edu.rosehulman.TFPartialVectorReducer.java Source code

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Here is the source code for edu.rosehulman.TFPartialVectorReducer.java

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/**
 * 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 edu.rosehulman;

import com.google.common.io.Closeables;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.lucene.analysis.shingle.ShingleFilter;
import org.apache.lucene.analysis.tokenattributes.CharTermAttribute;
import org.apache.mahout.common.HadoopUtil;
import org.apache.mahout.common.Pair;
import org.apache.mahout.common.StringTuple;
import org.apache.mahout.common.iterator.sequencefile.SequenceFileIterable;
import org.apache.mahout.common.lucene.IteratorTokenStream;
import org.apache.mahout.math.NamedVector;
import org.apache.mahout.math.RandomAccessSparseVector;
import org.apache.mahout.math.SequentialAccessSparseVector;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.VectorWritable;
import org.apache.mahout.math.map.OpenObjectIntHashMap;
import org.apache.mahout.vectorizer.DictionaryVectorizer;
import org.apache.mahout.vectorizer.common.PartialVectorMerger;

import java.io.IOException;
import java.util.Iterator;

/**
 * Converts a document in to a sparse vector
 */
public class TFPartialVectorReducer extends Reducer<Text, StringTuple, Text, VectorWritable> {

    private final OpenObjectIntHashMap<String> dictionary = new OpenObjectIntHashMap<String>();

    private int dimension;

    private boolean sequentialAccess;

    private boolean namedVector;

    private int maxNGramSize = 1;

    @Override
    protected void reduce(Text key, Iterable<StringTuple> values, Context context)
            throws IOException, InterruptedException {
        Iterator<StringTuple> it = values.iterator();
        if (!it.hasNext()) {
            return;
        }
        StringTuple value = it.next();

        Vector vector = new RandomAccessSparseVector(dimension, value.length()); // guess at initial size

        if (maxNGramSize >= 2) {
            ShingleFilter sf = new ShingleFilter(new IteratorTokenStream(value.getEntries().iterator()),
                    maxNGramSize);
            sf.reset();
            try {
                do {
                    String term = sf.getAttribute(CharTermAttribute.class).toString();
                    if (!term.isEmpty() && dictionary.containsKey(term)) { // ngram
                        int termId = dictionary.get(term);
                        vector.setQuick(termId, vector.getQuick(termId) + 1);
                    }
                } while (sf.incrementToken());

                sf.end();
            } finally {
                Closeables.close(sf, true);
            }
        } else {
            for (String term : value.getEntries()) {
                if (!term.isEmpty() && dictionary.containsKey(term)) { // unigram
                    int termId = dictionary.get(term);
                    vector.setQuick(termId, vector.getQuick(termId) + 1);
                }
            }
        }
        if (sequentialAccess) {
            vector = new SequentialAccessSparseVector(vector);
        }

        if (namedVector) {
            vector = new NamedVector(vector, key.toString());
        }

        // if the vector has no nonZero entries (nothing in the dictionary), let's not waste space sending it to disk.
        if (vector.getNumNondefaultElements() > 0) {
            VectorWritable vectorWritable = new VectorWritable(vector);
            context.write(key, vectorWritable);
        } else {
            context.getCounter("TFPartialVectorReducer", "emptyVectorCount").increment(1);
        }
    }

    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
        super.setup(context);
        Configuration conf = context.getConfiguration();

        dimension = conf.getInt(PartialVectorMerger.DIMENSION, Integer.MAX_VALUE);
        sequentialAccess = conf.getBoolean(PartialVectorMerger.SEQUENTIAL_ACCESS, false);
        namedVector = conf.getBoolean(PartialVectorMerger.NAMED_VECTOR, false);
        maxNGramSize = conf.getInt(DictionaryVectorizer.MAX_NGRAMS, maxNGramSize);

        //MAHOUT-1247
        Path dictionaryFile = HadoopUtil.getSingleCachedFile(conf);
        // key is word value is id
        for (Pair<Writable, IntWritable> record : new SequenceFileIterable<Writable, IntWritable>(dictionaryFile,
                true, conf)) {
            dictionary.put(record.getFirst().toString(), record.getSecond().get());
        }
    }

}