org.apache.lucene.search.spell.HighFrequencyDictionary Maven / Gradle / Ivy

/*
 * Copyright 2004-2009 the original author or authors.
 *
 * Licensed 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.lucene.search.spell;

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

import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.Term;
import org.apache.lucene.index.TermEnum;

/**
 * HighFrequencyDictionary: terms taken from the given field
 * of a Lucene index, which appear in a number of documents
 * above a given threshold.
 *
 * When using IndexReader.terms(Term) the code must not call next() on TermEnum
 * as the first call to TermEnum, see: http://issues.apache.org/jira/browse/LUCENE-6
 *
 * Threshold is a value in [0..1] representing the minimum
 * number of documents (of the total) where a term should appear.
 *
 * Based on LuceneDictionary.
 */
public class HighFrequencyDictionary implements Dictionary {
    private IndexReader reader;
    private String field;
    private float thresh;

    public HighFrequencyDictionary(IndexReader reader, String field, float thresh) {
        this.reader = reader;
        this.field = field.intern();
        this.thresh = thresh;
    }

    public final Iterator getWordsIterator() {
        return new HighFrequencyIterator();
    }

    final class HighFrequencyIterator implements Iterator {
        private TermEnum termEnum;
        private Term actualTerm;
        private boolean hasNextCalled;
        private int minNumDocs;

        HighFrequencyIterator() {
            try {
                termEnum = reader.terms(new Term(field, ""));
                minNumDocs = (int) (thresh * (float) reader.numDocs());
            } catch (IOException e) {
                throw new RuntimeException(e);
            }
        }

        private boolean isFrequent(Term term) {
            try {
                return reader.docFreq(term) >= minNumDocs;
            } catch (IOException e) {
                throw new RuntimeException(e);
            }
        }

        public Object next() {
            if (!hasNextCalled) {
                hasNext();
            }
            hasNextCalled = false;

            try {
                termEnum.next();
            } catch (IOException e) {
                throw new RuntimeException(e);
            }

            return (actualTerm != null) ? actualTerm.text() : null;
        }

        public boolean hasNext() {
            if (hasNextCalled) {
                return actualTerm != null;
            }
            hasNextCalled = true;

            do {
                actualTerm = termEnum.term();

                // if there are no words return false
                if (actualTerm == null) {
                    return false;
                }

                String currentField = actualTerm.field();

                // if the next word doesn't have the same field return false
                if (currentField != field) {
                    actualTerm = null;
                    return false;
                }

                // got a valid term, does it pass the threshold?
                if (isFrequent(actualTerm)) {
                    return true;
                }

                // term not up to threshold
                try {
                    termEnum.next();
                } catch (IOException e) {
                    throw new RuntimeException(e);
                }

            } while (true);
        }

        public void remove() {
            throw new UnsupportedOperationException();
        }
    }
}