/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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 org.apache.mahout.classifier.bayes.mapreduce.cbayes;
import java.io.IOException;
import java.util.Iterator;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.mahout.common.StringTuple;
/**
* Can also be used as a local Combiner beacuse only two values should be there inside the values
*/
public class CBayesThetaNormalizerReducer extends MapReduceBase implements
Reducer<StringTuple,DoubleWritable,StringTuple,DoubleWritable> {
@Override
public void reduce(StringTuple key,
Iterator<DoubleWritable> values,
OutputCollector<StringTuple,DoubleWritable> output,
Reporter reporter) throws IOException {
// Key is label,word, value is the number of times we've seen this label word per local node. Output is the same
double weightSumPerLabel = 0.0;
while (values.hasNext()) {
reporter.setStatus("Complementary Bayes Theta Normalizer Reducer: " + key);
weightSumPerLabel += values.next().get();
}
reporter.setStatus("Complementary Bayes Theta Normalizer Reducer: " + key + " => " + weightSumPerLabel);
output.collect(key, new DoubleWritable(weightSumPerLabel));
}
}