All Downloads are FREE. Search and download functionalities are using the official Maven repository.

com.codahale.metrics.SlidingTimeWindowMovingAverages Maven / Gradle / Ivy

Go to download

Metrics is a Java library which gives you unparalleled insight into what your code does in production. Metrics provides a powerful toolkit of ways to measure the behavior of critical components in your production environment.

There is a newer version: 4.2.28
Show newest version
package com.codahale.metrics;

import java.time.Duration;
import java.time.Instant;
import java.util.ArrayList;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.atomic.LongAdder;

/**
 * A triple of simple moving average rates (one, five and fifteen minutes rates) as needed by {@link Meter}.
 * 

* The averages are unweighted, i.e. they include strictly only the events in the * sliding time window, every event having the same weight. Unlike the * the more widely used {@link ExponentialMovingAverages} implementation, * with this class the moving average rate drops immediately to zero if the last * marked event is older than the time window. *

* A {@link Meter} with {@link SlidingTimeWindowMovingAverages} works similarly to * a {@link Histogram} with an {@link SlidingTimeWindowArrayReservoir}, but as a Meter * needs to keep track only of the count of events (not the events itself), the memory * overhead is much smaller. SlidingTimeWindowMovingAverages uses buckets with just one * counter to accumulate the number of events (one bucket per seconds, giving 900 buckets * for the 15 minutes time window). */ public class SlidingTimeWindowMovingAverages implements MovingAverages { private static final long TIME_WINDOW_DURATION_MINUTES = 15; private static final long TICK_INTERVAL = TimeUnit.SECONDS.toNanos(1); private static final Duration TIME_WINDOW_DURATION = Duration.ofMinutes(TIME_WINDOW_DURATION_MINUTES); // package private for the benefit of the unit test static final int NUMBER_OF_BUCKETS = (int) (TIME_WINDOW_DURATION.toNanos() / TICK_INTERVAL); private final AtomicLong lastTick; private final Clock clock; /** * One counter per time bucket/slot (i.e. per second, see TICK_INTERVAL) for the entire * time window (i.e. 15 minutes, see TIME_WINDOW_DURATION_MINUTES) */ private ArrayList buckets; /** * Index into buckets, pointing at the bucket containing the oldest counts */ private int oldestBucketIndex; /** * Index into buckets, pointing at the bucket with the count for the current time (tick) */ private int currentBucketIndex; /** * Instant at creation time of the time window. Used to calculate the currentBucketIndex * for the instant of a given tick (instant modulo time window duration) */ private final Instant bucketBaseTime; /** * Instant of the bucket with index oldestBucketIndex */ Instant oldestBucketTime; /** * Creates a new {@link SlidingTimeWindowMovingAverages}. */ public SlidingTimeWindowMovingAverages() { this(Clock.defaultClock()); } /** * Creates a new {@link SlidingTimeWindowMovingAverages}. * * @param clock the clock to use for the meter ticks */ public SlidingTimeWindowMovingAverages(Clock clock) { this.clock = clock; final long startTime = clock.getTick(); lastTick = new AtomicLong(startTime); buckets = new ArrayList<>(NUMBER_OF_BUCKETS); for (int i = 0; i < NUMBER_OF_BUCKETS; i++) { buckets.add(new LongAdder()); } bucketBaseTime = Instant.ofEpochSecond(0L, startTime); oldestBucketTime = bucketBaseTime; oldestBucketIndex = 0; currentBucketIndex = 0; } @Override public void update(long n) { buckets.get(currentBucketIndex).add(n); } @Override public void tickIfNecessary() { final long oldTick = lastTick.get(); final long newTick = clock.getTick(); final long age = newTick - oldTick; if (age >= TICK_INTERVAL) { // - the newTick doesn't fall into the same slot as the oldTick anymore // - newLastTick is the lower border time of the new currentBucketIndex slot final long newLastTick = newTick - age % TICK_INTERVAL; if (lastTick.compareAndSet(oldTick, newLastTick)) { Instant currentInstant = Instant.ofEpochSecond(0L, newLastTick); currentBucketIndex = normalizeIndex(calculateIndexOfTick(currentInstant)); cleanOldBuckets(currentInstant); } } } @Override public double getM15Rate() { return getMinuteRate(15); } @Override public double getM5Rate() { return getMinuteRate(5); } @Override public double getM1Rate() { return getMinuteRate(1); } private double getMinuteRate(int minutes) { Instant now = Instant.ofEpochSecond(0L, lastTick.get()); return sumBuckets(now, (int) (TimeUnit.MINUTES.toNanos(minutes) / TICK_INTERVAL)); } int calculateIndexOfTick(Instant tickTime) { return (int) (Duration.between(bucketBaseTime, tickTime).toNanos() / TICK_INTERVAL); } int normalizeIndex(int index) { int mod = index % NUMBER_OF_BUCKETS; return mod >= 0 ? mod : mod + NUMBER_OF_BUCKETS; } private void cleanOldBuckets(Instant currentTick) { int newOldestIndex; Instant oldestStillNeededTime = currentTick.minus(TIME_WINDOW_DURATION).plusNanos(TICK_INTERVAL); Instant youngestNotInWindow = oldestBucketTime.plus(TIME_WINDOW_DURATION); if (oldestStillNeededTime.isAfter(youngestNotInWindow)) { // there was no update() call for more than two whole TIME_WINDOW_DURATION newOldestIndex = oldestBucketIndex; oldestBucketTime = currentTick; } else if (oldestStillNeededTime.isAfter(oldestBucketTime)) { newOldestIndex = normalizeIndex(calculateIndexOfTick(oldestStillNeededTime)); oldestBucketTime = oldestStillNeededTime; } else { return; } cleanBucketRange(oldestBucketIndex, newOldestIndex); oldestBucketIndex = newOldestIndex; } private void cleanBucketRange(int fromIndex, int toIndex) { if (fromIndex < toIndex) { for (int i = fromIndex; i < toIndex; i++) { buckets.get(i).reset(); } } else { for (int i = fromIndex; i < NUMBER_OF_BUCKETS; i++) { buckets.get(i).reset(); } for (int i = 0; i < toIndex; i++) { buckets.get(i).reset(); } } } private long sumBuckets(Instant toTime, int numberOfBuckets) { // increment toIndex to include the current bucket into the sum int toIndex = normalizeIndex(calculateIndexOfTick(toTime) + 1); int fromIndex = normalizeIndex(toIndex - numberOfBuckets); LongAdder adder = new LongAdder(); if (fromIndex < toIndex) { buckets.stream() .skip(fromIndex) .limit(toIndex - fromIndex) .mapToLong(LongAdder::longValue) .forEach(adder::add); } else { buckets.stream().limit(toIndex).mapToLong(LongAdder::longValue).forEach(adder::add); buckets.stream().skip(fromIndex).mapToLong(LongAdder::longValue).forEach(adder::add); } long retval = adder.longValue(); return retval; } }





© 2015 - 2024 Weber Informatics LLC | Privacy Policy