org.apache.lucene.search.suggest.analyzing.XFuzzySuggester Maven / Gradle / Ivy
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package org.apache.lucene.search.suggest.analyzing;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.TokenStreamToAutomaton;
import org.apache.lucene.util.BytesRef;
import org.apache.lucene.util.IntsRef;
import org.apache.lucene.util.UnicodeUtil;
import org.apache.lucene.util.automaton.Automata;
import org.apache.lucene.util.automaton.Automaton;
import org.apache.lucene.util.automaton.FiniteStringsIterator;
import org.apache.lucene.util.automaton.LevenshteinAutomata;
import org.apache.lucene.util.automaton.Operations;
import org.apache.lucene.util.automaton.UTF32ToUTF8;
import org.apache.lucene.util.fst.FST;
import org.apache.lucene.util.fst.PairOutputs;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import static org.apache.lucene.util.automaton.Operations.DEFAULT_MAX_DETERMINIZED_STATES;
/**
* Implements a fuzzy {@link AnalyzingSuggester}. The similarity measurement is
* based on the Damerau-Levenshtein (optimal string alignment) algorithm, though
* you can explicitly choose classic Levenshtein by passing false
* for the transpositions
parameter.
*
* At most, this query will match terms up to
* {@value org.apache.lucene.util.automaton.LevenshteinAutomata#MAXIMUM_SUPPORTED_DISTANCE}
* edits. Higher distances are not supported. Note that the
* fuzzy distance is measured in "byte space" on the bytes
* returned by the {@link org.apache.lucene.analysis.TokenStream}'s {@link
* org.apache.lucene.analysis.tokenattributes.TermToBytesRefAttribute}, usually UTF8. By default
* the analyzed bytes must be at least 3 {@link
* #DEFAULT_MIN_FUZZY_LENGTH} bytes before any edits are
* considered. Furthermore, the first 1 {@link
* #DEFAULT_NON_FUZZY_PREFIX} byte is not allowed to be
* edited. We allow up to 1 (@link
* #DEFAULT_MAX_EDITS} edit.
* If {@link #unicodeAware} parameter in the constructor is set to true, maxEdits,
* minFuzzyLength, transpositions and nonFuzzyPrefix are measured in Unicode code
* points (actual letters) instead of bytes.*
*
*
* NOTE: This suggester does not boost suggestions that
* required no edits over suggestions that did require
* edits. This is a known limitation.
*
*
* Note: complex query analyzers can have a significant impact on the lookup
* performance. It's recommended to not use analyzers that drop or inject terms
* like synonyms to keep the complexity of the prefix intersection low for good
* lookup performance. At index time, complex analyzers can safely be used.
*
*/
public final class XFuzzySuggester extends XAnalyzingSuggester {
private final int maxEdits;
private final boolean transpositions;
private final int nonFuzzyPrefix;
private final int minFuzzyLength;
private final boolean unicodeAware;
/**
* Measure maxEdits, minFuzzyLength, transpositions and nonFuzzyPrefix
* parameters in Unicode code points (actual letters)
* instead of bytes.
*/
public static final boolean DEFAULT_UNICODE_AWARE = false;
/**
* The default minimum length of the key passed to {@link
* #lookup} before any edits are allowed.
*/
public static final int DEFAULT_MIN_FUZZY_LENGTH = 3;
/**
* The default prefix length where edits are not allowed.
*/
public static final int DEFAULT_NON_FUZZY_PREFIX = 1;
/**
* The default maximum number of edits for fuzzy
* suggestions.
*/
public static final int DEFAULT_MAX_EDITS = 1;
/**
* The default transposition value passed to {@link org.apache.lucene.util.automaton.LevenshteinAutomata}
*/
public static final boolean DEFAULT_TRANSPOSITIONS = true;
/**
* Creates a {@link FuzzySuggester} instance initialized with default values.
*
* @param analyzer the analyzer used for this suggester
*/
public XFuzzySuggester(Analyzer analyzer) {
this(analyzer, analyzer);
}
/**
* Creates a {@link FuzzySuggester} instance with an index & a query analyzer initialized with default values.
*
* @param indexAnalyzer
* Analyzer that will be used for analyzing suggestions while building the index.
* @param queryAnalyzer
* Analyzer that will be used for analyzing query text during lookup
*/
public XFuzzySuggester(Analyzer indexAnalyzer, Analyzer queryAnalyzer) {
this(indexAnalyzer, null, queryAnalyzer, EXACT_FIRST | PRESERVE_SEP, 256, -1,
DEFAULT_MAX_EDITS, DEFAULT_TRANSPOSITIONS,
DEFAULT_NON_FUZZY_PREFIX, DEFAULT_MIN_FUZZY_LENGTH, DEFAULT_UNICODE_AWARE,
null, false, 0, SEP_LABEL, PAYLOAD_SEP, END_BYTE, HOLE_CHARACTER);
}
/**
* Creates a {@link FuzzySuggester} instance.
*
* @param indexAnalyzer Analyzer that will be used for
* analyzing suggestions while building the index.
* @param queryAnalyzer Analyzer that will be used for
* analyzing query text during lookup
* @param options see {@link #EXACT_FIRST}, {@link #PRESERVE_SEP}
* @param maxSurfaceFormsPerAnalyzedForm Maximum number of
* surface forms to keep for a single analyzed form.
* When there are too many surface forms we discard the
* lowest weighted ones.
* @param maxGraphExpansions Maximum number of graph paths
* to expand from the analyzed form. Set this to -1 for
* no limit.
* @param maxEdits must be >= 0 and <= {@link org.apache.lucene.util.automaton.LevenshteinAutomata#MAXIMUM_SUPPORTED_DISTANCE} .
* @param transpositions true
if transpositions should be treated as a primitive
* edit operation. If this is false, comparisons will implement the classic
* Levenshtein algorithm.
* @param nonFuzzyPrefix length of common (non-fuzzy) prefix (see default {@link #DEFAULT_NON_FUZZY_PREFIX}
* @param minFuzzyLength minimum length of lookup key before any edits are allowed (see default {@link #DEFAULT_MIN_FUZZY_LENGTH})
* @param sepLabel separation label
* @param payloadSep payload separator byte
* @param endByte end byte marker byte
*/
public XFuzzySuggester(Analyzer indexAnalyzer, Automaton queryPrefix, Analyzer queryAnalyzer,
int options, int maxSurfaceFormsPerAnalyzedForm, int maxGraphExpansions,
int maxEdits, boolean transpositions, int nonFuzzyPrefix, int minFuzzyLength,
boolean unicodeAware, FST> fst, boolean hasPayloads,
int maxAnalyzedPathsForOneInput, int sepLabel, int payloadSep, int endByte, int holeCharacter) {
super(indexAnalyzer, queryPrefix, queryAnalyzer, options, maxSurfaceFormsPerAnalyzedForm, maxGraphExpansions,
true, fst, hasPayloads, maxAnalyzedPathsForOneInput, sepLabel, payloadSep, endByte, holeCharacter);
if (maxEdits < 0 || maxEdits > LevenshteinAutomata.MAXIMUM_SUPPORTED_DISTANCE) {
throw new IllegalArgumentException(
"maxEdits must be between 0 and " + LevenshteinAutomata.MAXIMUM_SUPPORTED_DISTANCE);
}
if (nonFuzzyPrefix < 0) {
throw new IllegalArgumentException("nonFuzzyPrefix must not be >= 0 (got " + nonFuzzyPrefix + ")");
}
if (minFuzzyLength < 0) {
throw new IllegalArgumentException("minFuzzyLength must not be >= 0 (got " + minFuzzyLength + ")");
}
this.maxEdits = maxEdits;
this.transpositions = transpositions;
this.nonFuzzyPrefix = nonFuzzyPrefix;
this.minFuzzyLength = minFuzzyLength;
this.unicodeAware = unicodeAware;
}
@Override
protected List>> getFullPrefixPaths(
List>> prefixPaths, Automaton lookupAutomaton,
FST> fst)
throws IOException {
// TODO: right now there's no penalty for fuzzy/edits,
// ie a completion whose prefix matched exactly what the
// user typed gets no boost over completions that
// required an edit, which get no boost over completions
// requiring two edits. I suspect a multiplicative
// factor is appropriate (eg, say a fuzzy match must be at
// least 2X better weight than the non-fuzzy match to
// "compete") ... in which case I think the wFST needs
// to be log weights or something ...
Automaton levA = convertAutomaton(toLevenshteinAutomata(lookupAutomaton));
/*
Writer w = new OutputStreamWriter(new FileOutputStream("out.dot"), "UTF-8");
w.write(levA.toDot());
w.close();
System.out.println("Wrote LevA to out.dot");
*/
return FSTUtil.intersectPrefixPaths(levA, fst);
}
@Override
protected Automaton convertAutomaton(Automaton a) {
if (unicodeAware) {
// FLORIAN EDIT: get converted Automaton from superclass
Automaton utf8automaton = new UTF32ToUTF8().convert(super.convertAutomaton(a));
// This automaton should not blow up during determinize:
utf8automaton = Operations.determinize(utf8automaton, Integer.MAX_VALUE);
return utf8automaton;
} else {
return super.convertAutomaton(a);
}
}
@Override
public TokenStreamToAutomaton getTokenStreamToAutomaton() {
final TokenStreamToAutomaton tsta = super.getTokenStreamToAutomaton();
tsta.setUnicodeArcs(unicodeAware);
return tsta;
}
Automaton toLevenshteinAutomata(Automaton automaton) {
List subs = new ArrayList<>();
FiniteStringsIterator finiteStrings = new FiniteStringsIterator(automaton);
for (IntsRef string; (string = finiteStrings.next()) != null;) {
if (string.length <= nonFuzzyPrefix || string.length < minFuzzyLength) {
subs.add(Automata.makeString(string.ints, string.offset, string.length));
} else {
int ints[] = new int[string.length-nonFuzzyPrefix];
System.arraycopy(string.ints, string.offset+nonFuzzyPrefix, ints, 0, ints.length);
// TODO: maybe add alphaMin to LevenshteinAutomata,
// and pass 1 instead of 0? We probably don't want
// to allow the trailing dedup bytes to be
// edited... but then 0 byte is "in general" allowed
// on input (but not in UTF8).
LevenshteinAutomata lev = new LevenshteinAutomata(
ints, unicodeAware ? Character.MAX_CODE_POINT : 255, transpositions);
subs.add(lev.toAutomaton(maxEdits, UnicodeUtil.newString(string.ints, string.offset, nonFuzzyPrefix)));
}
}
if (subs.isEmpty()) {
// automaton is empty, there is no accepted paths through it
return Automata.makeEmpty(); // matches nothing
} else if (subs.size() == 1) {
// no synonyms or anything: just a single path through the tokenstream
return subs.get(0);
} else {
// multiple paths: this is really scary! is it slow?
// maybe we should not do this and throw UOE?
Automaton a = Operations.union(subs);
// TODO: we could call toLevenshteinAutomata() before det?
// this only happens if you have multiple paths anyway (e.g. synonyms)
return Operations.determinize(a, DEFAULT_MAX_DETERMINIZED_STATES);
}
}
}