package sarama import ( "fmt" "strings" "github.com/rcrowley/go-metrics" ) // 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 https://github.com/dropwizard/metrics/blob/v3.1.0/metrics-core/src/main/java/com/codahale/metrics/ExponentiallyDecayingReservoir.java#L38 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)) }).(metrics.Histogram) } 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) }