001 /**
002 * Licensed to the Apache Software Foundation (ASF) under one
003 * or more contributor license agreements. See the NOTICE file
004 * distributed with this work for additional information
005 * regarding copyright ownership. The ASF licenses this file
006 * to you under the Apache License, Version 2.0 (the
007 * "License"); you may not use this file except in compliance
008 * with the License. You may obtain a copy of the License at
009 *
010 * http://www.apache.org/licenses/LICENSE-2.0
011 *
012 * Unless required by applicable law or agreed to in writing, software
013 * distributed under the License is distributed on an "AS IS" BASIS,
014 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
015 * See the License for the specific language governing permissions and
016 * limitations under the License.
017 */
018
019 package org.apache.hadoop.metrics2.util;
020
021 import org.apache.hadoop.classification.InterfaceAudience;
022
023 /**
024 * Helper to compute running sample stats
025 */
026 @InterfaceAudience.Private
027 public class SampleStat {
028 private final MinMax minmax = new MinMax();
029 private long numSamples = 0;
030 private double a0, a1, s0, s1;
031
032 /**
033 * Construct a new running sample stat
034 */
035 public SampleStat() {
036 a0 = s0 = 0.0;
037 }
038
039 public void reset() {
040 numSamples = 0;
041 a0 = s0 = 0.0;
042 minmax.reset();
043 }
044
045 // We want to reuse the object, sometimes.
046 void reset(long numSamples, double a0, double a1, double s0, double s1,
047 MinMax minmax) {
048 this.numSamples = numSamples;
049 this.a0 = a0;
050 this.a1 = a1;
051 this.s0 = s0;
052 this.s1 = s1;
053 this.minmax.reset(minmax);
054 }
055
056 /**
057 * Copy the values to other (saves object creation and gc.)
058 * @param other the destination to hold our values
059 */
060 public void copyTo(SampleStat other) {
061 other.reset(numSamples, a0, a1, s0, s1, minmax);
062 }
063
064 /**
065 * Add a sample the running stat.
066 * @param x the sample number
067 * @return self
068 */
069 public SampleStat add(double x) {
070 minmax.add(x);
071 return add(1, x);
072 }
073
074 /**
075 * Add some sample and a partial sum to the running stat.
076 * Note, min/max is not evaluated using this method.
077 * @param nSamples number of samples
078 * @param x the partial sum
079 * @return self
080 */
081 public SampleStat add(long nSamples, double x) {
082 numSamples += nSamples;
083
084 if (numSamples == 1) {
085 a0 = a1 = x;
086 s0 = 0.0;
087 }
088 else {
089 // The Welford method for numerical stability
090 a1 = a0 + (x - a0) / numSamples;
091 s1 = s0 + (x - a0) * (x - a1);
092 a0 = a1;
093 s0 = s1;
094 }
095 return this;
096 }
097
098 /**
099 * @return the total number of samples
100 */
101 public long numSamples() {
102 return numSamples;
103 }
104
105 /**
106 * @return the arithmetic mean of the samples
107 */
108 public double mean() {
109 return numSamples > 0 ? a1 : 0.0;
110 }
111
112 /**
113 * @return the variance of the samples
114 */
115 public double variance() {
116 return numSamples > 1 ? s1 / (numSamples - 1) : 0.0;
117 }
118
119 /**
120 * @return the standard deviation of the samples
121 */
122 public double stddev() {
123 return Math.sqrt(variance());
124 }
125
126 /**
127 * @return the minimum value of the samples
128 */
129 public double min() {
130 return minmax.min();
131 }
132
133 /**
134 * @return the maximum value of the samples
135 */
136 public double max() {
137 return minmax.max();
138 }
139
140 /**
141 * Helper to keep running min/max
142 */
143 @SuppressWarnings("PublicInnerClass")
144 public static class MinMax {
145
146 // Float.MAX_VALUE is used rather than Double.MAX_VALUE, even though the
147 // min and max variables are of type double.
148 // Float.MAX_VALUE is big enough, and using Double.MAX_VALUE makes
149 // Ganglia core due to buffer overflow.
150 // The same reasoning applies to the MIN_VALUE counterparts.
151 static final double DEFAULT_MIN_VALUE = Float.MAX_VALUE;
152 static final double DEFAULT_MAX_VALUE = Float.MIN_VALUE;
153
154 private double min = DEFAULT_MIN_VALUE;
155 private double max = DEFAULT_MAX_VALUE;
156
157 public void add(double value) {
158 if (value > max) max = value;
159 if (value < min) min = value;
160 }
161
162 public double min() { return min; }
163 public double max() { return max; }
164
165 public void reset() {
166 min = DEFAULT_MIN_VALUE;
167 max = DEFAULT_MAX_VALUE;
168 }
169
170 public void reset(MinMax other) {
171 min = other.min();
172 max = other.max();
173 }
174 }
175 }