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/*
* =========================================================================================
* Copyright © 2013-2014 the kamon project <http://kamon.io/>
*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file
* except in compliance with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software distributed under the
* License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
* either express or implied. See the License for the specific language governing permissions
* and limitations under the License.
* =========================================================================================
*/
package kamon.influxdb
import java.lang.management.ManagementFactory
import com.typesafe.config.Config
import kamon.metric.instrument.Histogram
import kamon.metric.{ Entity, MetricKey }
import collection.JavaConversions._
trait TagsGenerator {
protected val config: Config
protected val application = config.getString("application-name")
val hostname = {
val hostnameOverride = config.getString("hostname-override")
if (hostnameOverride.equals("none")) {
ManagementFactory.getRuntimeMXBean.getName.split('@')(1)
} else {
hostnameOverride
}
}
protected val percentiles = config.getDoubleList("percentiles").toList
protected def generateTags(entity: Entity, metricKey: MetricKey): Map[String, String] =
entity.category match {
case "trace-segment" ⇒
Map(
"category" -> normalize(entity.tags("trace")),
"entity" -> normalize(entity.name),
"hostname" -> normalize(hostname),
"metric" -> normalize(metricKey.name))
case _ ⇒
Map(
"category" -> normalize(entity.category),
"entity" -> normalize(entity.name),
"hostname" -> normalize(hostname),
"metric" -> normalize(metricKey.name))
}
protected def histogramValues(hs: Histogram.Snapshot): Map[String, BigDecimal] = {
val defaults = Map(
"lower" -> BigDecimal(hs.min),
"mean" -> average(hs),
"upper" -> BigDecimal(hs.max))
percentiles.foldLeft(defaults) { (acc, p) ⇒
val fractional = p % 1
val integral = (p - fractional).toInt
val percentile = BigDecimal(hs.percentile(p))
if (fractional > 0.0) acc ++ Map(s"p$p" -> percentile)
else acc ++ Map(s"p$integral" -> percentile)
}
}
protected def normalize(s: String): String =
s
.replace(": ", "-")
.replace(":\\", "-")
.replace(":", "-")
.replace(" ", "-")
.replace("\\", "-")
.replace("/", "-")
.replace(".", "-")
private def average(histogram: Histogram.Snapshot): BigDecimal = {
if (histogram.numberOfMeasurements == 0) BigDecimal(0.0)
else BigDecimal(histogram.sum / histogram.numberOfMeasurements.toDouble)
}
}
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