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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 org.apache.lucene.search;


import java.io.IOException;

import org.apache.lucene.index.SingleTermsEnum;
import org.apache.lucene.index.Term;
import org.apache.lucene.index.Terms;
import org.apache.lucene.index.TermsEnum;
import org.apache.lucene.util.AttributeSource;
import org.apache.lucene.util.automaton.LevenshteinAutomata;

/** Implements the fuzzy search query. The similarity measurement
 * is based on the Damerau-Levenshtein (optimal string alignment) algorithm,
 * though you can explicitly choose classic Levenshtein by passing false
 * to the transpositions parameter.
 * 
 * 

This query uses {@link MultiTermQuery.TopTermsBlendedFreqScoringRewrite} * as default. So terms will be collected and scored according to their * edit distance. Only the top terms are used for building the {@link BooleanQuery}. * It is not recommended to change the rewrite mode for fuzzy queries. * *

At most, this query will match terms up to * {@value org.apache.lucene.util.automaton.LevenshteinAutomata#MAXIMUM_SUPPORTED_DISTANCE} edits. * Higher distances (especially with transpositions enabled), are generally not useful and * will match a significant amount of the term dictionary. If you really want this, consider * using an n-gram indexing technique (such as the SpellChecker in the * suggest module) instead. * *

NOTE: terms of length 1 or 2 will sometimes not match because of how the scaled * distance between two terms is computed. For a term to match, the edit distance between * the terms must be less than the minimum length term (either the input term, or * the candidate term). For example, FuzzyQuery on term "abcd" with maxEdits=2 will * not match an indexed term "ab", and FuzzyQuery on term "a" with maxEdits=2 will not * match an indexed term "abc". */ public class FuzzyQuery extends MultiTermQuery { public final static int defaultMaxEdits = LevenshteinAutomata.MAXIMUM_SUPPORTED_DISTANCE; public final static int defaultPrefixLength = 0; public final static int defaultMaxExpansions = 50; public final static boolean defaultTranspositions = true; private final int maxEdits; private final int maxExpansions; private final boolean transpositions; private final int prefixLength; private final Term term; /** * Create a new FuzzyQuery that will match terms with an edit distance * of at most maxEdits to term. * If a prefixLength > 0 is specified, a common prefix * of that length is also required. * * @param term the term to search for * @param maxEdits must be {@code >= 0} and {@code <=} {@link LevenshteinAutomata#MAXIMUM_SUPPORTED_DISTANCE}. * @param prefixLength length of common (non-fuzzy) prefix * @param maxExpansions the maximum number of terms to match. If this number is * greater than {@link BooleanQuery#getMaxClauseCount} when the query is rewritten, * then the maxClauseCount will be used instead. * @param transpositions true if transpositions should be treated as a primitive * edit operation. If this is false, comparisons will implement the classic * Levenshtein algorithm. */ public FuzzyQuery(Term term, int maxEdits, int prefixLength, int maxExpansions, boolean transpositions) { super(term.field()); if (maxEdits < 0 || maxEdits > LevenshteinAutomata.MAXIMUM_SUPPORTED_DISTANCE) { throw new IllegalArgumentException("maxEdits must be between 0 and " + LevenshteinAutomata.MAXIMUM_SUPPORTED_DISTANCE); } if (prefixLength < 0) { throw new IllegalArgumentException("prefixLength cannot be negative."); } if (maxExpansions <= 0) { throw new IllegalArgumentException("maxExpansions must be positive."); } this.term = term; this.maxEdits = maxEdits; this.prefixLength = prefixLength; this.transpositions = transpositions; this.maxExpansions = maxExpansions; setRewriteMethod(new MultiTermQuery.TopTermsBlendedFreqScoringRewrite(maxExpansions)); } /** * Calls {@link #FuzzyQuery(Term, int, int, int, boolean) * FuzzyQuery(term, maxEdits, prefixLength, defaultMaxExpansions, defaultTranspositions)}. */ public FuzzyQuery(Term term, int maxEdits, int prefixLength) { this(term, maxEdits, prefixLength, defaultMaxExpansions, defaultTranspositions); } /** * Calls {@link #FuzzyQuery(Term, int, int) FuzzyQuery(term, maxEdits, defaultPrefixLength)}. */ public FuzzyQuery(Term term, int maxEdits) { this(term, maxEdits, defaultPrefixLength); } /** * Calls {@link #FuzzyQuery(Term, int) FuzzyQuery(term, defaultMaxEdits)}. */ public FuzzyQuery(Term term) { this(term, defaultMaxEdits); } /** * @return the maximum number of edit distances allowed for this query to match. */ public int getMaxEdits() { return maxEdits; } /** * Returns the non-fuzzy prefix length. This is the number of characters at the start * of a term that must be identical (not fuzzy) to the query term if the query * is to match that term. */ public int getPrefixLength() { return prefixLength; } /** * Returns true if transpositions should be treated as a primitive edit operation. * If this is false, comparisons will implement the classic Levenshtein algorithm. */ public boolean getTranspositions() { return transpositions; } @Override protected TermsEnum getTermsEnum(Terms terms, AttributeSource atts) throws IOException { if (maxEdits == 0 || prefixLength >= term.text().length()) { // can only match if it's exact return new SingleTermsEnum(terms.iterator(), term.bytes()); } return new FuzzyTermsEnum(terms, atts, getTerm(), maxEdits, prefixLength, transpositions); } /** * Returns the pattern term. */ public Term getTerm() { return term; } @Override public String toString(String field) { final StringBuilder buffer = new StringBuilder(); if (!term.field().equals(field)) { buffer.append(term.field()); buffer.append(":"); } buffer.append(term.text()); buffer.append('~'); buffer.append(Integer.toString(maxEdits)); return buffer.toString(); } @Override public int hashCode() { final int prime = 31; int result = super.hashCode(); result = prime * result + maxEdits; result = prime * result + prefixLength; result = prime * result + maxExpansions; result = prime * result + (transpositions ? 0 : 1); result = prime * result + ((term == null) ? 0 : term.hashCode()); return result; } @Override public boolean equals(Object obj) { if (this == obj) return true; if (!super.equals(obj)) return false; if (getClass() != obj.getClass()) return false; FuzzyQuery other = (FuzzyQuery) obj; if (maxEdits != other.maxEdits) return false; if (prefixLength != other.prefixLength) return false; if (maxExpansions != other.maxExpansions) return false; if (transpositions != other.transpositions) return false; if (term == null) { if (other.term != null) return false; } else if (!term.equals(other.term)) return false; return true; } /** * @deprecated pass integer edit distances instead. */ @Deprecated public final static float defaultMinSimilarity = LevenshteinAutomata.MAXIMUM_SUPPORTED_DISTANCE; /** * Helper function to convert from deprecated "minimumSimilarity" fractions * to raw edit distances. * * @param minimumSimilarity scaled similarity * @param termLen length (in unicode codepoints) of the term. * @return equivalent number of maxEdits * @deprecated pass integer edit distances instead. */ @Deprecated public static int floatToEdits(float minimumSimilarity, int termLen) { if (minimumSimilarity >= 1f) { return (int) Math.min(minimumSimilarity, LevenshteinAutomata.MAXIMUM_SUPPORTED_DISTANCE); } else if (minimumSimilarity == 0.0f) { return 0; // 0 means exact, not infinite # of edits! } else { return Math.min((int) ((1D-minimumSimilarity) * termLen), LevenshteinAutomata.MAXIMUM_SUPPORTED_DISTANCE); } } }





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