0
0
bleve/search/scorers/scorer_term_test.go
Marty Schoch ce0b299d6f switch sort impl to use interface
this improves perf in the case where we're not doing any sorting
as we avoid allocating memory and converting scores into
numeric terms
2016-08-24 19:02:22 -04:00

252 lines
6.3 KiB
Go

// Copyright (c) 2013 Couchbase, Inc.
// Licensed 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 scorers
import (
"math"
"reflect"
"testing"
"github.com/blevesearch/bleve/index"
"github.com/blevesearch/bleve/search"
)
func TestTermScorer(t *testing.T) {
var docTotal uint64 = 100
var docTerm uint64 = 9
var queryTerm = "beer"
var queryField = "desc"
var queryBoost = 1.0
scorer := NewTermQueryScorer(queryTerm, queryField, queryBoost, docTotal, docTerm, true)
idf := 1.0 + math.Log(float64(docTotal)/float64(docTerm+1.0))
tests := []struct {
termMatch *index.TermFieldDoc
result *search.DocumentMatch
}{
// test some simple math
{
termMatch: &index.TermFieldDoc{
ID: index.IndexInternalID("one"),
Freq: 1,
Norm: 1.0,
Vectors: []*index.TermFieldVector{
{
Field: "desc",
Pos: 1,
Start: 0,
End: 4,
},
},
},
result: &search.DocumentMatch{
IndexInternalID: index.IndexInternalID("one"),
Score: math.Sqrt(1.0) * idf,
Sort: []interface{}{},
Expl: &search.Explanation{
Value: math.Sqrt(1.0) * idf,
Message: "fieldWeight(desc:beer in one), product of:",
Children: []*search.Explanation{
{
Value: 1,
Message: "tf(termFreq(desc:beer)=1",
},
{
Value: 1,
Message: "fieldNorm(field=desc, doc=one)",
},
{
Value: idf,
Message: "idf(docFreq=9, maxDocs=100)",
},
},
},
Locations: search.FieldTermLocationMap{
"desc": search.TermLocationMap{
"beer": []*search.Location{
{
Pos: 1,
Start: 0,
End: 4,
},
},
},
},
},
},
// test the same thing again (score should be cached this time)
{
termMatch: &index.TermFieldDoc{
ID: index.IndexInternalID("one"),
Freq: 1,
Norm: 1.0,
},
result: &search.DocumentMatch{
IndexInternalID: index.IndexInternalID("one"),
Score: math.Sqrt(1.0) * idf,
Sort: []interface{}{},
Expl: &search.Explanation{
Value: math.Sqrt(1.0) * idf,
Message: "fieldWeight(desc:beer in one), product of:",
Children: []*search.Explanation{
{
Value: 1,
Message: "tf(termFreq(desc:beer)=1",
},
{
Value: 1,
Message: "fieldNorm(field=desc, doc=one)",
},
{
Value: idf,
Message: "idf(docFreq=9, maxDocs=100)",
},
},
},
},
},
// test a case where the sqrt isn't precalculated
{
termMatch: &index.TermFieldDoc{
ID: index.IndexInternalID("one"),
Freq: 65,
Norm: 1.0,
},
result: &search.DocumentMatch{
IndexInternalID: index.IndexInternalID("one"),
Score: math.Sqrt(65) * idf,
Sort: []interface{}{},
Expl: &search.Explanation{
Value: math.Sqrt(65) * idf,
Message: "fieldWeight(desc:beer in one), product of:",
Children: []*search.Explanation{
{
Value: math.Sqrt(65),
Message: "tf(termFreq(desc:beer)=65",
},
{
Value: 1,
Message: "fieldNorm(field=desc, doc=one)",
},
{
Value: idf,
Message: "idf(docFreq=9, maxDocs=100)",
},
},
},
},
},
}
for _, test := range tests {
ctx := &search.SearchContext{
DocumentMatchPool: search.NewDocumentMatchPool(1, 0),
}
actual := scorer.Score(ctx, test.termMatch)
if !reflect.DeepEqual(actual, test.result) {
t.Errorf("expected %#v got %#v for %#v", test.result, actual, test.termMatch)
}
}
}
func TestTermScorerWithQueryNorm(t *testing.T) {
var docTotal uint64 = 100
var docTerm uint64 = 9
var queryTerm = "beer"
var queryField = "desc"
var queryBoost = 3.0
scorer := NewTermQueryScorer(queryTerm, queryField, queryBoost, docTotal, docTerm, true)
idf := 1.0 + math.Log(float64(docTotal)/float64(docTerm+1.0))
scorer.SetQueryNorm(2.0)
expectedQueryWeight := 3 * idf * 3 * idf
actualQueryWeight := scorer.Weight()
if expectedQueryWeight != actualQueryWeight {
t.Errorf("expected query weight %f, got %f", expectedQueryWeight, actualQueryWeight)
}
tests := []struct {
termMatch *index.TermFieldDoc
result *search.DocumentMatch
}{
{
termMatch: &index.TermFieldDoc{
ID: index.IndexInternalID("one"),
Freq: 1,
Norm: 1.0,
},
result: &search.DocumentMatch{
IndexInternalID: index.IndexInternalID("one"),
Score: math.Sqrt(1.0) * idf * 3.0 * idf * 2.0,
Sort: []interface{}{},
Expl: &search.Explanation{
Value: math.Sqrt(1.0) * idf * 3.0 * idf * 2.0,
Message: "weight(desc:beer^3.000000 in one), product of:",
Children: []*search.Explanation{
{
Value: 2.0 * idf * 3.0,
Message: "queryWeight(desc:beer^3.000000), product of:",
Children: []*search.Explanation{
{
Value: 3,
Message: "boost",
},
{
Value: idf,
Message: "idf(docFreq=9, maxDocs=100)",
},
{
Value: 2,
Message: "queryNorm",
},
},
},
{
Value: math.Sqrt(1.0) * idf,
Message: "fieldWeight(desc:beer in one), product of:",
Children: []*search.Explanation{
{
Value: 1,
Message: "tf(termFreq(desc:beer)=1",
},
{
Value: 1,
Message: "fieldNorm(field=desc, doc=one)",
},
{
Value: idf,
Message: "idf(docFreq=9, maxDocs=100)",
},
},
},
},
},
},
},
}
for _, test := range tests {
ctx := &search.SearchContext{
DocumentMatchPool: search.NewDocumentMatchPool(1, 0),
}
actual := scorer.Score(ctx, test.termMatch)
if !reflect.DeepEqual(actual, test.result) {
t.Errorf("expected %#v got %#v for %#v", test.result, actual, test.termMatch)
}
}
}