1 //
2 //  ========================================================================
3 //  Copyright (c) 1995-2014 Mort Bay Consulting Pty. Ltd.
4 //  ------------------------------------------------------------------------
5 //  All rights reserved. This program and the accompanying materials
6 //  are made available under the terms of the Eclipse Public License v1.0
7 //  and Apache License v2.0 which accompanies this distribution.
8 //
9 //      The Eclipse Public License is available at
10 //      http://www.eclipse.org/legal/epl-v10.html
11 //
12 //      The Apache License v2.0 is available at
13 //      http://www.opensource.org/licenses/apache2.0.php
14 //
15 //  You may elect to redistribute this code under either of these licenses.
16 //  ========================================================================
17 //
18 
19 package org.eclipse.jetty.util.statistic;
20 
21 import java.util.concurrent.atomic.AtomicLong;
22 
23 import org.eclipse.jetty.util.Atomics;
24 
25 
26 /* ------------------------------------------------------------ */
27 /**
28  * SampledStatistics
29  * <p>
30  * Provides max, total, mean, count, variance, and standard
31  * deviation of continuous sequence of samples.
32  * <p>
33  * Calculates estimates of mean, variance, and standard deviation
34  * characteristics of a sample using a non synchronized
35  * approximation of the on-line algorithm presented
36  * in Donald Knuth's Art of Computer Programming, Volume 2,
37  * Seminumerical Algorithms, 3rd edition, page 232,
38  * Boston: Addison-Wesley. that cites a 1962 paper by B.P. Welford
39  * that can be found by following the link http://www.jstor.org/pss/1266577
40  * <p>
41  * This algorithm is also described in Wikipedia at
42  * http://en.wikipedia.org/w/index.php?title=Algorithms_for_calculating_variance&section=4#On-line_algorithm
43  */
44 public class SampleStatistic
45 {
46     protected final AtomicLong _max = new AtomicLong();
47     protected final AtomicLong _total = new AtomicLong();
48     protected final AtomicLong _count = new AtomicLong();
49     protected final AtomicLong _totalVariance100 = new AtomicLong();
50 
reset()51     public void reset()
52     {
53         _max.set(0);
54         _total.set(0);
55         _count.set(0);
56         _totalVariance100.set(0);
57     }
58 
set(final long sample)59     public void set(final long sample)
60     {
61         long total = _total.addAndGet(sample);
62         long count = _count.incrementAndGet();
63 
64         if (count>1)
65         {
66             long mean10 = total*10/count;
67             long delta10 = sample*10 - mean10;
68             _totalVariance100.addAndGet(delta10*delta10);
69         }
70 
71         Atomics.updateMax(_max, sample);
72     }
73 
74     /**
75      * @return the max value
76      */
getMax()77     public long getMax()
78     {
79         return _max.get();
80     }
81 
getTotal()82     public long getTotal()
83     {
84         return _total.get();
85     }
86 
getCount()87     public long getCount()
88     {
89         return _count.get();
90     }
91 
getMean()92     public double getMean()
93     {
94         return (double)_total.get()/_count.get();
95     }
96 
getVariance()97     public double getVariance()
98     {
99         final long variance100 = _totalVariance100.get();
100         final long count = _count.get();
101 
102         return count>1?((double)variance100)/100.0/(count-1):0.0;
103     }
104 
getStdDev()105     public double getStdDev()
106     {
107         return Math.sqrt(getVariance());
108     }
109 }
110