Commit eee49a49 by Torkel Ödegaard

feat(instrumentation): added meter, histogram and new timer, timer now send p25,…

feat(instrumentation): added meter, histogram and new timer, timer now send p25, p75, p90, p99 percentiles in 1000 sample exp decaying sample
parent 86f00077
......@@ -12,8 +12,12 @@ import (
)
var (
NotFound = ApiError(404, "Not found", nil)
ServerError = ApiError(500, "Server error", nil)
NotFound = func() Response {
return ApiError(404, "Not found", nil)
}
ServerError = func() Response {
return ApiError(500, "Server error", nil)
}
)
type Response interface {
......@@ -34,7 +38,7 @@ func wrap(action interface{}) macaron.Handler {
if err == nil && val != nil && len(val) > 0 {
res = val[0].Interface().(Response)
} else {
res = ServerError
res = ServerError()
}
res.WriteTo(c.Resp)
......
......@@ -58,13 +58,13 @@ func main() {
flag.Parse()
writePIDFile()
initRuntime()
metrics.Init()
search.Init()
login.Init()
social.NewOAuthService()
eventpublisher.Init()
plugins.Init()
metrics.Init()
if err := notifications.Init(); err != nil {
log.Fatal(3, "Notification service failed to initialize", err)
......@@ -87,6 +87,7 @@ func initRuntime() {
log.Info("Starting Grafana")
log.Info("Version: %v, Commit: %v, Build date: %v", setting.BuildVersion, setting.BuildCommit, time.Unix(setting.BuildStamp, 0))
setting.LogConfigurationInfo()
sqlstore.NewEngine()
......
// includes code from
// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
// Copyright 2012 Richard Crowley. All rights reserved.
package metrics
import (
"math"
"sync"
"sync/atomic"
)
// EWMAs continuously calculate an exponentially-weighted moving average
// based on an outside source of clock ticks.
type EWMA interface {
Rate() float64
Snapshot() EWMA
Tick()
Update(int64)
}
// NewEWMA constructs a new EWMA with the given alpha.
func NewEWMA(alpha float64) EWMA {
if UseNilMetrics {
return NilEWMA{}
}
return &StandardEWMA{alpha: alpha}
}
// NewEWMA1 constructs a new EWMA for a one-minute moving average.
func NewEWMA1() EWMA {
return NewEWMA(1 - math.Exp(-5.0/60.0/1))
}
// NewEWMA5 constructs a new EWMA for a five-minute moving average.
func NewEWMA5() EWMA {
return NewEWMA(1 - math.Exp(-5.0/60.0/5))
}
// NewEWMA15 constructs a new EWMA for a fifteen-minute moving average.
func NewEWMA15() EWMA {
return NewEWMA(1 - math.Exp(-5.0/60.0/15))
}
// EWMASnapshot is a read-only copy of another EWMA.
type EWMASnapshot float64
// Rate returns the rate of events per second at the time the snapshot was
// taken.
func (a EWMASnapshot) Rate() float64 { return float64(a) }
// Snapshot returns the snapshot.
func (a EWMASnapshot) Snapshot() EWMA { return a }
// Tick panics.
func (EWMASnapshot) Tick() {
panic("Tick called on an EWMASnapshot")
}
// Update panics.
func (EWMASnapshot) Update(int64) {
panic("Update called on an EWMASnapshot")
}
// NilEWMA is a no-op EWMA.
type NilEWMA struct{}
// Rate is a no-op.
func (NilEWMA) Rate() float64 { return 0.0 }
// Snapshot is a no-op.
func (NilEWMA) Snapshot() EWMA { return NilEWMA{} }
// Tick is a no-op.
func (NilEWMA) Tick() {}
// Update is a no-op.
func (NilEWMA) Update(n int64) {}
// StandardEWMA is the standard implementation of an EWMA and tracks the number
// of uncounted events and processes them on each tick. It uses the
// sync/atomic package to manage uncounted events.
type StandardEWMA struct {
uncounted int64 // /!\ this should be the first member to ensure 64-bit alignment
alpha float64
rate float64
init bool
mutex sync.Mutex
}
// Rate returns the moving average rate of events per second.
func (a *StandardEWMA) Rate() float64 {
a.mutex.Lock()
defer a.mutex.Unlock()
return a.rate * float64(1e9)
}
// Snapshot returns a read-only copy of the EWMA.
func (a *StandardEWMA) Snapshot() EWMA {
return EWMASnapshot(a.Rate())
}
// Tick ticks the clock to update the moving average. It assumes it is called
// every five seconds.
func (a *StandardEWMA) Tick() {
count := atomic.LoadInt64(&a.uncounted)
atomic.AddInt64(&a.uncounted, -count)
instantRate := float64(count) / float64(5e9)
a.mutex.Lock()
defer a.mutex.Unlock()
if a.init {
a.rate += a.alpha * (instantRate - a.rate)
} else {
a.init = true
a.rate = instantRate
}
}
// Update adds n uncounted events.
func (a *StandardEWMA) Update(n int64) {
atomic.AddInt64(&a.uncounted, n)
}
package metrics
// type comboCounterRef struct {
// *MetricMeta
// usageCounter Counter
// metricCounter Counter
// }
//
// 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 (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()
// }
......@@ -58,5 +58,4 @@ type Metric interface {
GetTagsCopy() map[string]string
StringifyTags() string
Snapshot() Metric
Clear()
}
......@@ -6,6 +6,7 @@ import "sync/atomic"
type Counter interface {
Metric
Clear()
Count() int64
Dec(int64)
Inc(int64)
......@@ -19,6 +20,12 @@ func NewCounter(meta *MetricMeta) Counter {
}
}
func RegCounter(name string, tagStrings ...string) Counter {
cr := NewCounter(NewMetricMeta(name, tagStrings))
MetricStats.Register(cr)
return cr
}
// StandardCounter is the standard implementation of a Counter and uses the
// sync/atomic package to manage a single int64 value.
type StandardCounter struct {
......
......@@ -4,6 +4,7 @@ import (
"bytes"
"fmt"
"net"
"reflect"
"time"
"github.com/grafana/grafana/pkg/log"
......@@ -40,23 +41,38 @@ func (this *GraphitePublisher) Publish(metrics []Metric) {
buf := bytes.NewBufferString("")
now := time.Now().Unix()
addToBuf := func(metric string, value int64) {
addIntToBuf := func(metric string, value int64) {
buf.WriteString(fmt.Sprintf("%s %d %d\n", metric, value, now))
}
addFloatToBuf := func(metric string, value float64) {
buf.WriteString(fmt.Sprintf("%s %f %d\n", metric, value, now))
}
for _, m := range metrics {
log.Info("metric: %v, %v", m, reflect.TypeOf(m))
metricName := this.Prefix + m.Name() + m.StringifyTags()
log.Info(metricName)
switch metric := m.(type) {
case Counter:
addToBuf(metricName+".count", metric.Count())
addIntToBuf(metricName+".count", metric.Count())
case SimpleTimer:
addIntToBuf(metricName+".count", metric.Count())
addIntToBuf(metricName+".max", metric.Max())
addIntToBuf(metricName+".min", metric.Min())
addFloatToBuf(metricName+".mean", metric.Mean())
case Timer:
addToBuf(metricName+".count", metric.Count())
addToBuf(metricName+".max", metric.Max())
addToBuf(metricName+".min", metric.Min())
addToBuf(metricName+".avg", metric.Avg())
percentiles := metric.Percentiles([]float64{0.25, 0.75, 0.90, 0.99})
addIntToBuf(metricName+".count", metric.Count())
addIntToBuf(metricName+".max", metric.Max())
addIntToBuf(metricName+".min", metric.Min())
addFloatToBuf(metricName+".mean", metric.Mean())
addFloatToBuf(metricName+".std", metric.StdDev())
addFloatToBuf(metricName+".p25", percentiles[0])
addFloatToBuf(metricName+".p75", percentiles[1])
addFloatToBuf(metricName+".p90", percentiles[2])
addFloatToBuf(metricName+".p99", percentiles[3])
}
}
log.Trace("Metrics: GraphitePublisher.Publish() \n%s", buf)
......
// includes code from
// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
// Copyright 2012 Richard Crowley. All rights reserved.
package metrics
// Histograms calculate distribution statistics from a series of int64 values.
type Histogram interface {
Metric
Clear()
Count() int64
Max() int64
Mean() float64
Min() int64
Percentile(float64) float64
Percentiles([]float64) []float64
StdDev() float64
Sum() int64
Update(int64)
Variance() float64
}
func NewHistogram(meta *MetricMeta, s Sample) Histogram {
return &StandardHistogram{
MetricMeta: meta,
sample: s,
}
}
// HistogramSnapshot is a read-only copy of another Histogram.
type HistogramSnapshot struct {
*MetricMeta
sample *SampleSnapshot
}
// Clear panics.
func (*HistogramSnapshot) Clear() {
panic("Clear called on a HistogramSnapshot")
}
// Count returns the number of samples recorded at the time the snapshot was
// taken.
func (h *HistogramSnapshot) Count() int64 { return h.sample.Count() }
// Max returns the maximum value in the sample at the time the snapshot was
// taken.
func (h *HistogramSnapshot) Max() int64 { return h.sample.Max() }
// Mean returns the mean of the values in the sample at the time the snapshot
// was taken.
func (h *HistogramSnapshot) Mean() float64 { return h.sample.Mean() }
// Min returns the minimum value in the sample at the time the snapshot was
// taken.
func (h *HistogramSnapshot) Min() int64 { return h.sample.Min() }
// Percentile returns an arbitrary percentile of values in the sample at the
// time the snapshot was taken.
func (h *HistogramSnapshot) Percentile(p float64) float64 {
return h.sample.Percentile(p)
}
// Percentiles returns a slice of arbitrary percentiles of values in the sample
// at the time the snapshot was taken.
func (h *HistogramSnapshot) Percentiles(ps []float64) []float64 {
return h.sample.Percentiles(ps)
}
// Sample returns the Sample underlying the histogram.
func (h *HistogramSnapshot) Sample() Sample { return h.sample }
// Snapshot returns the snapshot.
func (h *HistogramSnapshot) Snapshot() Metric { return h }
// StdDev returns the standard deviation of the values in the sample at the
// time the snapshot was taken.
func (h *HistogramSnapshot) StdDev() float64 { return h.sample.StdDev() }
// Sum returns the sum in the sample at the time the snapshot was taken.
func (h *HistogramSnapshot) Sum() int64 { return h.sample.Sum() }
// Update panics.
func (*HistogramSnapshot) Update(int64) {
panic("Update called on a HistogramSnapshot")
}
// Variance returns the variance of inputs at the time the snapshot was taken.
func (h *HistogramSnapshot) Variance() float64 { return h.sample.Variance() }
// NilHistogram is a no-op Histogram.
type NilHistogram struct {
*MetricMeta
}
// Clear is a no-op.
func (NilHistogram) Clear() {}
// Count is a no-op.
func (NilHistogram) Count() int64 { return 0 }
// Max is a no-op.
func (NilHistogram) Max() int64 { return 0 }
// Mean is a no-op.
func (NilHistogram) Mean() float64 { return 0.0 }
// Min is a no-op.
func (NilHistogram) Min() int64 { return 0 }
// Percentile is a no-op.
func (NilHistogram) Percentile(p float64) float64 { return 0.0 }
// Percentiles is a no-op.
func (NilHistogram) Percentiles(ps []float64) []float64 {
return make([]float64, len(ps))
}
// Sample is a no-op.
func (NilHistogram) Sample() Sample { return NilSample{} }
// Snapshot is a no-op.
func (n NilHistogram) Snapshot() Metric { return n }
// StdDev is a no-op.
func (NilHistogram) StdDev() float64 { return 0.0 }
// Sum is a no-op.
func (NilHistogram) Sum() int64 { return 0 }
// Update is a no-op.
func (NilHistogram) Update(v int64) {}
// Variance is a no-op.
func (NilHistogram) Variance() float64 { return 0.0 }
// StandardHistogram is the standard implementation of a Histogram and uses a
// Sample to bound its memory use.
type StandardHistogram struct {
*MetricMeta
sample Sample
}
// Clear clears the histogram and its sample.
func (h *StandardHistogram) Clear() { h.sample.Clear() }
// Count returns the number of samples recorded since the histogram was last
// cleared.
func (h *StandardHistogram) Count() int64 { return h.sample.Count() }
// Max returns the maximum value in the sample.
func (h *StandardHistogram) Max() int64 { return h.sample.Max() }
// Mean returns the mean of the values in the sample.
func (h *StandardHistogram) Mean() float64 { return h.sample.Mean() }
// Min returns the minimum value in the sample.
func (h *StandardHistogram) Min() int64 { return h.sample.Min() }
// Percentile returns an arbitrary percentile of the values in the sample.
func (h *StandardHistogram) Percentile(p float64) float64 {
return h.sample.Percentile(p)
}
// Percentiles returns a slice of arbitrary percentiles of the values in the
// sample.
func (h *StandardHistogram) Percentiles(ps []float64) []float64 {
return h.sample.Percentiles(ps)
}
// Sample returns the Sample underlying the histogram.
func (h *StandardHistogram) Sample() Sample { return h.sample }
// Snapshot returns a read-only copy of the histogram.
func (h *StandardHistogram) Snapshot() Metric {
return &HistogramSnapshot{sample: h.sample.Snapshot().(*SampleSnapshot)}
}
// StdDev returns the standard deviation of the values in the sample.
func (h *StandardHistogram) StdDev() float64 { return h.sample.StdDev() }
// Sum returns the sum in the sample.
func (h *StandardHistogram) Sum() int64 { return h.sample.Sum() }
// Update samples a new value.
func (h *StandardHistogram) Update(v int64) { h.sample.Update(v) }
// Variance returns the variance of the values in the sample.
func (h *StandardHistogram) Variance() float64 { return h.sample.Variance() }
// includes code from
// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
// Copyright 2012 Richard Crowley. All rights reserved.
package metrics
import "testing"
func BenchmarkHistogram(b *testing.B) {
h := NewHistogram(nil, NewUniformSample(100))
b.ResetTimer()
for i := 0; i < b.N; i++ {
h.Update(int64(i))
}
}
func TestHistogram10000(t *testing.T) {
h := NewHistogram(nil, NewUniformSample(100000))
for i := 1; i <= 10000; i++ {
h.Update(int64(i))
}
testHistogram10000(t, h)
}
func TestHistogramEmpty(t *testing.T) {
h := NewHistogram(nil, NewUniformSample(100))
if count := h.Count(); 0 != count {
t.Errorf("h.Count(): 0 != %v\n", count)
}
if min := h.Min(); 0 != min {
t.Errorf("h.Min(): 0 != %v\n", min)
}
if max := h.Max(); 0 != max {
t.Errorf("h.Max(): 0 != %v\n", max)
}
if mean := h.Mean(); 0.0 != mean {
t.Errorf("h.Mean(): 0.0 != %v\n", mean)
}
if stdDev := h.StdDev(); 0.0 != stdDev {
t.Errorf("h.StdDev(): 0.0 != %v\n", stdDev)
}
ps := h.Percentiles([]float64{0.5, 0.75, 0.99})
if 0.0 != ps[0] {
t.Errorf("median: 0.0 != %v\n", ps[0])
}
if 0.0 != ps[1] {
t.Errorf("75th percentile: 0.0 != %v\n", ps[1])
}
if 0.0 != ps[2] {
t.Errorf("99th percentile: 0.0 != %v\n", ps[2])
}
}
func TestHistogramSnapshot(t *testing.T) {
h := NewHistogram(nil, NewUniformSample(100000))
for i := 1; i <= 10000; i++ {
h.Update(int64(i))
}
snapshot := h.Snapshot().(Histogram)
h.Update(0)
testHistogram10000(t, snapshot)
}
func testHistogram10000(t *testing.T, h Histogram) {
if count := h.Count(); 10000 != count {
t.Errorf("h.Count(): 10000 != %v\n", count)
}
if min := h.Min(); 1 != min {
t.Errorf("h.Min(): 1 != %v\n", min)
}
if max := h.Max(); 10000 != max {
t.Errorf("h.Max(): 10000 != %v\n", max)
}
if mean := h.Mean(); 5000.5 != mean {
t.Errorf("h.Mean(): 5000.5 != %v\n", mean)
}
if stdDev := h.StdDev(); 2886.751331514372 != stdDev {
t.Errorf("h.StdDev(): 2886.751331514372 != %v\n", stdDev)
}
ps := h.Percentiles([]float64{0.5, 0.75, 0.99})
if 5000.5 != ps[0] {
t.Errorf("median: 5000.5 != %v\n", ps[0])
}
if 7500.75 != ps[1] {
t.Errorf("75th percentile: 7500.75 != %v\n", ps[1])
}
if 9900.99 != ps[2] {
t.Errorf("99th percentile: 9900.99 != %v\n", ps[2])
}
}
......@@ -76,7 +76,7 @@ func (this *InfluxPublisher) Publish(metrics []Metric) {
for _, m := range metrics {
tags := m.GetTagsCopy()
addPoint := func(name string, value int64) {
addPoint := func(name string, value interface{}) {
bp.Points = append(bp.Points, client.Point{
Measurement: name,
Tags: tags,
......@@ -87,11 +87,11 @@ func (this *InfluxPublisher) Publish(metrics []Metric) {
switch metric := m.(type) {
case Counter:
addPoint(metric.Name()+".count", metric.Count())
case Timer:
case SimpleTimer:
addPoint(metric.Name()+".count", metric.Count())
addPoint(metric.Name()+".max", metric.Max())
addPoint(metric.Name()+".min", metric.Min())
addPoint(metric.Name()+".avg", metric.Avg())
addPoint(metric.Name()+".avg", metric.Mean())
}
}
......
// includes code from
// https://raw.githubusercontent.com/rcrowley/go-metrics/master/sample.go
// Copyright 2012 Richard Crowley. All rights reserved.
package metrics
import (
"sync"
"time"
)
// Meters count events to produce exponentially-weighted moving average rates
// at one-, five-, and fifteen-minutes and a mean rate.
type Meter interface {
Metric
Count() int64
Mark(int64)
Rate1() float64
Rate5() float64
Rate15() float64
RateMean() float64
}
// NewMeter constructs a new StandardMeter and launches a goroutine.
func NewMeter(meta *MetricMeta) Meter {
if UseNilMetrics {
return NilMeter{}
}
m := newStandardMeter(meta)
arbiter.Lock()
defer arbiter.Unlock()
arbiter.meters = append(arbiter.meters, m)
if !arbiter.started {
arbiter.started = true
go arbiter.tick()
}
return m
}
type MeterSnapshot struct {
*MetricMeta
count int64
rate1, rate5, rate15, rateMean float64
}
// Count returns the count of events at the time the snapshot was taken.
func (m *MeterSnapshot) Count() int64 { return m.count }
// Mark panics.
func (*MeterSnapshot) Mark(n int64) {
panic("Mark called on a MeterSnapshot")
}
// Rate1 returns the one-minute moving average rate of events per second at the
// time the snapshot was taken.
func (m *MeterSnapshot) Rate1() float64 { return m.rate1 }
// Rate5 returns the five-minute moving average rate of events per second at
// the time the snapshot was taken.
func (m *MeterSnapshot) Rate5() float64 { return m.rate5 }
// Rate15 returns the fifteen-minute moving average rate of events per second
// at the time the snapshot was taken.
func (m *MeterSnapshot) Rate15() float64 { return m.rate15 }
// RateMean returns the meter's mean rate of events per second at the time the
// snapshot was taken.
func (m *MeterSnapshot) RateMean() float64 { return m.rateMean }
// Snapshot returns the snapshot.
func (m *MeterSnapshot) Snapshot() Metric { return m }
// NilMeter is a no-op Meter.
type NilMeter struct{ *MetricMeta }
// 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()
}
}
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()
}
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")
}
......@@ -15,14 +15,14 @@ import (
)
func Init() {
go instrumentationLoop()
settings := readSettings()
initMetricVars(settings)
go instrumentationLoop(settings)
}
func instrumentationLoop() chan struct{} {
func instrumentationLoop(settings *MetricSettings) chan struct{} {
M_Instance_Start.Inc(1)
settings := readSettings()
onceEveryDayTick := time.NewTicker(time.Hour * 24)
secondTicker := time.NewTicker(time.Second * time.Duration(settings.IntervalSeconds))
......@@ -61,16 +61,6 @@ func sendUsageStats() {
"metrics": metrics,
}
snapshots := UsageStats.GetSnapshots()
for _, m := range snapshots {
switch metric := m.(type) {
case Counter:
if metric.Count() > 0 {
metrics[metric.Name()+".count"] = metric.Count()
}
}
}
statsQuery := m.GetSystemStatsQuery{}
if err := bus.Dispatch(&statsQuery); err != nil {
log.Error(3, "Failed to get system stats", err)
......
......@@ -32,7 +32,12 @@ func (r *StandardRegistry) GetSnapshots() []Metric {
metrics := make([]Metric, len(r.metrics))
for i, metric := range r.metrics {
metrics[i] = metric.Snapshot()
metric.Clear()
switch typedMetric := metric.(type) {
case Histogram:
// do not clear histograms
case Counter:
typedMetric.Clear()
}
}
return metrics
}
// 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{}{}
}
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,
}
}
// 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() }
......@@ -39,12 +39,12 @@ func Logger() macaron.Handler {
rw := res.(macaron.ResponseWriter)
c.Next()
timeTakenMs := int64(time.Since(start) / time.Millisecond)
timeTakenMs := time.Since(start) / time.Millisecond
content := fmt.Sprintf("Completed %s %s \"%s %s %s\" %v %s %d bytes in %dms", c.RemoteAddr(), uname, req.Method, req.URL.Path, req.Proto, rw.Status(), http.StatusText(rw.Status()), rw.Size(), timeTakenMs)
if timer, ok := c.Data["perfmon.timer"]; ok {
timerTyped := timer.(metrics.Timer)
timerTyped.AddTiming(timeTakenMs)
timerTyped.Update(timeTakenMs)
}
switch rw.Status() {
......
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