/* * 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.pig.test; import static org.junit.Assert.assertTrue; import java.util.ArrayList; import java.util.Collections; import java.util.Iterator; import java.util.List; import java.util.Map; import java.util.Random; import org.apache.pig.data.BagFactory; import org.apache.pig.data.DataBag; import org.apache.pig.data.InternalMap; import org.apache.pig.data.NonSpillableDataBag; import org.apache.pig.data.Tuple; import org.apache.pig.data.TupleFactory; import org.apache.pig.impl.builtin.FindQuantiles; import org.junit.Test; public class TestFindQuantiles { private static TupleFactory tFact = TupleFactory.getInstance(); private static final float epsilon = 0.0001f; @Test public void testFindQuantiles() throws Exception { final int numSamples = 97778; final int numReducers = 1009; float sum = getProbVecSum(numSamples, numReducers); System.out.println("sum: " + sum); assertTrue(sum > (1-epsilon) && sum < (1+epsilon)); } @Test public void testFindQuantiles2() throws Exception { final int numSamples = 30000; final int numReducers = 3000; float sum = getProbVecSum(numSamples, numReducers); System.out.println("sum: " + sum); assertTrue(sum > (1-epsilon) && sum < (1+epsilon)); } @Test public void testFindQuantilesRemainder() throws Exception { final int numSamples = 1900; final int numReducers = 300; DataBag samples = generateRandomSortedSamples(numSamples, 365); Map<String, Object> findQuantilesResult = getFindQuantilesResult(samples, numReducers); DataBag quantilesBag = (DataBag)findQuantilesResult.get(FindQuantiles.QUANTILES_LIST); Iterator<Tuple> iter = quantilesBag.iterator(); Tuple lastQuantile = null; while (iter.hasNext()) { lastQuantile = iter.next(); } int lastQuantileNum = (Integer)lastQuantile.get(0); int count = 0; iter = samples.iterator(); while (iter.hasNext()) { Tuple t = iter.next(); int num = (Integer)t.get(0); if (num >= lastQuantileNum) { count++; } } assertTrue((double)count/numSamples <= 1.0/365 + 0.001); } private float[] getProbVec(Tuple values) throws Exception { float[] probVec = new float[values.size()]; for(int i = 0; i < values.size(); i++) { probVec[i] = (Float)values.get(i); } return probVec; } private DataBag generateRandomSortedSamples(int numSamples, int max) throws Exception { Random rand = new Random(1000); List<Tuple> samples = new ArrayList<Tuple>(); for (int i=0; i<numSamples; i++) { Tuple t = tFact.newTuple(1); t.set(0, rand.nextInt(max)); samples.add(t); } Collections.sort(samples); return new NonSpillableDataBag(samples); } private DataBag generateUniqueSamples(int numSamples) throws Exception { DataBag samples = BagFactory.getInstance().newDefaultBag(); for (int i=0; i<numSamples; i++) { Tuple t = tFact.newTuple(1); t.set(0, new Integer(23)); samples.add(t); } return samples; } private Map<String, Object> getFindQuantilesResult(DataBag samples, int numReduceres) throws Exception { Tuple in = tFact.newTuple(2); in.set(0, new Integer(numReduceres)); in.set(1, samples); FindQuantiles fq = new FindQuantiles(); Map<String, Object> res = fq.exec(in); return res; } private float getProbVecSum(int numSamples, int numReduceres) throws Exception { DataBag samples = generateUniqueSamples(numSamples); Map<String, Object> res = getFindQuantilesResult(samples, numReduceres); InternalMap weightedPartsData = (InternalMap) res.get(FindQuantiles.WEIGHTED_PARTS); Iterator<Object> it = weightedPartsData.values().iterator(); float[] probVec = getProbVec((Tuple)it.next()); float sum = 0.0f; for (float f : probVec) { sum += f; } return sum; } }