| /** |
| * 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 |
| * <p/> |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * <p/> |
| * 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.sink.timeline; |
| |
| import org.apache.commons.math3.analysis.interpolation.LinearInterpolator; |
| import org.apache.commons.math3.analysis.polynomials.PolynomialFunction; |
| import org.apache.commons.math3.analysis.polynomials.PolynomialSplineFunction; |
| |
| import java.util.HashMap; |
| import java.util.List; |
| import java.util.Map; |
| import java.util.TreeMap; |
| |
| public class PostProcessingUtil { |
| |
| /* |
| Helper function to interpolate missing data on a series. |
| */ |
| public static Map<Long, Double> interpolateMissingData(Map<Long, Double> metricValues, long expectedInterval) { |
| |
| if (metricValues == null) |
| return null; |
| |
| Long prevTime = null; |
| Double prevVal = null; |
| Map<Long, Double> interpolatedMetricValues = new TreeMap<Long, Double>(); |
| |
| for (Map.Entry<Long, Double> timeValueEntry : metricValues.entrySet()) { |
| Long currTime = timeValueEntry.getKey(); |
| Double currVal = timeValueEntry.getValue(); |
| |
| if (prevTime != null) { |
| Long stepTime = prevTime; |
| while ((currTime - stepTime) > expectedInterval) { |
| stepTime+=expectedInterval; |
| double interpolatedValue = interpolate(stepTime, |
| prevTime, prevVal, |
| currTime, currVal); |
| interpolatedMetricValues.put(stepTime, interpolatedValue); |
| } |
| } |
| |
| interpolatedMetricValues.put(currTime, currVal); |
| prevTime = currTime; |
| prevVal = currVal; |
| } |
| return interpolatedMetricValues; |
| } |
| |
| public static Double interpolate(Long t, Long t1, Double m1, |
| Long t2, Double m2) { |
| //Linear Interpolation : y = y0 + (y1 - y0) * ((x - x0) / (x1 - x0)) |
| if (m1 == null && m2 == null) { |
| return null; |
| } |
| |
| if (m1 == null) |
| return m2; |
| |
| if (m2 == null) |
| return m1; |
| |
| if (t1 == null || t2 == null) |
| return null; |
| |
| double slope = (m2 - m1) / (t2 - t1); |
| return m1 + slope * (t - t1); |
| } |
| |
| public static Map<Long, Double> interpolate(Map<Long, Double> valuesMap, List<Long> requiredTimestamps) { |
| |
| LinearInterpolator linearInterpolator = new LinearInterpolator(); |
| |
| if (valuesMap == null || valuesMap.isEmpty()) { |
| return null; |
| } |
| if (requiredTimestamps == null || requiredTimestamps.isEmpty()) { |
| return null; |
| } |
| |
| Map<Long, Double> interpolatedValuesMap = new HashMap<>(); |
| |
| if (valuesMap.size() == 1) { |
| //Just one value present in the window. Use that value to interpolate all required timestamps. |
| Double value = null; |
| for (Map.Entry<Long, Double> entry : valuesMap.entrySet()) { |
| value = entry.getValue(); |
| } |
| for (Long requiredTs : requiredTimestamps) { |
| interpolatedValuesMap.put(requiredTs, value); |
| } |
| return interpolatedValuesMap; |
| } |
| |
| double[] timestamps = new double[valuesMap.size()]; |
| double[] metrics = new double[valuesMap.size()]; |
| |
| int i = 0; |
| for (Map.Entry<Long, Double> entry : valuesMap.entrySet()) { |
| timestamps[i] = (double) entry.getKey(); |
| metrics[i++] = entry.getValue(); |
| } |
| |
| PolynomialSplineFunction function = linearInterpolator.interpolate(timestamps, metrics); |
| PolynomialFunction[] splines = function.getPolynomials(); |
| PolynomialFunction first = splines[0]; |
| |
| for (Long requiredTs : requiredTimestamps) { |
| |
| Double interpolatedValue = null; |
| if (timestampInRange(requiredTs, timestamps[0], timestamps[timestamps.length - 1])) { |
| /* |
| Interpolation Case |
| Required TS is within range of the set of values used for interpolation. |
| Hence, we can use library to get the interpolated value. |
| */ |
| interpolatedValue = function.value((double) requiredTs); |
| } else { |
| /* |
| Extrapolation Case |
| Required TS outside range of the set of values used for interpolation. |
| We will use the coefficients to make best effort extrapolation |
| y(x)= y1 + m * (x−x1) |
| where, m = (y2−y1)/(x2−x1) |
| */ |
| if (first.getCoefficients() != null && first.getCoefficients().length > 0) { |
| /* |
| y = c0 + c1x |
| where c0, c1 are coefficients |
| c1 will not be present if slope is zero. |
| */ |
| Double y1 = first.getCoefficients()[0]; |
| Double m = (first.getCoefficients().length > 1) ? first.getCoefficients()[1] : 0.0; |
| interpolatedValue = y1 + m * (requiredTs - timestamps[0]); |
| } |
| } |
| |
| if (interpolatedValue != null && interpolatedValue >= 0.0) { |
| interpolatedValuesMap.put(requiredTs, interpolatedValue); |
| } |
| } |
| return interpolatedValuesMap; |
| } |
| |
| private static boolean timestampInRange(Long timestamp, double left, double right) { |
| return (timestamp >= left && timestamp <= right); |
| } |
| |
| } |