the sample.
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func (h *StandardHistogram) StdDev() float64 { return h.sample.StdDev() } |
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// Sum returns the sum in the sample.
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func (h *StandardHistogram) Sum() int64 { return h.sample.Sum() } |
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// Update samples a new value.
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func (h *StandardHistogram) Update(v int64) { h.sample.Update(v) } |
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// Variance returns the variance of the values in the sample.
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func (h *StandardHistogram) Variance() float64 { return h.sample.Variance() } |
@ -0,0 +1,90 @@ |
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// includes code from
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// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
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// Copyright 2012 Richard Crowley. All rights reserved.
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package metrics |
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import "testing" |
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func BenchmarkHistogram(b *testing.B) { |
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h := NewHistogram(nil, NewUniformSample(100)) |
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b.ResetTimer() |
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for i := 0; i < b.N; i++ { |
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h.Update(int64(i)) |
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} |
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} |
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func TestHistogram10000(t *testing.T) { |
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h := NewHistogram(nil, NewUniformSample(100000)) |
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for i := 1; i <= 10000; i++ { |
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h.Update(int64(i)) |
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} |
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testHistogram10000(t, h) |
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} |
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func TestHistogramEmpty(t *testing.T) { |
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h := NewHistogram(nil, NewUniformSample(100)) |
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if count := h.Count(); 0 != count { |
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t.Errorf("h.Count(): 0 != %v\n", count) |
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} |
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if min := h.Min(); 0 != min { |
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t.Errorf("h.Min(): 0 != %v\n", min) |
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} |
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if max := h.Max(); 0 != max { |
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t.Errorf("h.Max(): 0 != %v\n", max) |
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} |
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if mean := h.Mean(); 0.0 != mean { |
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t.Errorf("h.Mean(): 0.0 != %v\n", mean) |
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} |
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if stdDev := h.StdDev(); 0.0 != stdDev { |
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t.Errorf("h.StdDev(): 0.0 != %v\n", stdDev) |
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} |
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ps := h.Percentiles([]float64{0.5, 0.75, 0.99}) |
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if 0.0 != ps[0] { |
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t.Errorf("median: 0.0 != %v\n", ps[0]) |
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} |
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if 0.0 != ps[1] { |
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t.Errorf("75th percentile: 0.0 != %v\n", ps[1]) |
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} |
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if 0.0 != ps[2] { |
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t.Errorf("99th percentile: 0.0 != %v\n", ps[2]) |
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} |
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} |
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func TestHistogramSnapshot(t *testing.T) { |
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h := NewHistogram(nil, NewUniformSample(100000)) |
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for i := 1; i <= 10000; i++ { |
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h.Update(int64(i)) |
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} |
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snapshot := h.Snapshot().(Histogram) |
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h.Update(0) |
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testHistogram10000(t, snapshot) |
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} |
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func testHistogram10000(t *testing.T, h Histogram) { |
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if count := h.Count(); 10000 != count { |
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t.Errorf("h.Count(): 10000 != %v\n", count) |
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} |
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if min := h.Min(); 1 != min { |
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t.Errorf("h.Min(): 1 != %v\n", min) |
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} |
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if max := h.Max(); 10000 != max { |
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t.Errorf("h.Max(): 10000 != %v\n", max) |
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} |
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if mean := h.Mean(); 5000.5 != mean { |
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t.Errorf("h.Mean(): 5000.5 != %v\n", mean) |
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} |
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if stdDev := h.StdDev(); 2886.751331514372 != stdDev { |
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t.Errorf("h.StdDev(): 2886.751331514372 != %v\n", stdDev) |
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} |
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ps := h.Percentiles([]float64{0.5, 0.75, 0.99}) |
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if 5000.5 != ps[0] { |
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t.Errorf("median: 5000.5 != %v\n", ps[0]) |
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} |
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if 7500.75 != ps[1] { |
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t.Errorf("75th percentile: 7500.75 != %v\n", ps[1]) |
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} |
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if 9900.99 != ps[2] { |
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t.Errorf("99th percentile: 9900.99 != %v\n", ps[2]) |
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} |
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} |
@ -0,0 +1,221 @@ |
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// includes code from
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// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
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// Copyright 2012 Richard Crowley. All rights reserved.
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package metrics |
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import ( |
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"sync" |
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"time" |
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) |
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// Meters count events to produce exponentially-weighted moving average rates
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// at one-, five-, and fifteen-minutes and a mean rate.
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type Meter interface { |
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Metric |
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Count() int64 |
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Mark(int64) |
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Rate1() float64 |
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Rate5() float64 |
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Rate15() float64 |
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RateMean() float64 |
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} |
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// NewMeter constructs a new StandardMeter and launches a goroutine.
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func NewMeter(meta *MetricMeta) Meter { |
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if UseNilMetrics { |
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return NilMeter{} |
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} |
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m := newStandardMeter(meta) |
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arbiter.Lock() |
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defer arbiter.Unlock() |
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arbiter.meters = append(arbiter.meters, m) |
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if !arbiter.started { |
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arbiter.started = true |
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go arbiter.tick() |
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} |
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return m |
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} |
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type MeterSnapshot struct { |
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*MetricMeta |
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count int64 |
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rate1, rate5, rate15, rateMean float64 |
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} |
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// Count returns the count of events at the time the snapshot was taken.
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func (m *MeterSnapshot) Count() int64 { return m.count } |
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// Mark panics.
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func (*MeterSnapshot) Mark(n int64) { |
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panic("Mark called on a MeterSnapshot") |
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} |
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// Rate1 returns the one-minute moving average rate of events per second at the
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// time the snapshot was taken.
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func (m *MeterSnapshot) Rate1() float64 { return m.rate1 } |
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// Rate5 returns the five-minute moving average rate of events per second at
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// the time the snapshot was taken.
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func (m *MeterSnapshot) Rate5() float64 { return m.rate5 } |
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// Rate15 returns the fifteen-minute moving average rate of events per second
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// at the time the snapshot was taken.
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func (m *MeterSnapshot) Rate15() float64 { return m.rate15 } |
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// RateMean returns the meter's mean rate of events per second at the time the
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// snapshot was taken.
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func (m *MeterSnapshot) RateMean() float64 { return m.rateMean } |
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// Snapshot returns the snapshot.
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func (m *MeterSnapshot) Snapshot() Metric { return m } |
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// NilMeter is a no-op Meter.
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type NilMeter struct{ *MetricMeta } |
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// Count is a no-op.
|
||||
func (NilMeter) Count() int64 { return 0 } |
||||
|
||||
// Mark is a no-op.
|
||||
func (NilMeter) Mark(n int64) {} |
||||
|
||||
// Rate1 is a no-op.
|
||||
func (NilMeter) Rate1() float64 { return 0.0 } |
||||
|
||||
// Rate5 is a no-op.
|
||||
func (NilMeter) Rate5() float64 { return 0.0 } |
||||
|
||||
// Rate15is a no-op.
|
||||
func (NilMeter) Rate15() float64 { return 0.0 } |
||||
|
||||
// RateMean is a no-op.
|
||||
func (NilMeter) RateMean() float64 { return 0.0 } |
||||
|
||||
// Snapshot is a no-op.
|
||||
func (NilMeter) Snapshot() Metric { return NilMeter{} } |
||||
|
||||
// StandardMeter is the standard implementation of a Meter.
|
||||
type StandardMeter struct { |
||||
*MetricMeta |
||||
lock sync.RWMutex |
||||
snapshot *MeterSnapshot |
||||
a1, a5, a15 EWMA |
||||
startTime time.Time |
||||
} |
||||
|
||||
func newStandardMeter(meta *MetricMeta) *StandardMeter { |
||||
return &StandardMeter{ |
||||
MetricMeta: meta, |
||||
snapshot: &MeterSnapshot{MetricMeta: meta}, |
||||
a1: NewEWMA1(), |
||||
a5: NewEWMA5(), |
||||
a15: NewEWMA15(), |
||||
startTime: time.Now(), |
||||
} |
||||
} |
||||
|
||||
// Count returns the number of events recorded.
|
||||
func (m *StandardMeter) Count() int64 { |
||||
m.lock.RLock() |
||||
count := m.snapshot.count |
||||
m.lock.RUnlock() |
||||
return count |
||||
} |
||||
|
||||
// Mark records the occurance of n events.
|
||||
func (m *StandardMeter) Mark(n int64) { |
||||
m.lock.Lock() |
||||
defer m.lock.Unlock() |
||||
m.snapshot.count += n |
||||
m.a1.Update(n) |
||||
m.a5.Update(n) |
||||
m.a15.Update(n) |
||||
m.updateSnapshot() |
||||
} |
||||
|
||||
// Rate1 returns the one-minute moving average rate of events per second.
|
||||
func (m *StandardMeter) Rate1() float64 { |
||||
m.lock.RLock() |
||||
rate1 := m.snapshot.rate1 |
||||
m.lock.RUnlock() |
||||
return rate1 |
||||
} |
||||
|
||||
// Rate5 returns the five-minute moving average rate of events per second.
|
||||
func (m *StandardMeter) Rate5() float64 { |
||||
m.lock.RLock() |
||||
rate5 := m.snapshot.rate5 |
||||
m.lock.RUnlock() |
||||
return rate5 |
||||
} |
||||
|
||||
// Rate15 returns the fifteen-minute moving average rate of events per second.
|
||||
func (m *StandardMeter) Rate15() float64 { |
||||
m.lock.RLock() |
||||
rate15 := m.snapshot.rate15 |
||||
m.lock.RUnlock() |
||||
return rate15 |
||||
} |
||||
|
||||
// RateMean returns the meter's mean rate of events per second.
|
||||
func (m *StandardMeter) RateMean() float64 { |
||||
m.lock.RLock() |
||||
rateMean := m.snapshot.rateMean |
||||
m.lock.RUnlock() |
||||
return rateMean |
||||
} |
||||
|
||||
// Snapshot returns a read-only copy of the meter.
|
||||
func (m *StandardMeter) Snapshot() Metric { |
||||
m.lock.RLock() |
||||
snapshot := *m.snapshot |
||||
m.lock.RUnlock() |
||||
return &snapshot |
||||
} |
||||
|
||||
func (m *StandardMeter) updateSnapshot() { |
||||
// should run with write lock held on m.lock
|
||||
snapshot := m.snapshot |
||||
snapshot.rate1 = m.a1.Rate() |
||||
snapshot.rate5 = m.a5.Rate() |
||||
snapshot.rate15 = m.a15.Rate() |
||||
snapshot.rateMean = float64(snapshot.count) / time.Since(m.startTime).Seconds() |
||||
} |
||||
|
||||
func (m *StandardMeter) tick() { |
||||
m.lock.Lock() |
||||
defer m.lock.Unlock() |
||||
m.a1.Tick() |
||||
m.a5.Tick() |
||||
m.a15.Tick() |
||||
m.updateSnapshot() |
||||
} |
||||
|
||||
type meterArbiter struct { |
||||
sync.RWMutex |
||||
started bool |
||||
meters []*StandardMeter |
||||
ticker *time.Ticker |
||||
} |
||||
|
||||
var arbiter = meterArbiter{ticker: time.NewTicker(5e9)} |
||||
|
||||
// Ticks meters on the scheduled interval
|
||||
func (ma *meterArbiter) tick() { |
||||
for { |
||||
select { |
||||
case <-ma.ticker.C: |
||||
ma.tickMeters() |
||||
} |
||||
} |
||||
} |
||||
|
||||
func (ma *meterArbiter) tickMeters() { |
||||
ma.RLock() |
||||
defer ma.RUnlock() |
||||
for _, meter := range ma.meters { |
||||
meter.tick() |
||||
} |
||||
} |
@ -1,101 +0,0 @@ |
||||
package metrics |
||||
|
||||
type comboCounterRef struct { |
||||
*MetricMeta |
||||
usageCounter Counter |
||||
metricCounter Counter |
||||
} |
||||
|
||||
type comboTimerRef struct { |
||||
*MetricMeta |
||||
usageTimer Timer |
||||
metricTimer Timer |
||||
} |
||||
|
||||
func RegComboCounter(name string, tagStrings ...string) Counter { |
||||
meta := NewMetricMeta(name, tagStrings) |
||||
cr := &comboCounterRef{ |
||||
MetricMeta: meta, |
||||
usageCounter: NewCounter(meta), |
||||
metricCounter: NewCounter(meta), |
||||
} |
||||
|
||||
UsageStats.Register(cr.usageCounter) |
||||
MetricStats.Register(cr.metricCounter) |
||||
|
||||
return cr |
||||
} |
||||
|
||||
func RegComboTimer(name string, tagStrings ...string) Timer { |
||||
meta := NewMetricMeta(name, tagStrings) |
||||
tr := &comboTimerRef{ |
||||
MetricMeta: meta, |
||||
usageTimer: NewTimer(meta), |
||||
metricTimer: NewTimer(meta), |
||||
} |
||||
|
||||
UsageStats.Register(tr.usageTimer) |
||||
MetricStats.Register(tr.metricTimer) |
||||
return tr |
||||
} |
||||
|
||||
func RegTimer(name string, tagStrings ...string) Timer { |
||||
tr := NewTimer(NewMetricMeta(name, tagStrings)) |
||||
MetricStats.Register(tr) |
||||
return tr |
||||
} |
||||
|
||||
func (t comboTimerRef) Clear() { |
||||
t.metricTimer.Clear() |
||||
t.usageTimer.Clear() |
||||
} |
||||
|
||||
func (t comboTimerRef) Avg() int64 { |
||||
panic("Avg called on combotimer ref") |
||||
} |
||||
|
||||
func (t comboTimerRef) Min() int64 { |
||||
panic("Avg called on combotimer ref") |
||||
} |
||||
|
||||
func (t comboTimerRef) Max() int64 { |
||||
panic("Avg called on combotimer ref") |
||||
} |
||||
|
||||
func (t comboTimerRef) Count() int64 { |
||||
panic("Avg called on combotimer ref") |
||||
} |
||||
|
||||
func (t comboTimerRef) Snapshot() Metric { |
||||
panic("Snapshot called on combotimer ref") |
||||
} |
||||
|
||||
func (t comboTimerRef) AddTiming(timing int64) { |
||||
t.metricTimer.AddTiming(timing) |
||||
t.usageTimer.AddTiming(timing) |
||||
} |
||||
|
||||
func (c comboCounterRef) Clear() { |
||||
c.usageCounter.Clear() |
||||
c.metricCounter.Clear() |
||||
} |
||||
|
||||
func (c comboCounterRef) Count() int64 { |
||||
panic("Count called on a combocounter ref") |
||||
} |
||||
|
||||
// Dec panics.
|
||||
func (c comboCounterRef) Dec(i int64) { |
||||
c.usageCounter.Dec(i) |
||||
c.metricCounter.Dec(i) |
||||
} |
||||
|
||||
// Inc panics.
|
||||
func (c comboCounterRef) Inc(i int64) { |
||||
c.usageCounter.Inc(i) |
||||
c.metricCounter.Inc(i) |
||||
} |
||||
|
||||
func (c comboCounterRef) Snapshot() Metric { |
||||
return c.metricCounter.Snapshot() |
||||
} |
@ -1,35 +1,65 @@ |
||||
package metrics |
||||
|
||||
var UsageStats = NewRegistry() |
||||
import "github.com/Unknwon/log" |
||||
|
||||
var MetricStats = NewRegistry() |
||||
var UseNilMetrics bool = true |
||||
|
||||
var ( |
||||
M_Instance_Start = RegComboCounter("instance_start") |
||||
M_Instance_Start Counter |
||||
M_Page_Status_200 Counter |
||||
M_Page_Status_500 Counter |
||||
M_Page_Status_404 Counter |
||||
M_Api_Status_500 Counter |
||||
M_Api_Status_404 Counter |
||||
M_Api_User_SignUpStarted Counter |
||||
M_Api_User_SignUpCompleted Counter |
||||
M_Api_User_SignUpInvite Counter |
||||
M_Api_Dashboard_Get Counter |
||||
M_Api_Dashboard_Post Counter |
||||
M_Api_Admin_User_Create Counter |
||||
M_Api_Login_Post Counter |
||||
M_Api_Login_OAuth Counter |
||||
M_Api_Org_Create Counter |
||||
M_Api_Dashboard_Snapshot_Create Counter |
||||
M_Api_Dashboard_Snapshot_External Counter |
||||
M_Api_Dashboard_Snapshot_Get Counter |
||||
M_Models_Dashboard_Insert Counter |
||||
|
||||
// Timers
|
||||
M_DataSource_ProxyReq_Timer Timer |
||||
) |
||||
|
||||
M_Page_Status_200 = RegComboCounter("page.resp_status", "code", "200") |
||||
M_Page_Status_500 = RegComboCounter("page.resp_status", "code", "500") |
||||
M_Page_Status_404 = RegComboCounter("page.resp_status", "code", "404") |
||||
func initMetricVars(settings *MetricSettings) { |
||||
log.Info("Init metric vars") |
||||
UseNilMetrics = settings.Enabled == false |
||||
|
||||
M_Api_Status_500 = RegComboCounter("api.resp_status", "code", "500") |
||||
M_Api_Status_404 = RegComboCounter("api.resp_status", "code", "404") |
||||
M_Instance_Start = RegCounter("instance_start") |
||||
|
||||
M_Api_User_SignUpStarted = RegComboCounter("api.user.signup_started") |
||||
M_Api_User_SignUpCompleted = RegComboCounter("api.user.signup_completed") |
||||
M_Api_User_SignUpInvite = RegComboCounter("api.user.signup_invite") |
||||
M_Api_Dashboard_Get = RegComboCounter("api.dashboard.get") |
||||
M_Page_Status_200 = RegCounter("page.resp_status", "code", "200") |
||||
M_Page_Status_500 = RegCounter("page.resp_status", "code", "500") |
||||
M_Page_Status_404 = RegCounter("page.resp_status", "code", "404") |
||||
|
||||
M_Api_Dashboard_Post = RegComboCounter("api.dashboard.post") |
||||
M_Api_Admin_User_Create = RegComboCounter("api.admin.user_create") |
||||
M_Api_Login_Post = RegComboCounter("api.login.post") |
||||
M_Api_Login_OAuth = RegComboCounter("api.login.oauth") |
||||
M_Api_Org_Create = RegComboCounter("api.org.create") |
||||
M_Api_Status_500 = RegCounter("api.resp_status", "code", "500") |
||||
M_Api_Status_404 = RegCounter("api.resp_status", "code", "404") |
||||
|
||||
M_Api_Dashboard_Snapshot_Create = RegComboCounter("api.dashboard_snapshot.create") |
||||
M_Api_Dashboard_Snapshot_External = RegComboCounter("api.dashboard_snapshot.external") |
||||
M_Api_Dashboard_Snapshot_Get = RegComboCounter("api.dashboard_snapshot.get") |
||||
M_Api_User_SignUpStarted = RegCounter("api.user.signup_started") |
||||
M_Api_User_SignUpCompleted = RegCounter("api.user.signup_completed") |
||||
M_Api_User_SignUpInvite = RegCounter("api.user.signup_invite") |
||||
M_Api_Dashboard_Get = RegCounter("api.dashboard.get") |
||||
|
||||
M_Models_Dashboard_Insert = RegComboCounter("models.dashboard.insert") |
||||
M_Api_Dashboard_Post = RegCounter("api.dashboard.post") |
||||
M_Api_Admin_User_Create = RegCounter("api.admin.user_create") |
||||
M_Api_Login_Post = RegCounter("api.login.post") |
||||
M_Api_Login_OAuth = RegCounter("api.login.oauth") |
||||
M_Api_Org_Create = RegCounter("api.org.create") |
||||
|
||||
M_Api_Dashboard_Snapshot_Create = RegCounter("api.dashboard_snapshot.create") |
||||
M_Api_Dashboard_Snapshot_External = RegCounter("api.dashboard_snapshot.external") |
||||
M_Api_Dashboard_Snapshot_Get = RegCounter("api.dashboard_snapshot.get") |
||||
|
||||
M_Models_Dashboard_Insert = RegCounter("models.dashboard.insert") |
||||
|
||||
// Timers
|
||||
M_DataSource_ProxyReq_Timer = RegComboTimer("api.dataproxy.request.all") |
||||
) |
||||
M_DataSource_ProxyReq_Timer = RegTimer("api.dataproxy.request.all") |
||||
} |
||||
|
@ -0,0 +1,607 @@ |
||||
// includes code from
|
||||
// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
|
||||
// Copyright 2012 Richard Crowley. All rights reserved.
|
||||
|
||||
package metrics |
||||
|
||||
import ( |
||||
"math" |
||||
"math/rand" |
||||
"sort" |
||||
"sync" |
||||
"time" |
||||
) |
||||
|
||||
const rescaleThreshold = time.Hour |
||||
|
||||
// Samples maintain a statistically-significant selection of values from
|
||||
// a stream.
|
||||
type Sample interface { |
||||
Clear() |
||||
Count() int64 |
||||
Max() int64 |
||||
Mean() float64 |
||||
Min() int64 |
||||
Percentile(float64) float64 |
||||
Percentiles([]float64) []float64 |
||||
Size() int |
||||
Snapshot() Sample |
||||
StdDev() float64 |
||||
Sum() int64 |
||||
Update(int64) |
||||
Values() []int64 |
||||
Variance() float64 |
||||
} |
||||
|
||||
// ExpDecaySample is an exponentially-decaying sample using a forward-decaying
|
||||
// priority reservoir. See Cormode et al's "Forward Decay: A Practical Time
|
||||
// Decay Model for Streaming Systems".
|
||||
//
|
||||
// <http://www.research.att.com/people/Cormode_Graham/library/publications/CormodeShkapenyukSrivastavaXu09.pdf>
|
||||
type ExpDecaySample struct { |
||||
alpha float64 |
||||
count int64 |
||||
mutex sync.Mutex |
||||
reservoirSize int |
||||
t0, t1 time.Time |
||||
values *expDecaySampleHeap |
||||
} |
||||
|
||||
// NewExpDecaySample constructs a new exponentially-decaying sample with the
|
||||
// given reservoir size and alpha.
|
||||
func NewExpDecaySample(reservoirSize int, alpha float64) Sample { |
||||
s := &ExpDecaySample{ |
||||
alpha: alpha, |
||||
reservoirSize: reservoirSize, |
||||
t0: time.Now(), |
||||
values: newExpDecaySampleHeap(reservoirSize), |
||||
} |
||||
s.t1 = s.t0.Add(rescaleThreshold) |
||||
return s |
||||
} |
||||
|
||||
// Clear clears all samples.
|
||||
func (s *ExpDecaySample) Clear() { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
s.count = 0 |
||||
s.t0 = time.Now() |
||||
s.t1 = s.t0.Add(rescaleThreshold) |
||||
s.values.Clear() |
||||
} |
||||
|
||||
// Count returns the number of samples recorded, which may exceed the
|
||||
// reservoir size.
|
||||
func (s *ExpDecaySample) Count() int64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return s.count |
||||
} |
||||
|
||||
// Max returns the maximum value in the sample, which may not be the maximum
|
||||
// value ever to be part of the sample.
|
||||
func (s *ExpDecaySample) Max() int64 { |
||||
return SampleMax(s.Values()) |
||||
} |
||||
|
||||
// Mean returns the mean of the values in the sample.
|
||||
func (s *ExpDecaySample) Mean() float64 { |
||||
return SampleMean(s.Values()) |
||||
} |
||||
|
||||
// Min returns the minimum value in the sample, which may not be the minimum
|
||||
// value ever to be part of the sample.
|
||||
func (s *ExpDecaySample) Min() int64 { |
||||
return SampleMin(s.Values()) |
||||
} |
||||
|
||||
// Percentile returns an arbitrary percentile of values in the sample.
|
||||
func (s *ExpDecaySample) Percentile(p float64) float64 { |
||||
return SamplePercentile(s.Values(), p) |
||||
} |
||||
|
||||
// Percentiles returns a slice of arbitrary percentiles of values in the
|
||||
// sample.
|
||||
func (s *ExpDecaySample) Percentiles(ps []float64) []float64 { |
||||
return SamplePercentiles(s.Values(), ps) |
||||
} |
||||
|
||||
// Size returns the size of the sample, which is at most the reservoir size.
|
||||
func (s *ExpDecaySample) Size() int { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return s.values.Size() |
||||
} |
||||
|
||||
// Snapshot returns a read-only copy of the sample.
|
||||
func (s *ExpDecaySample) Snapshot() Sample { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
vals := s.values.Values() |
||||
values := make([]int64, len(vals)) |
||||
for i, v := range vals { |
||||
values[i] = v.v |
||||
} |
||||
return &SampleSnapshot{ |
||||
count: s.count, |
||||
values: values, |
||||
} |
||||
} |
||||
|
||||
// StdDev returns the standard deviation of the values in the sample.
|
||||
func (s *ExpDecaySample) StdDev() float64 { |
||||
return SampleStdDev(s.Values()) |
||||
} |
||||
|
||||
// Sum returns the sum of the values in the sample.
|
||||
func (s *ExpDecaySample) Sum() int64 { |
||||
return SampleSum(s.Values()) |
||||
} |
||||
|
||||
// Update samples a new value.
|
||||
func (s *ExpDecaySample) Update(v int64) { |
||||
s.update(time.Now(), v) |
||||
} |
||||
|
||||
// Values returns a copy of the values in the sample.
|
||||
func (s *ExpDecaySample) Values() []int64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
vals := s.values.Values() |
||||
values := make([]int64, len(vals)) |
||||
for i, v := range vals { |
||||
values[i] = v.v |
||||
} |
||||
return values |
||||
} |
||||
|
||||
// Variance returns the variance of the values in the sample.
|
||||
func (s *ExpDecaySample) Variance() float64 { |
||||
return SampleVariance(s.Values()) |
||||
} |
||||
|
||||
// update samples a new value at a particular timestamp. This is a method all
|
||||
// its own to facilitate testing.
|
||||
func (s *ExpDecaySample) update(t time.Time, v int64) { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
s.count++ |
||||
if s.values.Size() == s.reservoirSize { |
||||
s.values.Pop() |
||||
} |
||||
s.values.Push(expDecaySample{ |
||||
k: math.Exp(t.Sub(s.t0).Seconds()*s.alpha) / rand.Float64(), |
||||
v: v, |
||||
}) |
||||
if t.After(s.t1) { |
||||
values := s.values.Values() |
||||
t0 := s.t0 |
||||
s.values.Clear() |
||||
s.t0 = t |
||||
s.t1 = s.t0.Add(rescaleThreshold) |
||||
for _, v := range values { |
||||
v.k = v.k * math.Exp(-s.alpha*s.t0.Sub(t0).Seconds()) |
||||
s.values.Push(v) |
||||
} |
||||
} |
||||
} |
||||
|
||||
// NilSample is a no-op Sample.
|
||||
type NilSample struct{} |
||||
|
||||
// Clear is a no-op.
|
||||
func (NilSample) Clear() {} |
||||
|
||||
// Count is a no-op.
|
||||
func (NilSample) Count() int64 { return 0 } |
||||
|
||||
// Max is a no-op.
|
||||
func (NilSample) Max() int64 { return 0 } |
||||
|
||||
// Mean is a no-op.
|
||||
func (NilSample) Mean() float64 { return 0.0 } |
||||
|
||||
// Min is a no-op.
|
||||
func (NilSample) Min() int64 { return 0 } |
||||
|
||||
// Percentile is a no-op.
|
||||
func (NilSample) Percentile(p float64) float64 { return 0.0 } |
||||
|
||||
// Percentiles is a no-op.
|
||||
func (NilSample) Percentiles(ps []float64) []float64 { |
||||
return make([]float64, len(ps)) |
||||
} |
||||
|
||||
// Size is a no-op.
|
||||
func (NilSample) Size() int { return 0 } |
||||
|
||||
// Sample is a no-op.
|
||||
func (NilSample) Snapshot() Sample { return NilSample{} } |
||||
|
||||
// StdDev is a no-op.
|
||||
func (NilSample) StdDev() float64 { return 0.0 } |
||||
|
||||
// Sum is a no-op.
|
||||
func (NilSample) Sum() int64 { return 0 } |
||||
|
||||
// Update is a no-op.
|
||||
func (NilSample) Update(v int64) {} |
||||
|
||||
// Values is a no-op.
|
||||
func (NilSample) Values() []int64 { return []int64{} } |
||||
|
||||
// Variance is a no-op.
|
||||
func (NilSample) Variance() float64 { return 0.0 } |
||||
|
||||
// SampleMax returns the maximum value of the slice of int64.
|
||||
func SampleMax(values []int64) int64 { |
||||
if 0 == len(values) { |
||||
return 0 |
||||
} |
||||
var max int64 = math.MinInt64 |
||||
for _, v := range values { |
||||
if max < v { |
||||
max = v |
||||
} |
||||
} |
||||
return max |
||||
} |
||||
|
||||
// SampleMean returns the mean value of the slice of int64.
|
||||
func SampleMean(values []int64) float64 { |
||||
if 0 == len(values) { |
||||
return 0.0 |
||||
} |
||||
return float64(SampleSum(values)) / float64(len(values)) |
||||
} |
||||
|
||||
// SampleMin returns the minimum value of the slice of int64.
|
||||
func SampleMin(values []int64) int64 { |
||||
if 0 == len(values) { |
||||
return 0 |
||||
} |
||||
var min int64 = math.MaxInt64 |
||||
for _, v := range values { |
||||
if min > v { |
||||
min = v |
||||
} |
||||
} |
||||
return min |
||||
} |
||||
|
||||
// SamplePercentiles returns an arbitrary percentile of the slice of int64.
|
||||
func SamplePercentile(values int64Slice, p float64) float64 { |
||||
return SamplePercentiles(values, []float64{p})[0] |
||||
} |
||||
|
||||
// SamplePercentiles returns a slice of arbitrary percentiles of the slice of
|
||||
// int64.
|
||||
func SamplePercentiles(values int64Slice, ps []float64) []float64 { |
||||
scores := make([]float64, len(ps)) |
||||
size := len(values) |
||||
if size > 0 { |
||||
sort.Sort(values) |
||||
for i, p := range ps { |
||||
pos := p * float64(size+1) |
||||
if pos < 1.0 { |
||||
scores[i] = float64(values[0]) |
||||
} else if pos >= float64(size) { |
||||
scores[i] = float64(values[size-1]) |
||||
} else { |
||||
lower := float64(values[int(pos)-1]) |
||||
upper := float64(values[int(pos)]) |
||||
scores[i] = lower + (pos-math.Floor(pos))*(upper-lower) |
||||
} |
||||
} |
||||
} |
||||
return scores |
||||
} |
||||
|
||||
// SampleSnapshot is a read-only copy of another Sample.
|
||||
type SampleSnapshot struct { |
||||
count int64 |
||||
values []int64 |
||||
} |
||||
|
||||
// Clear panics.
|
||||
func (*SampleSnapshot) Clear() { |
||||
panic("Clear called on a SampleSnapshot") |
||||
} |
||||
|
||||
// Count returns the count of inputs at the time the snapshot was taken.
|
||||
func (s *SampleSnapshot) Count() int64 { return s.count } |
||||
|
||||
// Max returns the maximal value at the time the snapshot was taken.
|
||||
func (s *SampleSnapshot) Max() int64 { return SampleMax(s.values) } |
||||
|
||||
// Mean returns the mean value at the time the snapshot was taken.
|
||||
func (s *SampleSnapshot) Mean() float64 { return SampleMean(s.values) } |
||||
|
||||
// Min returns the minimal value at the time the snapshot was taken.
|
||||
func (s *SampleSnapshot) Min() int64 { return SampleMin(s.values) } |
||||
|
||||
// Percentile returns an arbitrary percentile of values at the time the
|
||||
// snapshot was taken.
|
||||
func (s *SampleSnapshot) Percentile(p float64) float64 { |
||||
return SamplePercentile(s.values, p) |
||||
} |
||||
|
||||
// Percentiles returns a slice of arbitrary percentiles of values at the time
|
||||
// the snapshot was taken.
|
||||
func (s *SampleSnapshot) Percentiles(ps []float64) []float64 { |
||||
return SamplePercentiles(s.values, ps) |
||||
} |
||||
|
||||
// Size returns the size of the sample at the time the snapshot was taken.
|
||||
func (s *SampleSnapshot) Size() int { return len(s.values) } |
||||
|
||||
// Snapshot returns the snapshot.
|
||||
func (s *SampleSnapshot) Snapshot() Sample { return s } |
||||
|
||||
// StdDev returns the standard deviation of values at the time the snapshot was
|
||||
// taken.
|
||||
func (s *SampleSnapshot) StdDev() float64 { return SampleStdDev(s.values) } |
||||
|
||||
// Sum returns the sum of values at the time the snapshot was taken.
|
||||
func (s *SampleSnapshot) Sum() int64 { return SampleSum(s.values) } |
||||
|
||||
// Update panics.
|
||||
func (*SampleSnapshot) Update(int64) { |
||||
panic("Update called on a SampleSnapshot") |
||||
} |
||||
|
||||
// Values returns a copy of the values in the sample.
|
||||
func (s *SampleSnapshot) Values() []int64 { |
||||
values := make([]int64, len(s.values)) |
||||
copy(values, s.values) |
||||
return values |
||||
} |
||||
|
||||
// Variance returns the variance of values at the time the snapshot was taken.
|
||||
func (s *SampleSnapshot) Variance() float64 { return SampleVariance(s.values) } |
||||
|
||||
// SampleStdDev returns the standard deviation of the slice of int64.
|
||||
func SampleStdDev(values []int64) float64 { |
||||
return math.Sqrt(SampleVariance(values)) |
||||
} |
||||
|
||||
// SampleSum returns the sum of the slice of int64.
|
||||
func SampleSum(values []int64) int64 { |
||||
var sum int64 |
||||
for _, v := range values { |
||||
sum += v |
||||
} |
||||
return sum |
||||
} |
||||
|
||||
// SampleVariance returns the variance of the slice of int64.
|
||||
func SampleVariance(values []int64) float64 { |
||||
if 0 == len(values) { |
||||
return 0.0 |
||||
} |
||||
m := SampleMean(values) |
||||
var sum float64 |
||||
for _, v := range values { |
||||
d := float64(v) - m |
||||
sum += d * d |
||||
} |
||||
return sum / float64(len(values)) |
||||
} |
||||
|
||||
// A uniform sample using Vitter's Algorithm R.
|
||||
//
|
||||
// <http://www.cs.umd.edu/~samir/498/vitter.pdf>
|
||||
type UniformSample struct { |
||||
count int64 |
||||
mutex sync.Mutex |
||||
reservoirSize int |
||||
values []int64 |
||||
} |
||||
|
||||
// NewUniformSample constructs a new uniform sample with the given reservoir
|
||||
// size.
|
||||
func NewUniformSample(reservoirSize int) Sample { |
||||
return &UniformSample{ |
||||
reservoirSize: reservoirSize, |
||||
values: make([]int64, 0, reservoirSize), |
||||
} |
||||
} |
||||
|
||||
// Clear clears all samples.
|
||||
func (s *UniformSample) Clear() { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
s.count = 0 |
||||
s.values = make([]int64, 0, s.reservoirSize) |
||||
} |
||||
|
||||
// Count returns the number of samples recorded, which may exceed the
|
||||
// reservoir size.
|
||||
func (s *UniformSample) Count() int64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return s.count |
||||
} |
||||
|
||||
// Max returns the maximum value in the sample, which may not be the maximum
|
||||
// value ever to be part of the sample.
|
||||
func (s *UniformSample) Max() int64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return SampleMax(s.values) |
||||
} |
||||
|
||||
// Mean returns the mean of the values in the sample.
|
||||
func (s *UniformSample) Mean() float64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return SampleMean(s.values) |
||||
} |
||||
|
||||
// Min returns the minimum value in the sample, which may not be the minimum
|
||||
// value ever to be part of the sample.
|
||||
func (s *UniformSample) Min() int64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return SampleMin(s.values) |
||||
} |
||||
|
||||
// Percentile returns an arbitrary percentile of values in the sample.
|
||||
func (s *UniformSample) Percentile(p float64) float64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return SamplePercentile(s.values, p) |
||||
} |
||||
|
||||
// Percentiles returns a slice of arbitrary percentiles of values in the
|
||||
// sample.
|
||||
func (s *UniformSample) Percentiles(ps []float64) []float64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return SamplePercentiles(s.values, ps) |
||||
} |
||||
|
||||
// Size returns the size of the sample, which is at most the reservoir size.
|
||||
func (s *UniformSample) Size() int { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return len(s.values) |
||||
} |
||||
|
||||
// Snapshot returns a read-only copy of the sample.
|
||||
func (s *UniformSample) Snapshot() Sample { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
values := make([]int64, len(s.values)) |
||||
copy(values, s.values) |
||||
return &SampleSnapshot{ |
||||
count: s.count, |
||||
values: values, |
||||
} |
||||
} |
||||
|
||||
// StdDev returns the standard deviation of the values in the sample.
|
||||
func (s *UniformSample) StdDev() float64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return SampleStdDev(s.values) |
||||
} |
||||
|
||||
// Sum returns the sum of the values in the sample.
|
||||
func (s *UniformSample) Sum() int64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return SampleSum(s.values) |
||||
} |
||||
|
||||
// Update samples a new value.
|
||||
func (s *UniformSample) Update(v int64) { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
s.count++ |
||||
if len(s.values) < s.reservoirSize { |
||||
s.values = append(s.values, v) |
||||
} else { |
||||
r := rand.Int63n(s.count) |
||||
if r < int64(len(s.values)) { |
||||
s.values[int(r)] = v |
||||
} |
||||
} |
||||
} |
||||
|
||||
// Values returns a copy of the values in the sample.
|
||||
func (s *UniformSample) Values() []int64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
values := make([]int64, len(s.values)) |
||||
copy(values, s.values) |
||||
return values |
||||
} |
||||
|
||||
// Variance returns the variance of the values in the sample.
|
||||
func (s *UniformSample) Variance() float64 { |
||||
s.mutex.Lock() |
||||
defer s.mutex.Unlock() |
||||
return SampleVariance(s.values) |
||||
} |
||||
|
||||
// expDecaySample represents an individual sample in a heap.
|
||||
type expDecaySample struct { |
||||
k float64 |
||||
v int64 |
||||
} |
||||
|
||||
func newExpDecaySampleHeap(reservoirSize int) *expDecaySampleHeap { |
||||
return &expDecaySampleHeap{make([]expDecaySample, 0, reservoirSize)} |
||||
} |
||||
|
||||
// expDecaySampleHeap is a min-heap of expDecaySamples.
|
||||
// The internal implementation is copied from the standard library's container/heap
|
||||
type expDecaySampleHeap struct { |
||||
s []expDecaySample |
||||
} |
||||
|
||||
func (h *expDecaySampleHeap) Clear() { |
||||
h.s = h.s[:0] |
||||
} |
||||
|
||||
func (h *expDecaySampleHeap) Push(s expDecaySample) { |
||||
n := len(h.s) |
||||
h.s = h.s[0 : n+1] |
||||
h.s[n] = s |
||||
h.up(n) |
||||
} |
||||
|
||||
func (h *expDecaySampleHeap) Pop() expDecaySample { |
||||
n := len(h.s) - 1 |
||||
h.s[0], h.s[n] = h.s[n], h.s[0] |
||||
h.down(0, n) |
||||
|
||||
n = len(h.s) |
||||
s := h.s[n-1] |
||||
h.s = h.s[0 : n-1] |
||||
return s |
||||
} |
||||
|
||||
func (h *expDecaySampleHeap) Size() int { |
||||
return len(h.s) |
||||
} |
||||
|
||||
func (h *expDecaySampleHeap) Values() []expDecaySample { |
||||
return h.s |
||||
} |
||||
|
||||
func (h *expDecaySampleHeap) up(j int) { |
||||
for { |
||||
i := (j - 1) / 2 // parent
|
||||
if i == j || !(h.s[j].k < h.s[i].k) { |
||||
break |
||||
} |
||||
h.s[i], h.s[j] = h.s[j], h.s[i] |
||||
j = i |
||||
} |
||||
} |
||||
|
||||
func (h *expDecaySampleHeap) down(i, n int) { |
||||
for { |
||||
j1 := 2*i + 1 |
||||
if j1 >= n || j1 < 0 { // j1 < 0 after int overflow
|
||||
break |
||||
} |
||||
j := j1 // left child
|
||||
if j2 := j1 + 1; j2 < n && !(h.s[j1].k < h.s[j2].k) { |
||||
j = j2 // = 2*i + 2 // right child
|
||||
} |
||||
if !(h.s[j].k < h.s[i].k) { |
||||
break |
||||
} |
||||
h.s[i], h.s[j] = h.s[j], h.s[i] |
||||
i = j |
||||
} |
||||
} |
||||
|
||||
type int64Slice []int64 |
||||
|
||||
func (p int64Slice) Len() int { return len(p) } |
||||
func (p int64Slice) Less(i, j int) bool { return p[i] < p[j] } |
||||
func (p int64Slice) Swap(i, j int) { p[i], p[j] = p[j], p[i] } |
@ -0,0 +1,367 @@ |
||||
// includes code from
|
||||
// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
|
||||
// Copyright 2012 Richard Crowley. All rights reserved.
|
||||
|
||||
package metrics |
||||
|
||||
import ( |
||||
"math/rand" |
||||
"runtime" |
||||
"testing" |
||||
"time" |
||||
) |
||||
|
||||
// Benchmark{Compute,Copy}{1000,1000000} demonstrate that, even for relatively
|
||||
// expensive computations like Variance, the cost of copying the Sample, as
|
||||
// approximated by a make and copy, is much greater than the cost of the
|
||||
// computation for small samples and only slightly less for large samples.
|
||||
func BenchmarkCompute1000(b *testing.B) { |
||||
s := make([]int64, 1000) |
||||
for i := 0; i < len(s); i++ { |
||||
s[i] = int64(i) |
||||
} |
||||
b.ResetTimer() |
||||
for i := 0; i < b.N; i++ { |
||||
SampleVariance(s) |
||||
} |
||||
} |
||||
func BenchmarkCompute1000000(b *testing.B) { |
||||
s := make([]int64, 1000000) |
||||
for i := 0; i < len(s); i++ { |
||||
s[i] = int64(i) |
||||
} |
||||
b.ResetTimer() |
||||
for i := 0; i < b.N; i++ { |
||||
SampleVariance(s) |
||||
} |
||||
} |
||||
func BenchmarkCopy1000(b *testing.B) { |
||||
s := make([]int64, 1000) |
||||
for i := 0; i < len(s); i++ { |
||||
s[i] = int64(i) |
||||
} |
||||
b.ResetTimer() |
||||
for i := 0; i < b.N; i++ { |
||||
sCopy := make([]int64, len(s)) |
||||
copy(sCopy, s) |
||||
} |
||||
} |
||||
func BenchmarkCopy1000000(b *testing.B) { |
||||
s := make([]int64, 1000000) |
||||
for i := 0; i < len(s); i++ { |
||||
s[i] = int64(i) |
||||
} |
||||
b.ResetTimer() |
||||
for i := 0; i < b.N; i++ { |
||||
sCopy := make([]int64, len(s)) |
||||
copy(sCopy, s) |
||||
} |
||||
} |
||||
|
||||
func BenchmarkExpDecaySample257(b *testing.B) { |
||||
benchmarkSample(b, NewExpDecaySample(257, 0.015)) |
||||
} |
||||
|
||||
func BenchmarkExpDecaySample514(b *testing.B) { |
||||
benchmarkSample(b, NewExpDecaySample(514, 0.015)) |
||||
} |
||||
|
||||
func BenchmarkExpDecaySample1028(b *testing.B) { |
||||
benchmarkSample(b, NewExpDecaySample(1028, 0.015)) |
||||
} |
||||
|
||||
func BenchmarkUniformSample257(b *testing.B) { |
||||
benchmarkSample(b, NewUniformSample(257)) |
||||
} |
||||
|
||||
func BenchmarkUniformSample514(b *testing.B) { |
||||
benchmarkSample(b, NewUniformSample(514)) |
||||
} |
||||
|
||||
func BenchmarkUniformSample1028(b *testing.B) { |
||||
benchmarkSample(b, NewUniformSample(1028)) |
||||
} |
||||
|
||||
func TestExpDecaySample10(t *testing.T) { |
||||
rand.Seed(1) |
||||
s := NewExpDecaySample(100, 0.99) |
||||
for i := 0; i < 10; i++ { |
||||
s.Update(int64(i)) |
||||
} |
||||
if size := s.Count(); 10 != size { |
||||
t.Errorf("s.Count(): 10 != %v\n", size) |
||||
} |
||||
if size := s.Size(); 10 != size { |
||||
t.Errorf("s.Size(): 10 != %v\n", size) |
||||
} |
||||
if l := len(s.Values()); 10 != l { |
||||
t.Errorf("len(s.Values()): 10 != %v\n", l) |
||||
} |
||||
for _, v := range s.Values() { |
||||
if v > 10 || v < 0 { |
||||
t.Errorf("out of range [0, 10): %v\n", v) |
||||
} |
||||
} |
||||
} |
||||
|
||||
func TestExpDecaySample100(t *testing.T) { |
||||
rand.Seed(1) |
||||
s := NewExpDecaySample(1000, 0.01) |
||||
for i := 0; i < 100; i++ { |
||||
s.Update(int64(i)) |
||||
} |
||||
if size := s.Count(); 100 != size { |
||||
t.Errorf("s.Count(): 100 != %v\n", size) |
||||
} |
||||
if size := s.Size(); 100 != size { |
||||
t.Errorf("s.Size(): 100 != %v\n", size) |
||||
} |
||||
if l := len(s.Values()); 100 != l { |
||||
t.Errorf("len(s.Values()): 100 != %v\n", l) |
||||
} |
||||
for _, v := range s.Values() { |
||||
if v > 100 || v < 0 { |
||||
t.Errorf("out of range [0, 100): %v\n", v) |
||||
} |
||||
} |
||||
} |
||||
|
||||
func TestExpDecaySample1000(t *testing.T) { |
||||
rand.Seed(1) |
||||
s := NewExpDecaySample(100, 0.99) |
||||
for i := 0; i < 1000; i++ { |
||||
s.Update(int64(i)) |
||||
} |
||||
if size := s.Count(); 1000 != size { |
||||
t.Errorf("s.Count(): 1000 != %v\n", size) |
||||
} |
||||
if size := s.Size(); 100 != size { |
||||
t.Errorf("s.Size(): 100 != %v\n", size) |
||||
} |
||||
if l := len(s.Values()); 100 != l { |
||||
t.Errorf("len(s.Values()): 100 != %v\n", l) |
||||
} |
||||
for _, v := range s.Values() { |
||||
if v > 1000 || v < 0 { |
||||
t.Errorf("out of range [0, 1000): %v\n", v) |
||||
} |
||||
} |
||||
} |
||||
|
||||
// This test makes sure that the sample's priority is not amplified by using
|
||||
// nanosecond duration since start rather than second duration since start.
|
||||
// The priority becomes +Inf quickly after starting if this is done,
|
||||
// effectively freezing the set of samples until a rescale step happens.
|
||||
func TestExpDecaySampleNanosecondRegression(t *testing.T) { |
||||
rand.Seed(1) |
||||
s := NewExpDecaySample(100, 0.99) |
||||
for i := 0; i < 100; i++ { |
||||
s.Update(10) |
||||
} |
||||
time.Sleep(1 * time.Millisecond) |
||||
for i := 0; i < 100; i++ { |
||||
s.Update(20) |
||||
} |
||||
v := s.Values() |
||||
avg := float64(0) |
||||
for i := 0; i < len(v); i++ { |
||||
avg += float64(v[i]) |
||||
} |
||||
avg /= float64(len(v)) |
||||
if avg > 16 || avg < 14 { |
||||
t.Errorf("out of range [14, 16]: %v\n", avg) |
||||
} |
||||
} |
||||
|
||||
func TestExpDecaySampleRescale(t *testing.T) { |
||||
s := NewExpDecaySample(2, 0.001).(*ExpDecaySample) |
||||
s.update(time.Now(), 1) |
||||
s.update(time.Now().Add(time.Hour+time.Microsecond), 1) |
||||
for _, v := range s.values.Values() { |
||||
if v.k == 0.0 { |
||||
t.Fatal("v.k == 0.0") |
||||
} |
||||
} |
||||
} |
||||
|
||||
func TestExpDecaySampleSnapshot(t *testing.T) { |
||||
now := time.Now() |
||||
rand.Seed(1) |
||||
s := NewExpDecaySample(100, 0.99) |
||||
for i := 1; i <= 10000; i++ { |
||||
s.(*ExpDecaySample).update(now.Add(time.Duration(i)), int64(i)) |
||||
} |
||||
snapshot := s.Snapshot() |
||||
s.Update(1) |
||||
testExpDecaySampleStatistics(t, snapshot) |
||||
} |
||||
|
||||
func TestExpDecaySampleStatistics(t *testing.T) { |
||||
now := time.Now() |
||||
rand.Seed(1) |
||||
s := NewExpDecaySample(100, 0.99) |
||||
for i := 1; i <= 10000; i++ { |
||||
s.(*ExpDecaySample).update(now.Add(time.Duration(i)), int64(i)) |
||||
} |
||||
testExpDecaySampleStatistics(t, s) |
||||
} |
||||
|
||||
func TestUniformSample(t *testing.T) { |
||||
rand.Seed(1) |
||||
s := NewUniformSample(100) |
||||
for i := 0; i < 1000; i++ { |
||||
s.Update(int64(i)) |
||||
} |
||||
if size := s.Count(); 1000 != size { |
||||
t.Errorf("s.Count(): 1000 != %v\n", size) |
||||
} |
||||
if size := s.Size(); 100 != size { |
||||
t.Errorf("s.Size(): 100 != %v\n", size) |
||||
} |
||||
if l := len(s.Values()); 100 != l { |
||||
t.Errorf("len(s.Values()): 100 != %v\n", l) |
||||
} |
||||
for _, v := range s.Values() { |
||||
if v > 1000 || v < 0 { |
||||
t.Errorf("out of range [0, 100): %v\n", v) |
||||
} |
||||
} |
||||
} |
||||
|
||||
func TestUniformSampleIncludesTail(t *testing.T) { |
||||
rand.Seed(1) |
||||
s := NewUniformSample(100) |
||||
max := 100 |
||||
for i := 0; i < max; i++ { |
||||
s.Update(int64(i)) |
||||
} |
||||
v := s.Values() |
||||
sum := 0 |
||||
exp := (max - 1) * max / 2 |
||||
for i := 0; i < len(v); i++ { |
||||
sum += int(v[i]) |
||||
} |
||||
if exp != sum { |
||||
t.Errorf("sum: %v != %v\n", exp, sum) |
||||
} |
||||
} |
||||
|
||||
func TestUniformSampleSnapshot(t *testing.T) { |
||||
s := NewUniformSample(100) |
||||
for i := 1; i <= 10000; i++ { |
||||
s.Update(int64(i)) |
||||
} |
||||
snapshot := s.Snapshot() |
||||
s.Update(1) |
||||
testUniformSampleStatistics(t, snapshot) |
||||
} |
||||
|
||||
func TestUniformSampleStatistics(t *testing.T) { |
||||
rand.Seed(1) |
||||
s := NewUniformSample(100) |
||||
for i := 1; i <= 10000; i++ { |
||||
s.Update(int64(i)) |
||||
} |
||||
testUniformSampleStatistics(t, s) |
||||
} |
||||
|
||||
func benchmarkSample(b *testing.B, s Sample) { |
||||
var memStats runtime.MemStats |
||||
runtime.ReadMemStats(&memStats) |
||||
pauseTotalNs := memStats.PauseTotalNs |
||||
b.ResetTimer() |
||||
for i := 0; i < b.N; i++ { |
||||
s.Update(1) |
||||
} |
||||
b.StopTimer() |
||||
runtime.GC() |
||||
runtime.ReadMemStats(&memStats) |
||||
b.Logf("GC cost: %d ns/op", int(memStats.PauseTotalNs-pauseTotalNs)/b.N) |
||||
} |
||||
|
||||
func testExpDecaySampleStatistics(t *testing.T, s Sample) { |
||||
if count := s.Count(); 10000 != count { |
||||
t.Errorf("s.Count(): 10000 != %v\n", count) |
||||
} |
||||
if min := s.Min(); 107 != min { |
||||
t.Errorf("s.Min(): 107 != %v\n", min) |
||||
} |
||||
if max := s.Max(); 10000 != max { |
||||
t.Errorf("s.Max(): 10000 != %v\n", max) |
||||
} |
||||
if mean := s.Mean(); 4965.98 != mean { |
||||
t.Errorf("s.Mean(): 4965.98 != %v\n", mean) |
||||
} |
||||
if stdDev := s.StdDev(); 2959.825156930727 != stdDev { |
||||
t.Errorf("s.StdDev(): 2959.825156930727 != %v\n", stdDev) |
||||
} |
||||
ps := s.Percentiles([]float64{0.5, 0.75, 0.99}) |
||||
if 4615 != ps[0] { |
||||
t.Errorf("median: 4615 != %v\n", ps[0]) |
||||
} |
||||
if 7672 != ps[1] { |
||||
t.Errorf("75th percentile: 7672 != %v\n", ps[1]) |
||||
} |
||||
if 9998.99 != ps[2] { |
||||
t.Errorf("99th percentile: 9998.99 != %v\n", ps[2]) |
||||
} |
||||
} |
||||
|
||||
func testUniformSampleStatistics(t *testing.T, s Sample) { |
||||
if count := s.Count(); 10000 != count { |
||||
t.Errorf("s.Count(): 10000 != %v\n", count) |
||||
} |
||||
if min := s.Min(); 37 != min { |
||||
t.Errorf("s.Min(): 37 != %v\n", min) |
||||
} |
||||
if max := s.Max(); 9989 != max { |
||||
t.Errorf("s.Max(): 9989 != %v\n", max) |
||||
} |
||||
if mean := s.Mean(); 4748.14 != mean { |
||||
t.Errorf("s.Mean(): 4748.14 != %v\n", mean) |
||||
} |
||||
if stdDev := s.StdDev(); 2826.684117548333 != stdDev { |
||||
t.Errorf("s.StdDev(): 2826.684117548333 != %v\n", stdDev) |
||||
} |
||||
ps := s.Percentiles([]float64{0.5, 0.75, 0.99}) |
||||
if 4599 != ps[0] { |
||||
t.Errorf("median: 4599 != %v\n", ps[0]) |
||||
} |
||||
if 7380.5 != ps[1] { |
||||
t.Errorf("75th percentile: 7380.5 != %v\n", ps[1]) |
||||
} |
||||
if 9986.429999999998 != ps[2] { |
||||
t.Errorf("99th percentile: 9986.429999999998 != %v\n", ps[2]) |
||||
} |
||||
} |
||||
|
||||
// TestUniformSampleConcurrentUpdateCount would expose data race problems with
|
||||
// concurrent Update and Count calls on Sample when test is called with -race
|
||||
// argument
|
||||
func TestUniformSampleConcurrentUpdateCount(t *testing.T) { |
||||
if testing.Short() { |
||||
t.Skip("skipping in short mode") |
||||
} |
||||
s := NewUniformSample(100) |
||||
for i := 0; i < 100; i++ { |
||||
s.Update(int64(i)) |
||||
} |
||||
quit := make(chan struct{}) |
||||
go func() { |
||||
t := time.NewTicker(10 * time.Millisecond) |
||||
for { |
||||
select { |
||||
case <-t.C: |
||||
s.Update(rand.Int63()) |
||||
case <-quit: |
||||
t.Stop() |
||||
return |
||||
} |
||||
} |
||||
}() |
||||
for i := 0; i < 1000; i++ { |
||||
s.Count() |
||||
time.Sleep(5 * time.Millisecond) |
||||
} |
||||
quit <- struct{}{} |
||||
} |
@ -0,0 +1,89 @@ |
||||
package metrics |
||||
|
||||
//import "sync/atomic"
|
||||
|
||||
type SimpleTimer interface { |
||||
Metric |
||||
|
||||
AddTiming(int64) |
||||
Mean() float64 |
||||
Min() int64 |
||||
Max() int64 |
||||
Count() int64 |
||||
} |
||||
|
||||
type StandardSimpleTimer struct { |
||||
*MetricMeta |
||||
|
||||
total int64 |
||||
count int64 |
||||
mean float64 |
||||
min int64 |
||||
max int64 |
||||
} |
||||
|
||||
func NewSimpleTimer(meta *MetricMeta) SimpleTimer { |
||||
return &StandardSimpleTimer{ |
||||
MetricMeta: meta, |
||||
mean: 0, |
||||
min: 0, |
||||
max: 0, |
||||
total: 0, |
||||
count: 0, |
||||
} |
||||
} |
||||
|
||||
func RegSimpleTimer(name string, tagStrings ...string) SimpleTimer { |
||||
tr := NewSimpleTimer(NewMetricMeta(name, tagStrings)) |
||||
MetricStats.Register(tr) |
||||
return tr |
||||
} |
||||
|
||||
func (this *StandardSimpleTimer) AddTiming(time int64) { |
||||
if this.min > time { |
||||
this.min = time |
||||
} |
||||
|
||||
if this.max < time { |
||||
this.max = time |
||||
} |
||||
|
||||
this.total += time |
||||
this.count++ |
||||
this.mean = float64(this.total) / float64(this.count) |
||||
} |
||||
|
||||
func (this *StandardSimpleTimer) Clear() { |
||||
this.mean = 0 |
||||
this.min = 0 |
||||
this.max = 0 |
||||
this.total = 0 |
||||
this.count = 0 |
||||
} |
||||
|
||||
func (this *StandardSimpleTimer) Mean() float64 { |
||||
return this.mean |
||||
} |
||||
|
||||
func (this *StandardSimpleTimer) Min() int64 { |
||||
return this.min |
||||
} |
||||
|
||||
func (this *StandardSimpleTimer) Max() int64 { |
||||
return this.max |
||||
} |
||||
|
||||
func (this *StandardSimpleTimer) Count() int64 { |
||||
return this.count |
||||
} |
||||
|
||||
func (this *StandardSimpleTimer) Snapshot() Metric { |
||||
return &StandardSimpleTimer{ |
||||
MetricMeta: this.MetricMeta, |
||||
mean: this.mean, |
||||
min: this.min, |
||||
max: this.max, |
||||
total: this.total, |
||||
count: this.count, |
||||
} |
||||
} |
@ -1,84 +1,309 @@ |
||||
// includes code from
|
||||
// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
|
||||
// Copyright 2012 Richard Crowley. All rights reserved.
|
||||
|
||||
package metrics |
||||
|
||||
//import "sync/atomic"
|
||||
import ( |
||||
"sync" |
||||
"time" |
||||
) |
||||
|
||||
// Timers capture the duration and rate of events.
|
||||
type Timer interface { |
||||
Metric |
||||
|
||||
AddTiming(int64) |
||||
Avg() int64 |
||||
Min() int64 |
||||
Max() int64 |
||||
Count() int64 |
||||
Max() int64 |
||||
Mean() float64 |
||||
Min() int64 |
||||
Percentile(float64) float64 |
||||
Percentiles([]float64) []float64 |
||||
Rate1() float64 |
||||
Rate5() float64 |
||||
Rate15() float64 |
||||
RateMean() float64 |
||||
StdDev() float64 |
||||
Sum() int64 |
||||
Time(func()) |
||||
Update(time.Duration) |
||||
UpdateSince(time.Time) |
||||
Variance() float64 |
||||
} |
||||
|
||||
type StandardTimer struct { |
||||
*MetricMeta |
||||
|
||||
total int64 |
||||
count int64 |
||||
avg int64 |
||||
min int64 |
||||
max int64 |
||||
// NewCustomTimer constructs a new StandardTimer from a Histogram and a Meter.
|
||||
func NewCustomTimer(meta *MetricMeta, h Histogram, m Meter) Timer { |
||||
if UseNilMetrics { |
||||
return NilTimer{} |
||||
} |
||||
return &StandardTimer{ |
||||
MetricMeta: meta, |
||||
histogram: h, |
||||
meter: m, |
||||
} |
||||
} |
||||
|
||||
// NewTimer constructs a new StandardTimer using an exponentially-decaying
|
||||
// sample with the same reservoir size and alpha as UNIX load averages.
|
||||
func NewTimer(meta *MetricMeta) Timer { |
||||
if UseNilMetrics { |
||||
return NilTimer{} |
||||
} |
||||
return &StandardTimer{ |
||||
MetricMeta: meta, |
||||
avg: 0, |
||||
min: 0, |
||||
max: 0, |
||||
total: 0, |
||||
count: 0, |
||||
histogram: NewHistogram(meta, NewExpDecaySample(1028, 0.015)), |
||||
meter: NewMeter(meta), |
||||
} |
||||
} |
||||
|
||||
func (this *StandardTimer) AddTiming(time int64) { |
||||
if this.min > time { |
||||
this.min = time |
||||
} |
||||
func RegTimer(name string, tagStrings ...string) Timer { |
||||
tr := NewTimer(NewMetricMeta(name, tagStrings)) |
||||
MetricStats.Register(tr) |
||||
return tr |
||||
} |
||||
|
||||
if this.max < time { |
||||
this.max = time |
||||
} |
||||
// NilTimer is a no-op Timer.
|
||||
type NilTimer struct { |
||||
*MetricMeta |
||||
h Histogram |
||||
m Meter |
||||
} |
||||
|
||||
// Count is a no-op.
|
||||
func (NilTimer) Count() int64 { return 0 } |
||||
|
||||
// Max is a no-op.
|
||||
func (NilTimer) Max() int64 { return 0 } |
||||
|
||||
// Mean is a no-op.
|
||||
func (NilTimer) Mean() float64 { return 0.0 } |
||||
|
||||
// Min is a no-op.
|
||||
func (NilTimer) Min() int64 { return 0 } |
||||
|
||||
this.total += time |
||||
this.count++ |
||||
// Percentile is a no-op.
|
||||
func (NilTimer) Percentile(p float64) float64 { return 0.0 } |
||||
|
||||
this.avg = this.total / this.count |
||||
// Percentiles is a no-op.
|
||||
func (NilTimer) Percentiles(ps []float64) []float64 { |
||||
return make([]float64, len(ps)) |
||||
} |
||||
|
||||
func (this *StandardTimer) Clear() { |
||||
this.avg = 0 |
||||
this.min = 0 |
||||
this.max = 0 |
||||
this.total = 0 |
||||
this.count = 0 |
||||
// Rate1 is a no-op.
|
||||
func (NilTimer) Rate1() float64 { return 0.0 } |
||||
|
||||
// Rate5 is a no-op.
|
||||
func (NilTimer) Rate5() float64 { return 0.0 } |
||||
|
||||
// Rate15 is a no-op.
|
||||
func (NilTimer) Rate15() float64 { return 0.0 } |
||||
|
||||
// RateMean is a no-op.
|
||||
func (NilTimer) RateMean() float64 { return 0.0 } |
||||
|
||||
// Snapshot is a no-op.
|
||||
func (n NilTimer) Snapshot() Metric { return n } |
||||
|
||||
// StdDev is a no-op.
|
||||
func (NilTimer) StdDev() float64 { return 0.0 } |
||||
|
||||
// Sum is a no-op.
|
||||
func (NilTimer) Sum() int64 { return 0 } |
||||
|
||||
// Time is a no-op.
|
||||
func (NilTimer) Time(func()) {} |
||||
|
||||
// Update is a no-op.
|
||||
func (NilTimer) Update(time.Duration) {} |
||||
|
||||
// UpdateSince is a no-op.
|
||||
func (NilTimer) UpdateSince(time.Time) {} |
||||
|
||||
// Variance is a no-op.
|
||||
func (NilTimer) Variance() float64 { return 0.0 } |
||||
|
||||
// StandardTimer is the standard implementation of a Timer and uses a Histogram
|
||||
// and Meter.
|
||||
type StandardTimer struct { |
||||
*MetricMeta |
||||
histogram Histogram |
||||
meter Meter |
||||
mutex sync.Mutex |
||||
} |
||||
|
||||
func (this *StandardTimer) Avg() int64 { |
||||
return this.avg |
||||
// Count returns the number of events recorded.
|
||||
func (t *StandardTimer) Count() int64 { |
||||
return t.histogram.Count() |
||||
} |
||||
|
||||
func (this *StandardTimer) Min() int64 { |
||||
return this.min |
||||
// Max returns the maximum value in the sample.
|
||||
func (t *StandardTimer) Max() int64 { |
||||
return t.histogram.Max() |
||||
} |
||||
|
||||
func (this *StandardTimer) Max() int64 { |
||||
return this.max |
||||
// Mean returns the mean of the values in the sample.
|
||||
func (t *StandardTimer) Mean() float64 { |
||||
return t.histogram.Mean() |
||||
} |
||||
|
||||
func (this *StandardTimer) Count() int64 { |
||||
return this.count |
||||
// Min returns the minimum value in the sample.
|
||||
func (t *StandardTimer) Min() int64 { |
||||
return t.histogram.Min() |
||||
} |
||||
|
||||
func (this *StandardTimer) Snapshot() Metric { |
||||
return &StandardTimer{ |
||||
MetricMeta: this.MetricMeta, |
||||
avg: this.avg, |
||||
min: this.min, |
||||
max: this.max, |
||||
total: this.total, |
||||
count: this.count, |
||||
// Percentile returns an arbitrary percentile of the values in the sample.
|
||||
func (t *StandardTimer) Percentile(p float64) float64 { |
||||
return t.histogram.Percentile(p) |
||||
} |
||||
|
||||
// Percentiles returns a slice of arbitrary percentiles of the values in the
|
||||
// sample.
|
||||
func (t *StandardTimer) Percentiles(ps []float64) []float64 { |
||||
return t.histogram.Percentiles(ps) |
||||
} |
||||
|
||||
// Rate1 returns the one-minute moving average rate of events per second.
|
||||
func (t *StandardTimer) Rate1() float64 { |
||||
return t.meter.Rate1() |
||||
} |
||||
|
||||
// Rate5 returns the five-minute moving average rate of events per second.
|
||||
func (t *StandardTimer) Rate5() float64 { |
||||
return t.meter.Rate5() |
||||
} |
||||
|
||||
// Rate15 returns the fifteen-minute moving average rate of events per second.
|
||||
func (t *StandardTimer) Rate15() float64 { |
||||
return t.meter.Rate15() |
||||
} |
||||
|
||||
// RateMean returns the meter's mean rate of events per second.
|
||||
func (t *StandardTimer) RateMean() float64 { |
||||
return t.meter.RateMean() |
||||
} |
||||
|
||||
// Snapshot returns a read-only copy of the timer.
|
||||
func (t *StandardTimer) Snapshot() Metric { |
||||
t.mutex.Lock() |
||||
defer t.mutex.Unlock() |
||||
return &TimerSnapshot{ |
||||
MetricMeta: t.MetricMeta, |
||||
histogram: t.histogram.Snapshot().(*HistogramSnapshot), |
||||
meter: t.meter.Snapshot().(*MeterSnapshot), |
||||
} |
||||
} |
||||
|
||||
// StdDev returns the standard deviation of the values in the sample.
|
||||
func (t *StandardTimer) StdDev() float64 { |
||||
return t.histogram.StdDev() |
||||
} |
||||
|
||||
// Sum returns the sum in the sample.
|
||||
func (t *StandardTimer) Sum() int64 { |
||||
return t.histogram.Sum() |
||||
} |
||||
|
||||
// Record the duration of the execution of the given function.
|
||||
func (t *StandardTimer) Time(f func()) { |
||||
ts := time.Now() |
||||
f() |
||||
t.Update(time.Since(ts)) |
||||
} |
||||
|
||||
// Record the duration of an event.
|
||||
func (t *StandardTimer) Update(d time.Duration) { |
||||
t.mutex.Lock() |
||||
defer t.mutex.Unlock() |
||||
t.histogram.Update(int64(d)) |
||||
t.meter.Mark(1) |
||||
} |
||||
|
||||
// Record the duration of an event that started at a time and ends now.
|
||||
func (t *StandardTimer) UpdateSince(ts time.Time) { |
||||
t.mutex.Lock() |
||||
defer t.mutex.Unlock() |
||||
t.histogram.Update(int64(time.Since(ts))) |
||||
t.meter.Mark(1) |
||||
} |
||||
|
||||
// Variance returns the variance of the values in the sample.
|
||||
func (t *StandardTimer) Variance() float64 { |
||||
return t.histogram.Variance() |
||||
} |
||||
|
||||
// TimerSnapshot is a read-only copy of another Timer.
|
||||
type TimerSnapshot struct { |
||||
*MetricMeta |
||||
histogram *HistogramSnapshot |
||||
meter *MeterSnapshot |
||||
} |
||||
|
||||
// Count returns the number of events recorded at the time the snapshot was
|
||||
// taken.
|
||||
func (t *TimerSnapshot) Count() int64 { return t.histogram.Count() } |
||||
|
||||
// Max returns the maximum value at the time the snapshot was taken.
|
||||
func (t *TimerSnapshot) Max() int64 { return t.histogram.Max() } |
||||
|
||||
// Mean returns the mean value at the time the snapshot was taken.
|
||||
func (t *TimerSnapshot) Mean() float64 { return t.histogram.Mean() } |
||||
|
||||
// Min returns the minimum value at the time the snapshot was taken.
|
||||
func (t *TimerSnapshot) Min() int64 { return t.histogram.Min() } |
||||
|
||||
// Percentile returns an arbitrary percentile of sampled values at the time the
|
||||
// snapshot was taken.
|
||||
func (t *TimerSnapshot) Percentile(p float64) float64 { |
||||
return t.histogram.Percentile(p) |
||||
} |
||||
|
||||
// Percentiles returns a slice of arbitrary percentiles of sampled values at
|
||||
// the time the snapshot was taken.
|
||||
func (t *TimerSnapshot) Percentiles(ps []float64) []float64 { |
||||
return t.histogram.Percentiles(ps) |
||||
} |
||||
|
||||
// Rate1 returns the one-minute moving average rate of events per second at the
|
||||
// time the snapshot was taken.
|
||||
func (t *TimerSnapshot) Rate1() float64 { return t.meter.Rate1() } |
||||
|
||||
// Rate5 returns the five-minute moving average rate of events per second at
|
||||
// the time the snapshot was taken.
|
||||
func (t *TimerSnapshot) Rate5() float64 { return t.meter.Rate5() } |
||||
|
||||
// Rate15 returns the fifteen-minute moving average rate of events per second
|
||||
// at the time the snapshot was taken.
|
||||
func (t *TimerSnapshot) Rate15() float64 { return t.meter.Rate15() } |
||||
|
||||
// RateMean returns the meter's mean rate of events per second at the time the
|
||||
// snapshot was taken.
|
||||
func (t *TimerSnapshot) RateMean() float64 { return t.meter.RateMean() } |
||||
|
||||
// Snapshot returns the snapshot.
|
||||
func (t *TimerSnapshot) Snapshot() Metric { return t } |
||||
|
||||
// StdDev returns the standard deviation of the values at the time the snapshot
|
||||
// was taken.
|
||||
func (t *TimerSnapshot) StdDev() float64 { return t.histogram.StdDev() } |
||||
|
||||
// Sum returns the sum at the time the snapshot was taken.
|
||||
func (t *TimerSnapshot) Sum() int64 { return t.histogram.Sum() } |
||||
|
||||
// Time panics.
|
||||
func (*TimerSnapshot) Time(func()) { |
||||
panic("Time called on a TimerSnapshot") |
||||
} |
||||
|
||||
// Update panics.
|
||||
func (*TimerSnapshot) Update(time.Duration) { |
||||
panic("Update called on a TimerSnapshot") |
||||
} |
||||
|
||||
// UpdateSince panics.
|
||||
func (*TimerSnapshot) UpdateSince(time.Time) { |
||||
panic("UpdateSince called on a TimerSnapshot") |
||||
} |
||||
|
||||
// Variance returns the variance of the values at the time the snapshot was
|
||||
// taken.
|
||||
func (t *TimerSnapshot) Variance() float64 { return t.histogram.Variance() } |
||||
|
Loading…
Reference in new issue