/** * 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)); } } }