f8fdfebb6c
- TermSearcher has alternate constructor if term is []byte, this can avoid copying in some cases. TermScorer updated to accept []byte term. Also removed a few struct fields which were not being used. - New MultiTermSearcher searches for documents containing any of a list of terms. Current implementation simply uses DisjunctionSearcher. - Several other searcher constructors now simply build a list of terms and then delegate to the MultiTermSearcher - NewPrefixSearcher - NewRegexpSearcher - NewFuzzySearcher - NewNumericRangeSearcher - NewGeoBoundingBoxSearcher and NewGeoPointDistanceSearcher make use of the MultiTermSearcher internally, and follow the pattern of returning an existing search.Searcher, as opposed to their own wrapping struct. - Callback filter functions used in NewGeoBoundingBoxSearcher and NewGeoPointDistanceSearcher have been extracted into separate functions which makes the code much easier to read.
183 lines
5.2 KiB
Go
183 lines
5.2 KiB
Go
// Copyright (c) 2014 Couchbase, Inc.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package scorer
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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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type TermQueryScorer struct {
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queryTerm []byte
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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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options search.SearcherOptions
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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 []byte, queryField string, queryBoost float64, docTotal, docTerm uint64, options search.SearcherOptions) *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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options: options,
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queryWeight: 1.0,
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}
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if options.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.options.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(ctx *search.SearchContext, 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 < MaxSqrtCache {
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tf = SqrtCache[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.options.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.options.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 := ctx.DocumentMatchPool.Get()
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rv.IndexInternalID = append(rv.IndexInternalID, termMatch.ID...)
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rv.Score = score
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if s.options.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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locs := make([]search.Location, len(termMatch.Vectors))
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locsUsed := 0
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totalPositions := 0
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for _, v := range termMatch.Vectors {
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totalPositions += len(v.ArrayPositions)
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}
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positions := make(search.ArrayPositions, totalPositions)
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positionsUsed := 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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rv.Locations[v.Field] = tlm
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}
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loc := &locs[locsUsed]
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locsUsed++
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loc.Pos = v.Pos
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loc.Start = v.Start
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loc.End = v.End
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if len(v.ArrayPositions) > 0 {
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loc.ArrayPositions = positions[positionsUsed : positionsUsed+len(v.ArrayPositions)]
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for i, ap := range v.ArrayPositions {
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loc.ArrayPositions[i] = ap
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}
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positionsUsed += len(v.ArrayPositions)
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}
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tlm[string(s.queryTerm)] = append(tlm[string(s.queryTerm)], loc)
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}
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}
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return rv
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}
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