3a0263bb72
you can do a manual fuzzy term search using the FuzzyQuery struct or, more suitable for most users the MatchQuery now supports some fuzzy options. Here you can specify fuzziness and prefix_length, to turn the underlying term search into a fuzzy term search. This has the benefit that analysis is performed on your input, just like the analyzed field, prior to computing the fuzzy variants. closes #82
192 lines
4.3 KiB
Go
192 lines
4.3 KiB
Go
// Copyright (c) 2014 Couchbase, Inc.
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// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file
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// except in compliance with the License. You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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// Unless required by applicable law or agreed to in writing, software distributed under the
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// License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
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// either express or implied. See the License for the specific language governing permissions
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// and limitations under the License.
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package searchers
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import (
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"math"
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"github.com/blevesearch/bleve/index"
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"github.com/blevesearch/bleve/search"
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)
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type FuzzySearcher struct {
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indexReader index.IndexReader
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term string
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prefix int
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fuzziness int
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field string
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explain bool
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searcher *DisjunctionSearcher
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}
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func NewFuzzySearcher(indexReader index.IndexReader, term string, prefix, fuzziness int, field string, boost float64, explain bool) (*FuzzySearcher, error) {
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prefixTerm := ""
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for i, r := range term {
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if i < prefix {
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prefixTerm += string(r)
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}
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}
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// find the terms with this prefix
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fieldReader, err := indexReader.FieldReader(field, []byte(prefixTerm), []byte(prefixTerm))
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// enumerate terms and check levenshtein distance
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candidateTerms := make([]string, 0)
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tfd, err := fieldReader.Next()
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for err == nil && tfd != nil {
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ld, exceeded := levenshteinDistanceMax(&term, &tfd.Term, fuzziness)
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if !exceeded && ld <= fuzziness {
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candidateTerms = append(candidateTerms, tfd.Term)
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}
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tfd, err = fieldReader.Next()
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}
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// enumerate all the terms in the range
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qsearchers := make([]search.Searcher, 0, 25)
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for _, cterm := range candidateTerms {
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qsearcher, err := NewTermSearcher(indexReader, cterm, field, 1.0, explain)
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if err != nil {
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return nil, err
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}
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qsearchers = append(qsearchers, qsearcher)
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}
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// build disjunction searcher of these ranges
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searcher, err := NewDisjunctionSearcher(indexReader, qsearchers, 0, explain)
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if err != nil {
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return nil, err
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}
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return &FuzzySearcher{
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indexReader: indexReader,
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term: term,
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prefix: prefix,
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fuzziness: fuzziness,
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field: field,
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explain: explain,
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searcher: searcher,
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}, nil
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}
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func (s *FuzzySearcher) Count() uint64 {
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return s.searcher.Count()
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}
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func (s *FuzzySearcher) Weight() float64 {
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return s.searcher.Weight()
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}
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func (s *FuzzySearcher) SetQueryNorm(qnorm float64) {
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s.searcher.SetQueryNorm(qnorm)
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}
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func (s *FuzzySearcher) Next() (*search.DocumentMatch, error) {
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return s.searcher.Next()
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}
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func (s *FuzzySearcher) Advance(ID string) (*search.DocumentMatch, error) {
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return s.searcher.Next()
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}
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func (s *FuzzySearcher) Close() {
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s.searcher.Close()
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}
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func (s *FuzzySearcher) Min() int {
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return 0
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}
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func levenshteinDistance(a, b *string) int {
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la := len(*a)
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lb := len(*b)
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d := make([]int, la+1)
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var lastdiag, olddiag, temp int
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for i := 1; i <= la; i++ {
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d[i] = i
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}
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for i := 1; i <= lb; i++ {
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d[0] = i
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lastdiag = i - 1
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for j := 1; j <= la; j++ {
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olddiag = d[j]
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min := d[j] + 1
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if (d[j-1] + 1) < min {
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min = d[j-1] + 1
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}
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if (*a)[j-1] == (*b)[i-1] {
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temp = 0
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} else {
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temp = 1
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}
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if (lastdiag + temp) < min {
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min = lastdiag + temp
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}
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d[j] = min
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lastdiag = olddiag
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}
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}
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return d[la]
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}
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// levenshteinDistanceMax same as levenshteinDistance but
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// attempts to bail early once we know the distance
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// will be greater than max
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// in which case the first return val will be the max
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// and the second will be true, indicating max was exceeded
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func levenshteinDistanceMax(a, b *string, max int) (int, bool) {
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la := len(*a)
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lb := len(*b)
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ld := int(math.Abs(float64(la - lb)))
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if ld > max {
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return max, true
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}
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d := make([]int, la+1)
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var lastdiag, olddiag, temp int
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for i := 1; i <= la; i++ {
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d[i] = i
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}
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for i := 1; i <= lb; i++ {
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d[0] = i
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lastdiag = i - 1
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rowmin := max + 1
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for j := 1; j <= la; j++ {
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olddiag = d[j]
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min := d[j] + 1
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if (d[j-1] + 1) < min {
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min = d[j-1] + 1
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}
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if (*a)[j-1] == (*b)[i-1] {
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temp = 0
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} else {
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temp = 1
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}
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if (lastdiag + temp) < min {
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min = lastdiag + temp
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}
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if min < rowmin {
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rowmin = min
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}
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d[j] = min
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lastdiag = olddiag
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}
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// after each row if rowmin isnt less than max stop
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if rowmin > max {
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return max, true
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}
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}
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return d[la], false
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}
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