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//
// ========================================================================
// 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());
}
}
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