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.io.IntWritable; import org.apache.hadoop.io.MapWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Reducer; public class AttributeInfoReducer extends Reducer<Text, AttributeCounterWritable, Text, MapWritable> { public void reduce(Text key, Iterable<AttributeCounterWritable> values, Context context) throws IOException, InterruptedException { MapWritable res = new MapWritable(); Text value; Text classification; IntWritable count; for (AttributeCounterWritable cur_attribute_counter : values) { value = cur_attribute_counter.getValue(); classification = cur_attribute_counter.getClassification(); count = cur_attribute_counter.getCount(); if (!res.containsKey(value)) { res.put(new Text(value), new MapWritable()); } MapWritable cur_map = (MapWritable) res.get(value); if (!cur_map.containsKey(classification)) { cur_map.put(new Text(classification), new IntWritable(0)); } ((IntWritable) cur_map.get(classification)) .set(((IntWritable) cur_map.get(classification)).get() + count.get()); } context.write(key, res); } }