it.tizianofagni.sparkboost.AdaBoostMHLearnerExe.java Source code

Introduction

Here is the source code for it.tizianofagni.sparkboost.AdaBoostMHLearnerExe.java

Source

/*
 *
 * ****************
 * This file is part of sparkboost software package (https://github.com/tizfa/sparkboost).
 *
 * Copyright 2016 Tiziano Fagni (tiziano.fagni@isti.cnr.it)
 *
 * Licensed 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 it.tizianofagni.sparkboost;

import org.apache.commons.cli.*;
import org.apache.log4j.Level;
import org.apache.log4j.Logger;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaSparkContext;

/**
 * @author Tiziano Fagni (tiziano.fagni@isti.cnr.it)
 */
public class AdaBoostMHLearnerExe {
    public static void main(String[] args) {
        Options options = new Options();
        options.addOption("b", "binaryProblem", false,
                "Indicate if the input dataset contains a binary problem and not a multilabel one");
        options.addOption("z", "labels0based", false,
                "Indicate if the labels IDs in the dataset to classifyLibSvmWithResults are already assigned in the range [0, numLabels-1] included");
        options.addOption("l", "enableSparkLogging", false, "Enable logging messages of Spark");
        options.addOption("w", "windowsLocalModeFix", true,
                "Set the directory containing the winutils.exe command");
        options.addOption("dp", "documentPartitions", true, "The number of document partitions");
        options.addOption("fp", "featurePartitions", true, "The number of feature partitions");
        options.addOption("lp", "labelPartitions", true, "The number of label partitions");

        CommandLineParser parser = new BasicParser();
        CommandLine cmd = null;
        String[] remainingArgs = null;
        try {
            cmd = parser.parse(options, args);
            remainingArgs = cmd.getArgs();
            if (remainingArgs.length != 5)
                throw new ParseException("You need to specify all mandatory parameters");
        } catch (ParseException e) {
            System.out.println("Parsing failed.  Reason: " + e.getMessage());
            HelpFormatter formatter = new HelpFormatter();
            formatter.printHelp(AdaBoostMHLearnerExe.class.getSimpleName()
                    + " [OPTIONS] <inputFile> <outputFile> <numIterations> <sparkMaster> <parallelismDegree>",
                    options);
            System.exit(-1);
        }

        boolean binaryProblem = false;
        if (cmd.hasOption("b"))
            binaryProblem = true;
        boolean labels0Based = false;
        if (cmd.hasOption("z"))
            labels0Based = true;
        boolean enablingSparkLogging = false;
        if (cmd.hasOption("l"))
            enablingSparkLogging = true;

        if (cmd.hasOption("w")) {
            System.setProperty("hadoop.home.dir", cmd.getOptionValue("w"));
        }

        String inputFile = remainingArgs[0];
        String outputFile = remainingArgs[1];
        int numIterations = Integer.parseInt(remainingArgs[2]);
        String sparkMaster = remainingArgs[3];
        int parallelismDegree = Integer.parseInt(remainingArgs[4]);

        long startTime = System.currentTimeMillis();

        // Disable Spark logging.
        if (!enablingSparkLogging) {
            Logger.getLogger("org").setLevel(Level.OFF);
            Logger.getLogger("akka").setLevel(Level.OFF);
        }

        // Create and configure Spark context.
        SparkConf conf = new SparkConf().setAppName("Spark AdaBoost.MH learner");
        JavaSparkContext sc = new JavaSparkContext(conf);

        // Create and configure learner.
        AdaBoostMHLearner learner = new AdaBoostMHLearner(sc);
        learner.setNumIterations(numIterations);

        if (cmd.hasOption("dp")) {
            learner.setNumDocumentsPartitions(Integer.parseInt(cmd.getOptionValue("dp")));
        }
        if (cmd.hasOption("fp")) {
            learner.setNumFeaturesPartitions(Integer.parseInt(cmd.getOptionValue("fp")));
        }
        if (cmd.hasOption("lp")) {
            learner.setNumLabelsPartitions(Integer.parseInt(cmd.getOptionValue("lp")));
        }

        // Build classifier with MPBoost learner.
        BoostClassifier classifier = learner.buildModel(inputFile, labels0Based, binaryProblem);

        // Save classifier to disk.
        DataUtils.saveModel(sc, classifier, outputFile);

        long endTime = System.currentTimeMillis();
        System.out.println("Execution time: " + (endTime - startTime) + " milliseconds.");
    }
}