| /** |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you under the Apache License, Version 2.0 (the |
| * "License"); you may not use this file except in compliance |
| * with the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| |
| package org.apache.hadoop.metrics2.util; |
| |
| /** |
| * Helper to compute running sample stats |
| */ |
| public class SampleStat { |
| |
| private final MinMax minmax = new MinMax(); |
| private long numSamples = 0; |
| private double a0, a1, s0, s1; |
| |
| /** |
| * Construct a new running sample stat |
| */ |
| public SampleStat() { |
| a0 = s0 = 0.0; |
| } |
| |
| public void reset() { |
| numSamples = 0; |
| a0 = s0 = 0.0; |
| minmax.reset(); |
| } |
| |
| // We want to reuse the object, sometimes. |
| void reset(long numSamples, double a0, double a1, double s0, double s1, |
| MinMax minmax) { |
| this.numSamples = numSamples; |
| this.a0 = a0; |
| this.a1 = a1; |
| this.s0 = s0; |
| this.s1 = s1; |
| this.minmax.reset(minmax); |
| } |
| |
| /** |
| * Copy the values to other (saves object creation and gc.) |
| * @param other the destination to hold our values |
| */ |
| public void copyTo(SampleStat other) { |
| other.reset(numSamples, a0, a1, s0, s1, minmax); |
| } |
| |
| /** |
| * Add a sample the running stat. |
| * @param x the sample number |
| * @return self |
| */ |
| public SampleStat add(double x) { |
| minmax.add(x); |
| return add(1, x); |
| } |
| |
| /** |
| * Add some sample and a partial sum to the running stat. |
| * Note, min/max is not evaluated using this method. |
| * @param nSamples number of samples |
| * @param x the partial sum |
| * @return self |
| */ |
| public SampleStat add(long nSamples, double x) { |
| numSamples += nSamples; |
| |
| if (numSamples == 1) { |
| a0 = a1 = x; |
| s0 = 0.0; |
| } |
| else { |
| // The Welford method for numerical stability |
| a1 = a0 + (x - a0) / numSamples; |
| s1 = s0 + (x - a0) * (x - a1); |
| a0 = a1; |
| s0 = s1; |
| } |
| return this; |
| } |
| |
| /** |
| * @return the total number of samples |
| */ |
| public long numSamples() { |
| return numSamples; |
| } |
| |
| /** |
| * @return the arithmetic mean of the samples |
| */ |
| public double mean() { |
| return numSamples > 0 ? a1 : 0.0; |
| } |
| |
| /** |
| * @return the variance of the samples |
| */ |
| public double variance() { |
| return numSamples > 1 ? s1 / (numSamples - 1) : 0.0; |
| } |
| |
| /** |
| * @return the standard deviation of the samples |
| */ |
| public double stddev() { |
| return Math.sqrt(variance()); |
| } |
| |
| /** |
| * @return the minimum value of the samples |
| */ |
| public double min() { |
| return minmax.min(); |
| } |
| |
| /** |
| * @return the maximum value of the samples |
| */ |
| public double max() { |
| return minmax.max(); |
| } |
| |
| /** |
| * Helper to keep running min/max |
| */ |
| @SuppressWarnings("PublicInnerClass") |
| public static class MinMax { |
| |
| private double min = Double.MAX_VALUE; |
| private double max = Double.MIN_VALUE; |
| |
| public void add(double value) { |
| if (value > max) max = value; |
| if (value < min) min = value; |
| } |
| |
| public double min() { return min; } |
| public double max() { return max; } |
| |
| public void reset() { |
| min = Double.MAX_VALUE; |
| max = Double.MIN_VALUE; |
| } |
| |
| public void reset(MinMax other) { |
| min = other.min(); |
| max = other.max(); |
| } |
| |
| } |
| |
| } |