/* * INESC-ID, Instituto de Engenharia de Sistemas e Computadores Investigação e Desevolvimento em Lisboa * Copyright 2013 INESC-ID and/or its affiliates and other * contributors as indicated by the @author tags. All rights reserved. * See the copyright.txt in the distribution for a full listing of * individual contributors. * * This is free software; you can redistribute it and/or modify it * under the terms of the GNU Lesser General Public License as * published by the Free Software Foundation; either version 3.0 of * the License, or (at your option) any later version. * * This software is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this software; if not, write to the Free * Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA * 02110-1301 USA, or see the FSF site: http://www.fsf.org. */ package org.infinispan.dataplacement.c50; import org.infinispan.dataplacement.c50.keyfeature.Feature; import org.infinispan.dataplacement.c50.keyfeature.FeatureValue; import org.infinispan.dataplacement.c50.keyfeature.KeyFeatureManager; import org.infinispan.dataplacement.c50.lookup.BloomFilter; import org.infinispan.dataplacement.c50.tree.DecisionTree; import org.infinispan.dataplacement.lookup.ObjectLookup; import org.infinispan.dataplacement.stats.IncrementableLong; import java.util.LinkedList; import java.util.List; import java.util.Map; /** * the object lookup implementation for the Bloom Filter + Machine Learner technique * * @author Pedro Ruivo * @since 5.2 */ public class C50MLObjectLookup implements ObjectLookup { private final BloomFilter bloomFilter; private final DecisionTree[] decisionTreeArray; private transient KeyFeatureManager keyFeatureManager; public C50MLObjectLookup(int numberOfOwners, BloomFilter bloomFilter) { this.bloomFilter = bloomFilter; decisionTreeArray = new DecisionTree[numberOfOwners]; } public void setDecisionTreeList(int index, DecisionTree decisionTree) { decisionTreeArray[index] = decisionTree; } public void setKeyFeatureManager(KeyFeatureManager keyFeatureManager) { this.keyFeatureManager = keyFeatureManager; } public BloomFilter getBloomFilter() { return bloomFilter; } public DecisionTree[] getDecisionTreeArray() { return decisionTreeArray; } @Override public List<Integer> query(Object key) { if (!bloomFilter.contains(key)) { return null; } else { Map<Feature, FeatureValue> keyFeatures = keyFeatureManager.getFeatures(key); List<Integer> owners = new LinkedList<Integer>(); for (DecisionTree tree : decisionTreeArray) { owners.add(tree.query(keyFeatures)); } return owners; } } @Override public List<Integer> queryWithProfiling(Object key, IncrementableLong[] phaseDurations) { long ts0 = System.nanoTime(); if (!bloomFilter.contains(key)) { long ts1 = System.nanoTime(); if (phaseDurations.length > 0) { phaseDurations[0].add(ts1 - ts0); } return null; } else { long ts1 = System.nanoTime(); List<Integer> owners = new LinkedList<Integer>(); Map<Feature, FeatureValue> keyFeatures = keyFeatureManager.getFeatures(key); long ts2 = System.nanoTime(); for (DecisionTree tree : decisionTreeArray) { owners.add(tree.query(keyFeatures)); } long ts3 = System.nanoTime(); if (phaseDurations.length > 2) { phaseDurations[0].add(ts1 - ts0); phaseDurations[1].add(ts2 - ts1); phaseDurations[2].add(ts3 - ts2); } else if (phaseDurations.length > 1) { phaseDurations[0].add(ts1 - ts0); phaseDurations[1].add(ts2 - ts1); } else if (phaseDurations.length > 0) { phaseDurations[0].add(ts1 - ts0); } return owners; } } }