| /* |
| * 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.sysds.runtime.compress.estim.sample; |
| |
| import org.apache.commons.math3.distribution.ChiSquaredDistribution; |
| import org.apache.sysds.runtime.compress.utils.Bitmap; |
| |
| public class ShlosserJackknifeEstimator { |
| |
| private final static double SHLOSSER_JACKKNIFE_ALPHA = 0.975; |
| |
| /** |
| * Peter J. Haas, Jeffrey F. Naughton, S. Seshadri, and Lynne Stokes. 1995. Sampling-Based Estimation of the Number |
| * of Distinct Values of an Attribute. VLDB'95, Section 5.2, recommended estimator by the authors |
| * |
| * @param ubm The Uncompressed Bitmap containing the data from the sample |
| * @param nRows The original number of rows in the entire input |
| * @param sampleSize The number of rows in the sample |
| * @return an estimation of number of distinct values. |
| */ |
| @SuppressWarnings("unused") |
| private static int shlosserJackknifeEstimator(Bitmap ubm, int nRows, int sampleSize) { |
| int numVals = ubm.getNumValues(); |
| CriticalValue cv = computeCriticalValue(sampleSize); |
| |
| // uniformity chi-square test |
| double nBar = ((double) sampleSize) / numVals; |
| // test-statistic |
| double u = 0; |
| for(int i = 0; i < numVals; i++) { |
| u += Math.pow(ubm.getNumOffsets(i) - nBar, 2); |
| } |
| u /= nBar; |
| if(sampleSize != cv.usedSampleSize) |
| computeCriticalValue(sampleSize); |
| if(u < cv.uniformityCriticalValue) // uniform |
| return SmoothedJackknifeEstimator.get(ubm, nRows, sampleSize); |
| else |
| return ShlosserEstimator.get(ubm, nRows, sampleSize); |
| } |
| |
| private static CriticalValue computeCriticalValue(int sampleSize) { |
| ChiSquaredDistribution chiSqr = new ChiSquaredDistribution(sampleSize - 1); |
| return new CriticalValue(chiSqr.inverseCumulativeProbability(SHLOSSER_JACKKNIFE_ALPHA), sampleSize); |
| } |
| |
| /* |
| * In the shlosserSmoothedJackknifeEstimator as long as the sample size did not change, we will have the same |
| * critical value each time the estimator is used (given that alpha is the same). We cache the critical value to |
| * avoid recomputing it in each call. |
| */ |
| private static class CriticalValue { |
| public final double uniformityCriticalValue; |
| public final int usedSampleSize; |
| |
| public CriticalValue(double cv, int size) { |
| uniformityCriticalValue = cv; |
| usedSampleSize = size; |
| } |
| } |
| } |