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/* =========================================================================================
* Copyright © 2013-2017 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.metric
import java.time.{Duration, Instant}
import kamon.{Kamon, Tags}
import kamon.metric.PeriodSnapshotAccumulator.{MetricDistributionKey, MetricValueKey}
import kamon.util.Clock
import scala.collection.mutable
class DistributionAccumulator(dynamicRange: DynamicRange) {
private val accumulatorHistogram = new HdrHistogram("metric-distribution-accumulator",
tags = Map.empty, unit = MeasurementUnit.none, dynamicRange)
def add(distribution: Distribution): Unit =
distribution.bucketsIterator.foreach(b => accumulatorHistogram.record(b.value, b.frequency))
def result(resetState: Boolean): Distribution =
accumulatorHistogram.snapshot(resetState).distribution
}
/**
* Merges snapshots over the specified duration and produces a snapshot with all merged metrics provided to it within
* the period. This class is mutable, not thread safe and assumes that all snapshots passed to the `accumulate(...)`
* function are ordered in time.
*
* The typical use of this class would be when writing metric reporters that have to report data at a specific interval
* and wants to protect from users configuring a more frequent metrics tick interval. Example:
*
* {{{
* class Reporter extends MetricsReporter {
* val accumulator = new PeriodSnapshotAccumulator(Duration.ofSeconds(60), Duration.ofSeconds(1))
*
* def reportPeriodSnapshot(snapshot: PeriodSnapshot): Unit = {
* accumulator.add(snapshot).foreach(accumulatedSnapshot => {
* // Process your snapshot here, will only be called when the expected period has passed.
* }
* }
*
* ...
* }
* }}}
*
* The margin time is used to determine how close the current accumulated interval can to be to the expected interval
* and still get reported. In the example above a accumulated period of 59.6 seconds has a margin to 60 seconds of
* 0.4 seconds, thus, getting reported immediately instead of waiting for the next snapshot.
*
* A detail of what has been accumulated by calling the `.peek()` function.
*
* @param duration for how long to accumulate snapshots
* @param margin error margin for expected reporting period
*/
class PeriodSnapshotAccumulator(duration: Duration, margin: Duration) {
private val counters = mutable.Map[MetricValueKey, Long]()
private val gauges = mutable.Map[MetricValueKey, Long]()
private val histograms = mutable.Map[MetricDistributionKey, DistributionAccumulator]()
private val rangeSamplers = mutable.Map[MetricDistributionKey, DistributionAccumulator]()
private var nextTick: Instant = Instant.EPOCH
private var accumulatingFrom: Option[Instant] = None
def add(periodSnapshot: PeriodSnapshot): Option[PeriodSnapshot] = {
// Initialize the next tick based on incoming snapshots.
if(nextTick == Instant.EPOCH)
nextTick = Clock.nextTick(periodSnapshot.to, duration)
// short-circuit if there is no need to accumulate (e.g. when metrics tick-interval is the same as duration or the
// snapshots have a longer period than the duration).
if(isSameDurationAsTickInterval() || (isAroundNextTick(periodSnapshot.to) && accumulatingFrom.isEmpty)) Some(periodSnapshot) else {
if (accumulatingFrom.isEmpty)
accumulatingFrom = Some(periodSnapshot.from)
periodSnapshot.metrics.counters.foreach(c => accumulateValue(counters, c))
periodSnapshot.metrics.gauges.foreach(g => replaceValue(gauges, g))
periodSnapshot.metrics.histograms.foreach(h => accumulateDistribution(histograms, h))
periodSnapshot.metrics.rangeSamplers.foreach(rs => accumulateDistribution(rangeSamplers, rs))
for(from <- accumulatingFrom if isAroundNextTick(periodSnapshot.to)) yield {
val accumulatedPeriodSnapshot = buildPeriodSnapshot(from, periodSnapshot.to, resetState = true)
nextTick = Clock.nextTick(nextTick, duration)
accumulatingFrom = None
clearAccumulatedData()
accumulatedPeriodSnapshot
}
}
}
def peek(): PeriodSnapshot = {
buildPeriodSnapshot(accumulatingFrom.getOrElse(nextTick), nextTick, resetState = false)
}
private def isAroundNextTick(instant: Instant): Boolean = {
Duration.between(instant, nextTick.minus(margin)).toMillis() <= 0
}
private def isSameDurationAsTickInterval(): Boolean = {
Kamon.config().getDuration("kamon.metric.tick-interval").equals(duration)
}
private def buildPeriodSnapshot(from: Instant, to: Instant, resetState: Boolean): PeriodSnapshot = {
val metrics = MetricsSnapshot(
histograms = histograms.map(createDistributionSnapshot(resetState)).toSeq,
rangeSamplers = rangeSamplers.map(createDistributionSnapshot(resetState)).toSeq,
gauges = gauges.map(createValueSnapshot(resetState)).toSeq,
counters = counters.map(createValueSnapshot(resetState)).toSeq
)
PeriodSnapshot(from, to, metrics)
}
private def accumulateValue(cache: mutable.Map[MetricValueKey, Long], metric: MetricValue): Unit = {
val key = MetricValueKey(metric.name, metric.tags, metric.unit)
cache.get(key).map(previousValue => {
cache.put(key, metric.value + previousValue)
}).orElse {
cache.put(key, metric.value)
}
}
private def replaceValue(cache: mutable.Map[MetricValueKey, Long], metric: MetricValue): Unit = {
val key = MetricValueKey(metric.name, metric.tags, metric.unit)
cache.put(key, metric.value)
}
private def createValueSnapshot(reset: Boolean)(pair: (MetricValueKey, Long)): MetricValue = {
val (key, value) = pair
MetricValue(key.name, key.tags, key.unit, value)
}
private def createDistributionSnapshot(resetState: Boolean)(pair: (MetricDistributionKey, DistributionAccumulator)): MetricDistribution = {
val (key, value) = pair
MetricDistribution(key.name, key.tags, key.unit, key.dynamicRange, value.result(resetState))
}
private def accumulateDistribution(cache: mutable.Map[MetricDistributionKey, DistributionAccumulator], metric: MetricDistribution): Unit = {
val key = MetricDistributionKey(metric.name, metric.tags, metric.unit, metric.dynamicRange)
cache.get(key).map(previousValue => {
previousValue.add(metric.distribution)
}).orElse {
val distributionAccumulator = new DistributionAccumulator(key.dynamicRange)
distributionAccumulator.add(metric.distribution)
cache.put(key, distributionAccumulator)
}
}
private def clearAccumulatedData(): Unit = {
histograms.clear()
rangeSamplers.clear()
counters.clear()
gauges.clear()
}
}
object PeriodSnapshotAccumulator {
case class MetricValueKey(name: String, tags: Tags, unit: MeasurementUnit)
case class MetricDistributionKey(name: String, tags: Tags, unit: MeasurementUnit, dynamicRange: DynamicRange)
}
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