/**
* 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.clustering.lda;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.mahout.common.IntPairWritable;
import com.google.common.base.Preconditions;
/**
* A very simple reducer which simply logSums the input doubles and outputs a new double for sufficient
* statistics, and sums log likelihoods.
*/
public class LDAReducer extends Reducer<IntPairWritable,DoubleWritable,IntPairWritable,DoubleWritable> {
@Override
public void reduce(IntPairWritable topicWord,
Iterable<DoubleWritable> values,
Context context) throws java.io.IOException, InterruptedException {
// sum likelihoods
if (topicWord.getSecond() == LDADriver.LOG_LIKELIHOOD_KEY) {
double accum = 0.0;
for (DoubleWritable vw : values) {
double v = vw.get();
Preconditions.checkArgument(!Double.isNaN(v),
"Found NaN for topic=(%d,%d)", topicWord.getFirst(), topicWord.getSecond());
accum += v;
}
context.write(topicWord, new DoubleWritable(accum));
} else { // log sum sufficient statistics.
double accum = Double.NEGATIVE_INFINITY;
for (DoubleWritable vw : values) {
double v = vw.get();
Preconditions.checkArgument(!Double.isNaN(v),
"Found NaN for topic = (%d,%d)", topicWord.getFirst(), topicWord.getSecond());
accum = LDAUtil.logSum(accum, v);
Preconditions.checkArgument(!Double.isNaN(accum),
"Accumulated NaN for topic = (%d,%d)", topicWord.getFirst(), topicWord.getSecond());
}
context.write(topicWord, new DoubleWritable(accum));
}
}
}