Knows.java

/*
 * Copyright (c) 2013 LDBC
 * Linked Data Benchmark Council (http://ldbc.eu)
 *
 * This file is part of ldbc_socialnet_dbgen.
 *
 * ldbc_socialnet_dbgen is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 * 
 * ldbc_socialnet_dbgen 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 General Public License for more details.
 * 
 * You should have received a copy of the GNU General Public License
 * along with ldbc_socialnet_dbgen.  If not, see <http://www.gnu.org/licenses/>.
 *
 * Copyright (C) 2011 OpenLink Software <bdsmt@openlinksw.com>
 * All Rights Reserved.
 *
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation;  only Version 2 of the License dated
 * June 1991.
 *
 * This program 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 General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
 */
package ldbc.snb.datagen.objects;

import ldbc.snb.datagen.dictionary.Dictionaries;
import ldbc.snb.datagen.generator.DatagenParams;
import ldbc.snb.datagen.util.RandomGeneratorFarm;
import org.apache.hadoop.io.Writable;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Comparator;
import java.util.Random;


public class Knows implements Writable, Comparable<Knows> {

    long creationDate_;
	Person.PersonSummary to_= null;
    float weight_ = 0.0f;

	public Knows() {
		to_ = new Person.PersonSummary();
	}

    public Knows(Knows k) {
	    to_ = new Person.PersonSummary(k.to());
	    creationDate_ = k.creationDate();
        weight_ = k.weight();
    }

    public Knows( Person to, long creationDate, float weight ){
	    to_ = new Person.PersonSummary(to);
	    creationDate_ = creationDate;
        weight_ = weight;
    }

    public Person.PersonSummary to ( ) {
	    return to_;
    }

    public void to( Person.PersonSummary to ) {
	    to_.copy(to);
    }

    public long creationDate() {
	    return creationDate_;
    }

    public void creationDate ( long creationDate ) {
	    creationDate_ = creationDate;
    }

    public void weight ( float weight ) {
        weight_ = weight;
    }

    public float weight() {
        return weight_;
    }

    public void readFields(DataInput arg0) throws IOException {
        to_.readFields(arg0);
        creationDate_ = arg0.readLong();
        weight_ = arg0.readFloat();
    }

    public void write(DataOutput arg0) throws IOException {
	    to_.write(arg0);
	    arg0.writeLong(creationDate_);
        arg0.writeFloat(weight_);
    }

    public int compareTo(Knows k) {
        long res =  (to_.accountId() - k.to().accountId());
        if( res > 0 ) return 1;
        if( res < 0 ) return -1;
        /*long res2 = creationDate_ - k.creationDate();
        if( res2 > 0 ) return 1;
        if( res2 < 0 ) return -1;
        */
        return 0;
    }

    static public class FullComparator implements Comparator<Knows> {

        public int compare(Knows a, Knows b) {
            long res =  (a.to_.accountId() - b.to().accountId());
            if( res > 0 ) return 1;
            if( res < 0 ) return -1;
            long res2 = a.creationDate_ - b.creationDate();
            if( res2 > 0 ) return 1;
            if( res2 < 0 ) return -1;
            return 0;
        }

    }

    public static int num = 0;

    public static boolean createKnow( Random random, Person personA, Person personB ) {
        long  creationDate = Dictionaries.dates.randomKnowsCreationDate(
                random,
                personA,
                personB);
        creationDate = creationDate - personA.creationDate() >= DatagenParams.deltaTime ? creationDate : creationDate + (DatagenParams.deltaTime - (creationDate - personA.creationDate()));
        creationDate = creationDate - personB.creationDate() >= DatagenParams.deltaTime ? creationDate : creationDate + (DatagenParams.deltaTime - (creationDate - personB.creationDate()));
        /*if( creationDate <= Dictionaries.dates.getEndDateTime() )*/ {
            float similarity = Person.personSimilarity.Similarity(personA,personB);
            if(!personB.knows().add(new Knows(personA, creationDate, similarity))) return false;
            if(!personA.knows().add(new Knows(personB, creationDate, similarity))) return false;
            return true;
        }
        //return false;
    }

    public static long target_edges(Person person, ArrayList<Float> percentages, int step_index ) {
        int generated_edges = 0;
        for (int i = 0; i < step_index; ++i) {
            generated_edges += Math.ceil(percentages.get(i)*person.maxNumKnows());
        }
        generated_edges = Math.min(generated_edges, (int)person.maxNumKnows());
        int to_generate = Math.min( (int)person.maxNumKnows() - generated_edges, (int)Math.ceil(percentages.get(step_index)*person.maxNumKnows()));
        return  to_generate;
    }
}