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author | Ivan Topolnjak <ivantopo@gmail.com> | 2017-04-24 13:54:40 +0200 |
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committer | Ivan Topolnjak <ivantopo@gmail.com> | 2017-04-24 13:54:40 +0200 |
commit | 4d828e1a3195e55365c865aa3a78af9668742643 (patch) | |
tree | 07fff2683933c96297a8ba577bbdc89888da16e1 /kamon-core/src/legacy-main/scala/kamon/metric/instrument/Histogram.scala | |
parent | 469c11dc1ddb140f407a33f48033e533bf60611c (diff) | |
download | Kamon-4d828e1a3195e55365c865aa3a78af9668742643.tar.gz Kamon-4d828e1a3195e55365c865aa3a78af9668742643.tar.bz2 Kamon-4d828e1a3195e55365c865aa3a78af9668742643.zip |
Prepare for the major cleanup
Moved all the original files from src/main to src/legacy-main, same with test files. Also
removed the autoweave module, examples and bench as I'm planning to have them in separate
repositories.
Diffstat (limited to 'kamon-core/src/legacy-main/scala/kamon/metric/instrument/Histogram.scala')
-rw-r--r-- | kamon-core/src/legacy-main/scala/kamon/metric/instrument/Histogram.scala | 331 |
1 files changed, 331 insertions, 0 deletions
diff --git a/kamon-core/src/legacy-main/scala/kamon/metric/instrument/Histogram.scala b/kamon-core/src/legacy-main/scala/kamon/metric/instrument/Histogram.scala new file mode 100644 index 00000000..399f0880 --- /dev/null +++ b/kamon-core/src/legacy-main/scala/kamon/metric/instrument/Histogram.scala @@ -0,0 +1,331 @@ +/* + * ========================================================================================= + * Copyright © 2013 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.instrument + +import java.nio.LongBuffer + +import kamon.metric.instrument.Histogram.{DynamicRange, Snapshot} +import kamon.util.logger.LazyLogger +import org.HdrHistogram.ModifiedAtomicHistogram + +trait Histogram extends Instrument { + type SnapshotType = Histogram.Snapshot + + def record(value: Long): Unit + def record(value: Long, count: Long): Unit +} + +object Histogram { + + /** + * Scala API: + * + * Create a new High Dynamic Range Histogram ([[kamon.metric.instrument.HdrHistogram]]) using the given + * [[kamon.metric.instrument.Histogram.DynamicRange]]. + */ + def apply(dynamicRange: DynamicRange): Histogram = new HdrHistogram(dynamicRange) + + /** + * Java API: + * + * Create a new High Dynamic Range Histogram ([[kamon.metric.instrument.HdrHistogram]]) using the given + * [[kamon.metric.instrument.Histogram.DynamicRange]]. + */ + def create(dynamicRange: DynamicRange): Histogram = apply(dynamicRange) + + /** + * DynamicRange is a configuration object used to supply range and precision configuration to a + * [[kamon.metric.instrument.HdrHistogram]]. See the [[http://hdrhistogram.github.io/HdrHistogram/ HdrHistogram website]] + * for more details on how it works and the effects of these configuration values. + * + * @param lowestDiscernibleValue + * The lowest value that can be discerned (distinguished from 0) by the histogram.Must be a positive integer that + * is >= 1. May be internally rounded down to nearest power of 2. + * @param highestTrackableValue + * The highest value to be tracked by the histogram. Must be a positive integer that is >= (2 * lowestDiscernibleValue). + * Must not be larger than (Long.MAX_VALUE/2). + * @param precision + * The number of significant decimal digits to which the histogram will maintain value resolution and separation. + * Must be a non-negative integer between 1 and 3. + */ + case class DynamicRange(lowestDiscernibleValue: Long, highestTrackableValue: Long, precision: Int) + + trait Record { + def level: Long + def count: Long + + private[kamon] def rawCompactRecord: Long + } + + case class MutableRecord(var level: Long, var count: Long) extends Record { + var rawCompactRecord: Long = 0L + } + + trait Snapshot extends InstrumentSnapshot { + + def isEmpty: Boolean = numberOfMeasurements == 0 + def numberOfMeasurements: Long + def min: Long + def max: Long + def sum: Long + def percentile(percentile: Double): Long + def recordsIterator: Iterator[Record] + def merge(that: InstrumentSnapshot, context: CollectionContext): InstrumentSnapshot + def merge(that: Histogram.Snapshot, context: CollectionContext): Histogram.Snapshot + + override def scale(from: UnitOfMeasurement, to: UnitOfMeasurement): Histogram.Snapshot = + new ScaledSnapshot(from, to, this) + } + + class ScaledSnapshot(from: UnitOfMeasurement, to: UnitOfMeasurement, snapshot: Snapshot) extends Snapshot { + private def doScale(v: Long) = from.tryScale(to)(v).toLong + override def numberOfMeasurements: Long = snapshot.numberOfMeasurements + + override def max: Long = doScale(snapshot.max) + + override def merge(that: InstrumentSnapshot, context: CollectionContext): InstrumentSnapshot = snapshot.merge(that, context) + + override def merge(that: Snapshot, context: CollectionContext): Snapshot = snapshot.merge(that, context) + + override def percentile(percentile: Double): Long = doScale(snapshot.percentile(percentile)) + + override def min: Long = doScale(snapshot.min) + + override def sum: Long = doScale(snapshot.sum) + + override def recordsIterator: Iterator[Record] = { + snapshot.recordsIterator.map(record ⇒ new Record { + override def count: Long = record.count + + override def level: Long = doScale(record.level) + + override private[kamon] def rawCompactRecord: Long = record.rawCompactRecord + }) + } + + override def scale(from: UnitOfMeasurement, to: UnitOfMeasurement): Histogram.Snapshot = + if (this.from == from && this.to == to) this else super.scale(from, to) + } + + object Snapshot { + val empty = new Snapshot { + override def min: Long = 0L + override def max: Long = 0L + override def sum: Long = 0L + override def percentile(percentile: Double): Long = 0L + override def recordsIterator: Iterator[Record] = Iterator.empty + override def merge(that: InstrumentSnapshot, context: CollectionContext): InstrumentSnapshot = that + override def merge(that: Histogram.Snapshot, context: CollectionContext): Histogram.Snapshot = that + override def numberOfMeasurements: Long = 0L + override def scale(from: UnitOfMeasurement, to: UnitOfMeasurement): Histogram.Snapshot = this + } + } +} + +object HdrHistogram { + private val log = LazyLogger(classOf[HdrHistogram]) +} + +/** + * This implementation is meant to be used for real time data collection where data snapshots are taken often over time. + * The collect(..) operation extracts all the recorded values from the histogram and resets the counts, but still + * leave it in a consistent state even in the case of concurrent modification while the snapshot is being taken. + */ +class HdrHistogram(dynamicRange: DynamicRange) extends ModifiedAtomicHistogram( + dynamicRange.lowestDiscernibleValue, + dynamicRange.highestTrackableValue, dynamicRange.precision +) with Histogram { + import HdrHistogram.log + + def record(value: Long): Unit = tryRecord(value, 1L) + + def record(value: Long, count: Long): Unit = tryRecord(value, count) + + private def tryRecord(value: Long, count: Long): Unit = { + try { + recordValueWithCount(value, count) + } catch { + case anyException: Throwable ⇒ + log.warn(s"Failed to store value $value in HdrHistogram, please review your range configuration.", anyException) + } + } + + def collect(context: CollectionContext): Histogram.Snapshot = { + import context.buffer + buffer.clear() + val nrOfMeasurements = writeSnapshotTo(buffer) + + buffer.flip() + + val measurementsArray = Array.ofDim[Long](buffer.limit()) + buffer.get(measurementsArray, 0, measurementsArray.length) + new CompactHdrSnapshot(nrOfMeasurements, measurementsArray, protectedUnitMagnitude(), protectedSubBucketHalfCount(), protectedSubBucketHalfCountMagnitude()) + } + + def getCounts = countsArray().length() + + def cleanup: Unit = {} + + private def writeSnapshotTo(buffer: LongBuffer): Long = { + val counts = countsArray() + val countsLength = counts.length() + + var nrOfMeasurements = 0L + var index = 0L + while (index < countsLength) { + val countAtIndex = counts.getAndSet(index.toInt, 0L) + + if (countAtIndex > 0) { + buffer.put(CompactHdrSnapshot.compactRecord(index, countAtIndex)) + nrOfMeasurements += countAtIndex + } + + index += 1 + } + nrOfMeasurements + } +} + +case class CompactHdrSnapshot(numberOfMeasurements: Long, compactRecords: Array[Long], unitMagnitude: Int, + subBucketHalfCount: Int, subBucketHalfCountMagnitude: Int) extends Histogram.Snapshot { + + def min: Long = if (compactRecords.length == 0) 0 else levelFromCompactRecord(compactRecords(0)) + def max: Long = if (compactRecords.length == 0) 0 else levelFromCompactRecord(compactRecords(compactRecords.length - 1)) + def sum: Long = recordsIterator.foldLeft(0L)((a, r) ⇒ a + (r.count * r.level)) + + def percentile(p: Double): Long = { + val records = recordsIterator + val threshold = numberOfMeasurements * (p / 100D) + var countToCurrentLevel = 0L + var percentileLevel = 0L + + while (countToCurrentLevel < threshold && records.hasNext) { + val record = records.next() + countToCurrentLevel += record.count + percentileLevel = record.level + } + + percentileLevel + } + + def merge(that: Histogram.Snapshot, context: CollectionContext): Snapshot = + merge(that.asInstanceOf[InstrumentSnapshot], context) + + def merge(that: InstrumentSnapshot, context: CollectionContext): Histogram.Snapshot = that match { + case thatSnapshot: CompactHdrSnapshot ⇒ + if (thatSnapshot.isEmpty) this else if (this.isEmpty) thatSnapshot else { + import context.buffer + buffer.clear() + + val selfIterator = recordsIterator + val thatIterator = thatSnapshot.recordsIterator + var thatCurrentRecord: Histogram.Record = null + var mergedNumberOfMeasurements = 0L + + def nextOrNull(iterator: Iterator[Histogram.Record]): Histogram.Record = if (iterator.hasNext) iterator.next() else null + def addToBuffer(compactRecord: Long): Unit = { + mergedNumberOfMeasurements += countFromCompactRecord(compactRecord) + buffer.put(compactRecord) + } + + while (selfIterator.hasNext) { + val selfCurrentRecord = selfIterator.next() + + // Advance that to no further than the level of selfCurrentRecord + thatCurrentRecord = if (thatCurrentRecord == null) nextOrNull(thatIterator) else thatCurrentRecord + while (thatCurrentRecord != null && thatCurrentRecord.level < selfCurrentRecord.level) { + addToBuffer(thatCurrentRecord.rawCompactRecord) + thatCurrentRecord = nextOrNull(thatIterator) + } + + // Include the current record of self and optionally merge if has the same level as thatCurrentRecord + if (thatCurrentRecord != null && thatCurrentRecord.level == selfCurrentRecord.level) { + addToBuffer(mergeCompactRecords(thatCurrentRecord.rawCompactRecord, selfCurrentRecord.rawCompactRecord)) + thatCurrentRecord = nextOrNull(thatIterator) + } else { + addToBuffer(selfCurrentRecord.rawCompactRecord) + } + } + + // Include everything that might have been left from that + if (thatCurrentRecord != null) addToBuffer(thatCurrentRecord.rawCompactRecord) + while (thatIterator.hasNext) { + addToBuffer(thatIterator.next().rawCompactRecord) + } + + buffer.flip() + val compactRecords = Array.ofDim[Long](buffer.limit()) + buffer.get(compactRecords) + + new CompactHdrSnapshot(mergedNumberOfMeasurements, compactRecords, unitMagnitude, subBucketHalfCount, subBucketHalfCountMagnitude) + } + + case other ⇒ + sys.error(s"Cannot merge a CompactHdrSnapshot with the incompatible [${other.getClass.getName}] type.") + + } + + @inline private def mergeCompactRecords(left: Long, right: Long): Long = { + val index = left >> 48 + val leftCount = countFromCompactRecord(left) + val rightCount = countFromCompactRecord(right) + + CompactHdrSnapshot.compactRecord(index, leftCount + rightCount) + } + + @inline private def levelFromCompactRecord(compactRecord: Long): Long = { + val countsArrayIndex = (compactRecord >> 48).toInt + var bucketIndex: Int = (countsArrayIndex >> subBucketHalfCountMagnitude) - 1 + var subBucketIndex: Int = (countsArrayIndex & (subBucketHalfCount - 1)) + subBucketHalfCount + if (bucketIndex < 0) { + subBucketIndex -= subBucketHalfCount + bucketIndex = 0 + } + + subBucketIndex.toLong << (bucketIndex + unitMagnitude) + } + + @inline private def countFromCompactRecord(compactRecord: Long): Long = + compactRecord & CompactHdrSnapshot.CompactRecordCountMask + + def recordsIterator: Iterator[Histogram.Record] = new Iterator[Histogram.Record] { + var currentIndex = 0 + val mutableRecord = Histogram.MutableRecord(0, 0) + + override def hasNext: Boolean = currentIndex < compactRecords.length + + override def next(): Histogram.Record = { + if (hasNext) { + val measurement = compactRecords(currentIndex) + mutableRecord.rawCompactRecord = measurement + mutableRecord.level = levelFromCompactRecord(measurement) + mutableRecord.count = countFromCompactRecord(measurement) + currentIndex += 1 + + mutableRecord + } else { + throw new IllegalStateException("The iterator has already been consumed.") + } + } + } +} + +object CompactHdrSnapshot { + val CompactRecordCountMask = 0xFFFFFFFFFFFFL + + def compactRecord(index: Long, count: Long): Long = (index << 48) | count +} |