/
aggregator.go
271 lines (226 loc) · 6.4 KB
/
aggregator.go
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package statsd
import (
"strings"
"sync"
"sync/atomic"
"time"
)
type (
countsMap map[string]*countMetric
gaugesMap map[string]*gaugeMetric
setsMap map[string]*setMetric
bufferedMetricMap map[string]*histogramMetric
)
// bufferedMetricContexts represent the contexts for Histograms, Distributions
// and Timing. Since those 3 metric types behave the same way and are sampled
// with the same type they're represented by the same class.
type bufferedMetricContexts struct {
nbContext int32
mutex sync.RWMutex
values bufferedMetricMap
newMetric func(string, float64, string) *bufferedMetric
}
func newBufferedContexts(newMetric func(string, float64, string) *bufferedMetric) bufferedMetricContexts {
return bufferedMetricContexts{
values: bufferedMetricMap{},
newMetric: newMetric,
}
}
func (bc *bufferedMetricContexts) flush(metrics []metric) []metric {
bc.mutex.Lock()
values := bc.values
bc.values = bufferedMetricMap{}
bc.mutex.Unlock()
for _, d := range values {
metrics = append(metrics, d.flushUnsafe())
}
atomic.AddInt32(&bc.nbContext, int32(len(values)))
return metrics
}
func (bc *bufferedMetricContexts) sample(name string, value float64, tags []string) error {
context, stringTags := getContextAndTags(name, tags)
bc.mutex.RLock()
if v, found := bc.values[context]; found {
v.sample(value)
bc.mutex.RUnlock()
return nil
}
bc.mutex.RUnlock()
bc.mutex.Lock()
bc.values[context] = bc.newMetric(name, value, stringTags)
bc.mutex.Unlock()
return nil
}
func (bc *bufferedMetricContexts) resetAndGetNbContext() int32 {
return atomic.SwapInt32(&bc.nbContext, 0)
}
type aggregator struct {
nbContextGauge int32
nbContextCount int32
nbContextSet int32
countsM sync.RWMutex
gaugesM sync.RWMutex
setsM sync.RWMutex
gauges gaugesMap
counts countsMap
sets setsMap
histograms bufferedMetricContexts
distributions bufferedMetricContexts
timings bufferedMetricContexts
closed chan struct{}
exited chan struct{}
client *Client
}
type aggregatorMetrics struct {
nbContext int32
nbContextGauge int32
nbContextCount int32
nbContextSet int32
nbContextHistogram int32
nbContextDistribution int32
nbContextTiming int32
}
func newAggregator(c *Client) *aggregator {
return &aggregator{
client: c,
counts: countsMap{},
gauges: gaugesMap{},
sets: setsMap{},
histograms: newBufferedContexts(newHistogramMetric),
distributions: newBufferedContexts(newDistributionMetric),
timings: newBufferedContexts(newTimingMetric),
closed: make(chan struct{}),
exited: make(chan struct{}),
}
}
func (a *aggregator) start(flushInterval time.Duration) {
ticker := time.NewTicker(flushInterval)
go func() {
for {
select {
case <-ticker.C:
a.sendMetrics()
case <-a.closed:
close(a.exited)
return
}
}
}()
}
func (a *aggregator) sendMetrics() {
for _, m := range a.flushMetrics() {
a.client.send(m)
}
}
func (a *aggregator) stop() {
close(a.closed)
<-a.exited
a.sendMetrics()
}
func (a *aggregator) flushTelemetryMetrics() *aggregatorMetrics {
if a == nil {
return nil
}
am := &aggregatorMetrics{
nbContextGauge: atomic.SwapInt32(&a.nbContextGauge, 0),
nbContextCount: atomic.SwapInt32(&a.nbContextCount, 0),
nbContextSet: atomic.SwapInt32(&a.nbContextSet, 0),
nbContextHistogram: a.histograms.resetAndGetNbContext(),
nbContextDistribution: a.distributions.resetAndGetNbContext(),
nbContextTiming: a.timings.resetAndGetNbContext(),
}
am.nbContext = am.nbContextGauge + am.nbContextCount + am.nbContextSet + am.nbContextHistogram + am.nbContextDistribution + am.nbContextTiming
return am
}
func (a *aggregator) flushMetrics() []metric {
metrics := []metric{}
// We reset the values to avoid sending 'zero' values for metrics not
// sampled during this flush interval
a.setsM.Lock()
sets := a.sets
a.sets = setsMap{}
a.setsM.Unlock()
for _, s := range sets {
metrics = append(metrics, s.flushUnsafe()...)
}
a.gaugesM.Lock()
gauges := a.gauges
a.gauges = gaugesMap{}
a.gaugesM.Unlock()
for _, g := range gauges {
metrics = append(metrics, g.flushUnsafe())
}
a.countsM.Lock()
counts := a.counts
a.counts = countsMap{}
a.countsM.Unlock()
for _, c := range counts {
metrics = append(metrics, c.flushUnsafe())
}
metrics = a.histograms.flush(metrics)
metrics = a.distributions.flush(metrics)
metrics = a.timings.flush(metrics)
atomic.AddInt32(&a.nbContextCount, int32(len(counts)))
atomic.AddInt32(&a.nbContextGauge, int32(len(gauges)))
atomic.AddInt32(&a.nbContextSet, int32(len(sets)))
return metrics
}
func getContext(name string, tags []string) string {
return name + ":" + strings.Join(tags, tagSeparatorSymbol)
}
func getContextAndTags(name string, tags []string) (string, string) {
stringTags := strings.Join(tags, tagSeparatorSymbol)
return name + ":" + stringTags, stringTags
}
func (a *aggregator) count(name string, value int64, tags []string) error {
context := getContext(name, tags)
a.countsM.RLock()
if count, found := a.counts[context]; found {
count.sample(value)
a.countsM.RUnlock()
return nil
}
a.countsM.RUnlock()
a.countsM.Lock()
a.counts[context] = newCountMetric(name, value, tags)
a.countsM.Unlock()
return nil
}
func (a *aggregator) gauge(name string, value float64, tags []string) error {
context := getContext(name, tags)
a.gaugesM.RLock()
if gauge, found := a.gauges[context]; found {
gauge.sample(value)
a.gaugesM.RUnlock()
return nil
}
a.gaugesM.RUnlock()
gauge := newGaugeMetric(name, value, tags)
a.gaugesM.Lock()
a.gauges[context] = gauge
a.gaugesM.Unlock()
return nil
}
func (a *aggregator) set(name string, value string, tags []string) error {
context := getContext(name, tags)
a.setsM.RLock()
if set, found := a.sets[context]; found {
set.sample(value)
a.setsM.RUnlock()
return nil
}
a.setsM.RUnlock()
a.setsM.Lock()
a.sets[context] = newSetMetric(name, value, tags)
a.setsM.Unlock()
return nil
}
func (a *aggregator) histogram(name string, value float64, tags []string) error {
return a.histograms.sample(name, value, tags)
}
func (a *aggregator) distribution(name string, value float64, tags []string) error {
return a.distributions.sample(name, value, tags)
}
func (a *aggregator) timing(name string, value float64, tags []string) error {
return a.timings.sample(name, value, tags)
}