2ee7289bc8
this started initially to relocate highlighting into a self contained package, which would then also use the registry however, it turned into a much larger refactor in order to avoid cyclic imports now facets, searchers, scorers and collectors are also broken out into subpackages of search
171 lines
4.7 KiB
Go
171 lines
4.7 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 scorers
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import (
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"fmt"
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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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const MAX_SCORE_CACHE = 64
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type TermQueryScorer struct {
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queryTerm string
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queryField string
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queryBoost float64
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docTerm uint64
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docTotal uint64
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idf float64
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explain bool
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idfExplanation *search.Explanation
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queryNorm float64
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queryWeight float64
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queryWeightExplanation *search.Explanation
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}
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func NewTermQueryScorer(queryTerm string, queryField string, queryBoost float64, docTotal, docTerm uint64, explain bool) *TermQueryScorer {
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rv := TermQueryScorer{
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queryTerm: queryTerm,
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queryField: queryField,
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queryBoost: queryBoost,
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docTerm: docTerm,
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docTotal: docTotal,
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idf: 1.0 + math.Log(float64(docTotal)/float64(docTerm+1.0)),
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explain: explain,
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queryWeight: 1.0,
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}
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if explain {
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rv.idfExplanation = &search.Explanation{
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Value: rv.idf,
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Message: fmt.Sprintf("idf(docFreq=%d, maxDocs=%d)", docTerm, docTotal),
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}
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}
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return &rv
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}
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func (s *TermQueryScorer) Weight() float64 {
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sum := s.queryBoost * s.idf
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return sum * sum
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}
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func (s *TermQueryScorer) SetQueryNorm(qnorm float64) {
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s.queryNorm = qnorm
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// update the query weight
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s.queryWeight = s.queryBoost * s.idf * s.queryNorm
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if s.explain {
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childrenExplanations := make([]*search.Explanation, 3)
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childrenExplanations[0] = &search.Explanation{
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Value: s.queryBoost,
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Message: "boost",
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}
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childrenExplanations[1] = s.idfExplanation
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childrenExplanations[2] = &search.Explanation{
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Value: s.queryNorm,
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Message: "queryNorm",
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}
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s.queryWeightExplanation = &search.Explanation{
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Value: s.queryWeight,
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Message: fmt.Sprintf("queryWeight(%s:%s^%f), product of:", s.queryField, string(s.queryTerm), s.queryBoost),
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Children: childrenExplanations,
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}
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}
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}
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func (s *TermQueryScorer) Score(termMatch *index.TermFieldDoc) *search.DocumentMatch {
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var scoreExplanation *search.Explanation
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// need to compute score
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var tf float64
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if termMatch.Freq < MAX_SQRT_CACHE {
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tf = SQRT_CACHE[int(termMatch.Freq)]
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} else {
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tf = math.Sqrt(float64(termMatch.Freq))
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}
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score := tf * termMatch.Norm * s.idf
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if s.explain {
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childrenExplanations := make([]*search.Explanation, 3)
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childrenExplanations[0] = &search.Explanation{
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Value: tf,
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Message: fmt.Sprintf("tf(termFreq(%s:%s)=%d", s.queryField, string(s.queryTerm), termMatch.Freq),
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}
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childrenExplanations[1] = &search.Explanation{
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Value: termMatch.Norm,
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Message: fmt.Sprintf("fieldNorm(field=%s, doc=%s)", s.queryField, termMatch.ID),
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}
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childrenExplanations[2] = s.idfExplanation
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scoreExplanation = &search.Explanation{
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Value: score,
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Message: fmt.Sprintf("fieldWeight(%s:%s in %s), product of:", s.queryField, string(s.queryTerm), termMatch.ID),
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Children: childrenExplanations,
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}
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}
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// if the query weight isn't 1, multiply
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if s.queryWeight != 1.0 {
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score = score * s.queryWeight
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if s.explain {
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childExplanations := make([]*search.Explanation, 2)
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childExplanations[0] = s.queryWeightExplanation
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childExplanations[1] = scoreExplanation
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scoreExplanation = &search.Explanation{
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Value: score,
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Message: fmt.Sprintf("weight(%s:%s^%f in %s), product of:", s.queryField, string(s.queryTerm), s.queryBoost, termMatch.ID),
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Children: childExplanations,
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}
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}
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}
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rv := search.DocumentMatch{
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ID: termMatch.ID,
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Score: score,
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}
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if s.explain {
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rv.Expl = scoreExplanation
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}
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if termMatch.Vectors != nil && len(termMatch.Vectors) > 0 {
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rv.Locations = make(search.FieldTermLocationMap)
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for _, v := range termMatch.Vectors {
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tlm := rv.Locations[v.Field]
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if tlm == nil {
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tlm = make(search.TermLocationMap)
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}
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loc := search.Location{
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Pos: float64(v.Pos),
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Start: float64(v.Start),
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End: float64(v.End),
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}
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locations := tlm[s.queryTerm]
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if locations == nil {
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locations = make(search.Locations, 1)
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locations[0] = &loc
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} else {
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locations = append(locations, &loc)
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}
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tlm[s.queryTerm] = locations
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rv.Locations[v.Field] = tlm
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}
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}
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return &rv
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}
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