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package sarama
import (
// Use exponentially decaying reservoir for sampling histograms with the same defaults as the Java library:
// 1028 elements, which offers a 99.9% confidence level with a 5% margin of error assuming a normal distribution,
// and an alpha factor of 0.015, which heavily biases the reservoir to the past 5 minutes of measurements.
// See
const (
metricsReservoirSize = 1028
metricsAlphaFactor = 0.015
func getOrRegisterHistogram(name string, r metrics.Registry) metrics.Histogram {
return r.GetOrRegister(name, func() metrics.Histogram {
return metrics.NewHistogram(metrics.NewExpDecaySample(metricsReservoirSize, metricsAlphaFactor))
func getMetricNameForBroker(name string, broker *Broker) string {
// Use broker id like the Java client as it does not contain '.' or ':' characters that
// can be interpreted as special character by monitoring tool (e.g. Graphite)
return fmt.Sprintf(name+"-for-broker-%d", broker.ID())
func getOrRegisterBrokerMeter(name string, broker *Broker, r metrics.Registry) metrics.Meter {
return metrics.GetOrRegisterMeter(getMetricNameForBroker(name, broker), r)
func getOrRegisterBrokerHistogram(name string, broker *Broker, r metrics.Registry) metrics.Histogram {
return getOrRegisterHistogram(getMetricNameForBroker(name, broker), r)
func getMetricNameForTopic(name string, topic string) string {
// Convert dot to _ since reporters like Graphite typically use dot to represent hierarchy
// cf. KAFKA-1902 and KAFKA-2337
return fmt.Sprintf(name+"-for-topic-%s", strings.Replace(topic, ".", "_", -1))
func getOrRegisterTopicMeter(name string, topic string, r metrics.Registry) metrics.Meter {
return metrics.GetOrRegisterMeter(getMetricNameForTopic(name, topic), r)
func getOrRegisterTopicHistogram(name string, topic string, r metrics.Registry) metrics.Histogram {
return getOrRegisterHistogram(getMetricNameForTopic(name, topic), r)
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