Java tutorial
/** * This file is part of an implementation of C4.5 by Yohann Jardin. * * This implementation of C4.5 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. * * This implementation of C4.5 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 implementation of C4.5. If not, see <http://www.gnu.org/licenses/>. */ package full_MapReduce; import java.io.IOException; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.io.Writable; import org.apache.hadoop.mapreduce.Mapper; public class AttributeInfoMapper extends Mapper<TextArrayWritable, IntWritable, Text, AttributeCounterWritable> { public void map(TextArrayWritable key, IntWritable value, Context context) throws IOException, InterruptedException { Configuration conf = context.getConfiguration(); Writable[] key_values = key.get(); Text[] attributes_and_class = new Text[key_values.length]; for (Integer i = 0; i < key_values.length; ++i) { String[] value_needed = conf.getStrings(i.toString()); if (value_needed == null) { attributes_and_class[i] = (Text) key_values[i]; } else if (!value_needed[0].equals(((Text) key_values[i]).toString())) { return; } } Text classification = attributes_and_class[attributes_and_class.length - 1]; for (Integer i = 0; i < attributes_and_class.length - 1; ++i) { if (attributes_and_class[i] != null) { context.write(new Text(i.toString()), new AttributeCounterWritable(attributes_and_class[i], classification, value)); } } } }