edu.snu.dolphin.bsp.examples.ml.data.RegressionDataParser.java Source code

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Here is the source code for edu.snu.dolphin.bsp.examples.ml.data.RegressionDataParser.java

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/*
 * Copyright (C) 2015 Seoul National University
 *
 * 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 edu.snu.dolphin.bsp.examples.ml.data;

import edu.snu.dolphin.bsp.core.DataParser;
import edu.snu.dolphin.bsp.core.ParseException;
import edu.snu.dolphin.bsp.examples.ml.parameters.Dimension;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.mahout.math.DenseVector;
import org.apache.mahout.math.Vector;
import org.apache.reef.io.data.loading.api.DataSet;
import org.apache.reef.io.network.util.Pair;
import org.apache.reef.tang.annotations.Parameter;

import javax.inject.Inject;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.logging.Level;
import java.util.logging.Logger;

public final class RegressionDataParser implements DataParser<List<Row>> {
    private static final Logger LOG = Logger.getLogger(RegressionDataParser.class.getName());

    private final AtomicInteger count = new AtomicInteger(0);
    private final int dimension;
    private final DataSet<LongWritable, Text> dataSet;
    private List<Row> result;
    private ParseException parseException;

    @Inject
    public RegressionDataParser(@Parameter(Dimension.class) final int dimension,
            final DataSet<LongWritable, Text> dataSet) {
        this.dimension = dimension;
        this.dataSet = dataSet;
    }

    @Override
    public List<Row> get() throws ParseException {
        LOG.log(Level.INFO, "RegressionDataParser called {0} times", count.incrementAndGet());
        if (result == null) {
            parse();
        }

        if (parseException != null) {
            throw parseException;
        }

        return result;
    }

    @Override
    public void parse() {
        LOG.log(Level.INFO, "Trying to parse!");
        result = new ArrayList<>();

        for (final Pair<LongWritable, Text> keyValue : dataSet) {

            final String text = keyValue.getSecond().toString().trim();
            if (text.startsWith("#") || text.length() == 0) {
                continue;
            }

            final String[] split = text.split("\\s+");
            if (split.length != dimension + 1) {
                parseException = new ParseException("Parse failed: the number of features is not " + dimension);
                return;
            }

            final double output;
            final Vector feature = new DenseVector(split.length);
            try {
                output = Double.valueOf(split[dimension]);
                for (int i = 0; i < dimension; i++) {
                    feature.set(i, Double.valueOf(split[i]));
                }
                feature.set(dimension, 1);
            } catch (final NumberFormatException e) {
                parseException = new ParseException("Parse failed: numbers should be DOUBLE");
                return;
            }

            result.add(new Row(output, feature));
        }
    }
}