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

org.eclipse.jetty.util.statistic.SampleStatistic Maven / Gradle / Ivy

Go to download

Ehcache is an open source, standards-based cache used to boost performance, offload the database and simplify scalability. Ehcache is robust, proven and full-featured and this has made it the most widely-used Java-based cache.

There is a newer version: 2.10.9.2
Show newest version
//
//  ========================================================================
//  Copyright (c) 1995-2018 Mort Bay Consulting Pty. Ltd.
//  ------------------------------------------------------------------------
//  All rights reserved. This program and the accompanying materials
//  are made available under the terms of the Eclipse Public License v1.0
//  and Apache License v2.0 which accompanies this distribution.
//
//      The Eclipse Public License is available at
//      http://www.eclipse.org/legal/epl-v10.html
//
//      The Apache License v2.0 is available at
//      http://www.opensource.org/licenses/apache2.0.php
//
//  You may elect to redistribute this code under either of these licenses.
//  ========================================================================
//

package org.eclipse.jetty.util.statistic;

import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.atomic.LongAccumulator;
import java.util.concurrent.atomic.LongAdder;

/**
 * 

Statistics on a sampled value.

*

Provides max, total, mean, count, variance, and standard deviation of continuous sequence of samples.

*

Calculates estimates of mean, variance, and standard deviation characteristics of a sample using a non synchronized * approximation of the on-line algorithm presented in Donald Knuth's Art of Computer Programming, Volume 2, * Semi numerical Algorithms, 3rd edition, page 232, Boston: Addison-Wesley. That cites a 1962 paper by B.P. Welford: * Note on a Method for Calculating Corrected Sums of Squares and Products

*

This algorithm is also described in Wikipedia in the section "Online algorithm": * Algorithms for calculating variance.

*/ public class SampleStatistic { private final LongAccumulator _max = new LongAccumulator(Math::max, 0L); private final AtomicLong _total = new AtomicLong(); private final AtomicLong _count = new AtomicLong(); private final LongAdder _totalVariance100 = new LongAdder(); /** * Resets the statistics. */ public void reset() { _max.reset(); _total.set(0); _count.set(0); _totalVariance100.reset(); } /** * Records a sample value. * * @param sample the value to record. */ public void record(long sample) { long total = _total.addAndGet(sample); long count = _count.incrementAndGet(); if (count > 1) { long mean10 = total * 10 / count; long delta10 = sample * 10 - mean10; _totalVariance100.add(delta10 * delta10); } _max.accumulate(sample); } /** * @param sample the value to record. * @deprecated use {@link #record(long)} instead */ @Deprecated public void set(long sample) { record(sample); } /** * @return the max value of the recorded samples */ public long getMax() { return _max.get(); } /** * @return the sum of all the recorded samples */ public long getTotal() { return _total.get(); } /** * @return the number of samples recorded */ public long getCount() { return _count.get(); } /** * @return the average value of the samples recorded, or zero if there are no samples */ public double getMean() { long count = getCount(); return count > 0 ? (double)_total.get() / _count.get() : 0.0D; } /** * @return the variance of the samples recorded, or zero if there are less than 2 samples */ public double getVariance() { long variance100 = _totalVariance100.sum(); long count = getCount(); return count > 1 ? variance100 / 100.0D / (count - 1) : 0.0D; } /** * @return the standard deviation of the samples recorded */ public double getStdDev() { return Math.sqrt(getVariance()); } @Override public String toString() { return String.format("%s@%x{count=%d,mean=%d,total=%d,stddev=%f}", getClass().getSimpleName(), hashCode(), getCount(), getMax(), getTotal(), getStdDev()); } }




© 2015 - 2024 Weber Informatics LLC | Privacy Policy