--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/src/org/eclipse/jetty/util/statistic/SampleStatistic.java	Wed Sep 07 21:15:48 2016 -0600
@@ -0,0 +1,109 @@
+//
+//  ========================================================================
+//  Copyright (c) 1995-2014 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 org.eclipse.jetty.util.Atomics;
+
+
+/* ------------------------------------------------------------ */
+/**
+ * SampledStatistics
+ * <p>
+ * Provides max, total, mean, count, variance, and standard
+ * deviation of continuous sequence of samples.
+ * <p>
+ * 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,
+ * Seminumerical Algorithms, 3rd edition, page 232,
+ * Boston: Addison-Wesley. that cites a 1962 paper by B.P. Welford
+ * that can be found by following the link http://www.jstor.org/pss/1266577
+ * <p>
+ * This algorithm is also described in Wikipedia at
+ * http://en.wikipedia.org/w/index.php?title=Algorithms_for_calculating_variance&section=4#On-line_algorithm
+ */
+public class SampleStatistic
+{
+    protected final AtomicLong _max = new AtomicLong();
+    protected final AtomicLong _total = new AtomicLong();
+    protected final AtomicLong _count = new AtomicLong();
+    protected final AtomicLong _totalVariance100 = new AtomicLong();
+
+    public void reset()
+    {
+        _max.set(0);
+        _total.set(0);
+        _count.set(0);
+        _totalVariance100.set(0);
+    }
+
+    public void set(final 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.addAndGet(delta10*delta10);
+        }
+
+        Atomics.updateMax(_max, sample);
+    }
+
+    /**
+     * @return the max value
+     */
+    public long getMax()
+    {
+        return _max.get();
+    }
+
+    public long getTotal()
+    {
+        return _total.get();
+    }
+
+    public long getCount()
+    {
+        return _count.get();
+    }
+
+    public double getMean()
+    {
+        return (double)_total.get()/_count.get();
+    }
+
+    public double getVariance()
+    {
+        final long variance100 = _totalVariance100.get();
+        final long count = _count.get();
+
+        return count>1?((double)variance100)/100.0/(count-1):0.0;
+    }
+
+    public double getStdDev()
+    {
+        return Math.sqrt(getVariance());
+    }
+}