From 147574e5560783f9a36b88a4e971bd99f4394556 Mon Sep 17 00:00:00 2001 From: CascadingRadium Date: Thu, 16 Nov 2023 19:48:29 +0530 Subject: [PATCH 01/10] merge KNN --- index_alias_impl.go | 31 +- knn_test.go | 422 + search/scorer/scorer_conjunction.go | 4 +- search/scorer/scorer_disjunction.go | 12 +- search/scorer/scorer_knn.go | 8 + search/search.go | 2 + search/searcher/ordered_searchers_list.go | 12 +- search/searcher/search_conjunction.go | 13 +- search/searcher/search_disjunction_heap.go | 15 +- search/searcher/search_disjunction_slice.go | 19 +- search/util.go | 1 + search_knn.go | 93 + search_no_knn.go | 3 + test/tests/knn/dataset-30-docs.json | 11702 ++++++++++++++++++ test/tests/knn/small-query.json | 1606 +++ 15 files changed, 13920 insertions(+), 23 deletions(-) create mode 100644 knn_test.go create mode 100644 test/tests/knn/dataset-30-docs.json create mode 100644 test/tests/knn/small-query.json diff --git a/index_alias_impl.go b/index_alias_impl.go index ccb52f244..a2e1392d4 100644 --- a/index_alias_impl.go +++ b/index_alias_impl.go @@ -25,10 +25,11 @@ import ( ) type indexAliasImpl struct { - name string - indexes []Index - mutex sync.RWMutex - open bool + name string + indexes []Index + mutex sync.RWMutex + open bool + partitionedMode bool } // NewIndexAlias creates a new IndexAlias over the provided @@ -41,6 +42,10 @@ func NewIndexAlias(indexes ...Index) *indexAliasImpl { } } +func (i *indexAliasImpl) SetPartitionedMode(partitionedMode bool) { + i.partitionedMode = partitionedMode +} + // VisitIndexes invokes the visit callback on every // indexes included in the index alias. func (i *indexAliasImpl) VisitIndexes(visit func(Index)) { @@ -166,6 +171,7 @@ func (i *indexAliasImpl) SearchInContext(ctx context.Context, req *SearchRequest return i.indexes[0].SearchInContext(ctx, req) } + ctx = context.WithValue(ctx, search.AliasPartitionedModeKey, i.partitionedMode) return MultiSearch(ctx, req, i.indexes...) } @@ -504,6 +510,23 @@ func MultiSearch(ctx context.Context, req *SearchRequest, indexes ...Index) (*Se } } + if mode := ctx.Value(search.AliasPartitionedModeKey); mode != nil { + aliasForPartitionedIndex, ok := mode.(bool) + if ok && aliasForPartitionedIndex && len(indexes) > 1 { + // this is an alias for a partitioned index, where each child index + // is a partition of a larger index. + // when knn queries are present we need to perform + // a special merge of the hits to ensure that hits corresponding to the + // knn queries are representative of the entire index, not just the + // partition that was searched. If k is 2 and there are 3 partitions, + // then the top 2 hits from each partition is returned, resulting in + // 6 hits in total. This is incorrect because k=2 should return the + // top 2 hits from the entire index, not the top 2 hits from each + // partition. + mergeKNNResults(req, sr) + } + } + sortFunc := req.SortFunc() // sort all hits with the requested order if len(req.Sort) > 0 { diff --git a/knn_test.go b/knn_test.go new file mode 100644 index 000000000..8efd6144c --- /dev/null +++ b/knn_test.go @@ -0,0 +1,422 @@ +// Copyright (c) 2023 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. + +//go:build vectors +// +build vectors + +package bleve + +import ( + "encoding/json" + "math/rand" + "os" + "testing" + + "github.com/blevesearch/bleve/v2/mapping" +) + +const testDatasetFileName = "test/tests/knn/dataset-30-docs.json" +const testQueryFileName = "test/tests/knn/small-query.json" + +const testDatasetDims = 384 + +const randomizeDocuments = false + +type testDocument struct { + ID string `json:"id"` + Content string `json:"content"` + Vector []float64 `json:"vector"` +} + +func createVectorDataset(datasetFileName string) ([]testDocument, error) { + var dataset []testDocument + datasetFileData, err := os.ReadFile(datasetFileName) + if err != nil { + return nil, err + } + err = json.Unmarshal(datasetFileData, &dataset) + if err != nil { + return nil, err + } + return dataset, nil +} + +func makeDatasetIntoDocuments(dataset []testDocument) []map[string]interface{} { + documents := make([]map[string]interface{}, len(dataset)) + for i := 0; i < len(dataset); i++ { + document := make(map[string]interface{}) + document["id"] = dataset[i].ID + document["content"] = dataset[i].Content + document["vector"] = dataset[i].Vector + documents[i] = document + } + return documents +} + +func getSearchRequests(queryFileName string) ([]*SearchRequest, error) { + var reqArr []*SearchRequest + queryFileData, err := os.ReadFile(queryFileName) + if err != nil { + return nil, err + } + err = json.Unmarshal(queryFileData, &reqArr) + if err != nil { + return nil, err + } + return reqArr, nil +} + +func cleanUp(t *testing.T, indexPaths []string, indexes ...Index) { + for _, childIndex := range indexes { + err := childIndex.Close() + if err != nil { + t.Fatal(err) + } + } + for _, indexPath := range indexPaths { + cleanupTmpIndexPath(t, indexPath) + } +} + +func createPartitionedIndex(documents []map[string]interface{}, index *indexAliasImpl, numPartitions int, + mapping mapping.IndexMapping, t *testing.T) []string { + + partitionSize := len(documents) / numPartitions + var rv []string + for i := 0; i < numPartitions; i++ { + tmpIndexPath := createTmpIndexPath(t) + rv = append(rv, tmpIndexPath) + childIndex, err := New(tmpIndexPath, mapping) + if err != nil { + cleanUp(t, rv) + t.Fatal(err) + } + batch := childIndex.NewBatch() + for j := i * partitionSize; (j < (i+1)*partitionSize) && j < len(documents); j++ { + doc := documents[j] + err := batch.Index(doc["id"].(string), doc) + if err != nil { + cleanUp(t, rv) + t.Fatal(err) + } + } + err = childIndex.Batch(batch) + if err != nil { + cleanUp(t, rv) + t.Fatal(err) + } + index.Add(childIndex) + } + return rv +} + +// Fisher-Yates shuffle +func shuffleDocuments(documents []map[string]interface{}) []map[string]interface{} { + for i := range documents { + j := i + rand.Intn(len(documents)-i) + documents[i], documents[j] = documents[j], documents[i] + } + return documents +} + +func truncateScore(score float64) float64 { + return float64(int(score*1e6)) / 1e6 +} + +func TestSimilaritySearchQuery(t *testing.T) { + + dataset, err := createVectorDataset(testDatasetFileName) + if err != nil { + t.Fatal(err) + } + documents := makeDatasetIntoDocuments(dataset) + if randomizeDocuments { + documents = shuffleDocuments(documents) + } + searchRequests, err := getSearchRequests(testQueryFileName) + if err != nil { + t.Fatal(err) + } + + indexMapping := NewIndexMapping() + contentFieldMapping := NewTextFieldMapping() + contentFieldMapping.Analyzer = "en" + + vecFieldMapping := mapping.NewVectorFieldMapping() + vecFieldMapping.Dims = testDatasetDims + vecFieldMapping.Similarity = "l2_norm" + + indexMapping.DefaultMapping.AddFieldMappingsAt("content", contentFieldMapping) + indexMapping.DefaultMapping.AddFieldMappingsAt("vector", vecFieldMapping) + + index := NewIndexAlias() + index.SetPartitionedMode(true) + + type testResult struct { + score float64 + scoreBreakdown []float64 + } + + type testCase struct { + queryIndex int + numIndexPartitions int + expectedResults map[string]testResult + } + + testCases := []testCase{ + { + queryIndex: 0, + numIndexPartitions: 1, + expectedResults: map[string]testResult{ + "doc29": { + score: 0.5547758085810349, + scoreBreakdown: []float64{0, 1.1095516171620698}, + }, + "doc23": { + score: 0.3817633037007331, + scoreBreakdown: []float64{0, 0.7635266074014662}, + }, + "doc28": { + score: 0.33983667469689355, + scoreBreakdown: []float64{0, 0.6796733493937871}, + }, + }, + }, + { + queryIndex: 0, + numIndexPartitions: 4, + expectedResults: map[string]testResult{ + "doc23": { + score: 0.3817633037007331, + scoreBreakdown: []float64{0, 0.7635266074014662}, + }, + "doc28": { + score: 0.33983667469689355, + scoreBreakdown: []float64{0, 0.6796733493937871}, + }, + "doc13": { + score: 0.3206958457835452, + scoreBreakdown: []float64{0, 0.6413916915670904}, + }, + }, + }, + { + queryIndex: 0, + numIndexPartitions: 10, + expectedResults: map[string]testResult{ + "doc29": { + score: 0.554775, + scoreBreakdown: []float64{0, 1.109551}, + }, + "doc23": { + score: 0.381763, + scoreBreakdown: []float64{0, 0.763526}, + }, + "doc28": { + score: 0.339836, + scoreBreakdown: []float64{0, 0.679673}, + }, + }, + }, + { + queryIndex: 1, + numIndexPartitions: 1, + expectedResults: map[string]testResult{ + "doc23": { + score: 1.304929, + scoreBreakdown: []float64{1.016928, 0.288001}, + }, + "doc29": { + score: 1.137598, + scoreBreakdown: []float64{0.719076, 0.418521}, + }, + "doc27": { + score: 0.429730, + scoreBreakdown: []float64{0.859461, 0}, + }, + "doc28": { + score: 0.401976, + scoreBreakdown: []float64{0.803952, 0}, + }, + "doc30": { + score: 0.359538, + scoreBreakdown: []float64{0.719076, 0}, + }, + "doc24": { + score: 0.359538, + scoreBreakdown: []float64{0.719076, 0}, + }, + }, + }, + { + queryIndex: 1, + numIndexPartitions: 5, + expectedResults: map[string]testResult{ + "doc29": { + score: 1.0019961733597083, + scoreBreakdown: []float64{0.28546778431249004, 0.7165283890472183}, + }, + "doc28": { + score: 0.758083452201489, + scoreBreakdown: []float64{0.3191626822375969, 0.4389207699638921}, + }, + "doc23": { + score: 0.32598793043274804, + scoreBreakdown: []float64{0.6519758608654961, 0}, + }, + "doc24": { + score: 0.2305082774045959, + scoreBreakdown: []float64{0.4610165548091918, 0}, + }, + "doc27": { + score: 0.17059962977552257, + scoreBreakdown: []float64{0.34119925955104513, 0}, + }, + "doc30": { + score: 0.14273389215624502, + scoreBreakdown: []float64{0.28546778431249004, 0}, + }, + }, + }, + { + queryIndex: 2, + numIndexPartitions: 1, + expectedResults: map[string]testResult{ + "doc7": { + score: 3333.333333333333, + scoreBreakdown: []float64{0, 0, 10000}, + }, + "doc23": { + score: 0.3234943403006508, + scoreBreakdown: []float64{0.30977843187823456, 0.1754630785727416, 0}, + }, + "doc29": { + score: 0.31601878039486375, + scoreBreakdown: []float64{0.21904643099686824, 0.2549817395954274, 0}, + }, + "doc3": { + score: 0.24118912169729392, + scoreBreakdown: []float64{0.7235673650918818, 0, 0}, + }, + "doc13": { + score: 0.20887591025526625, + scoreBreakdown: []float64{0.6266277307657988, 0, 0}, + }, + "doc27": { + score: 0.08727018618864227, + scoreBreakdown: []float64{0.26181055856592683, 0, 0}, + }, + "doc28": { + score: 0.0816337841412418, + scoreBreakdown: []float64{0.2449013524237254, 0, 0}, + }, + "doc24": { + score: 0.07301547699895608, + scoreBreakdown: []float64{0.21904643099686824, 0, 0}, + }, + "doc30": { + score: 0.07301547699895608, + scoreBreakdown: []float64{0.21904643099686824, 0, 0}, + }, + "doc5": { + score: 0.06883694922797147, + scoreBreakdown: []float64{0, 0, 0.20651084768391442}, + }, + }, + }, + { + queryIndex: 2, + numIndexPartitions: 4, + expectedResults: map[string]testResult{ + "doc7": { + score: 3333.333333333333, + scoreBreakdown: []float64{0, 0, 10000}, + }, + "doc23": { + score: 0.2195946458144798, + scoreBreakdown: []float64{0.11312710434186327, 0.21626486437985648, 0}, + }, + "doc28": { + score: 0.18796580117926376, + scoreBreakdown: []float64{0.08943482824521586, 0.1925138735236798, 0}, + }, + "doc3": { + score: 0.12303621410516037, + scoreBreakdown: []float64{0.36910864231548113, 0, 0}, + }, + "doc13": { + score: 0.10655248891295889, + scoreBreakdown: []float64{0.3196574667388767, 0, 0}, + }, + "doc5": { + score: 0.07546992065969621, + scoreBreakdown: []float64{0, 0, 0.22640976197908863}, + }, + "doc27": { + score: 0.03186995104545246, + scoreBreakdown: []float64{0.09560985313635739, 0, 0}, + }, + "doc24": { + score: 0.02666431434541773, + scoreBreakdown: []float64{0.07999294303625319, 0, 0}, + }, + }, + }, + } + + for testCaseNum, testCase := range testCases { + index.indexes = make([]Index, 0) + indexPaths := createPartitionedIndex(documents, index, testCase.numIndexPartitions, indexMapping, t) + query := searchRequests[testCase.queryIndex] + res, err := index.Search(query) + if err != nil { + t.Fatal(err) + } + if len(res.Hits) != len(testCase.expectedResults) { + t.Fatalf("testcase %d failed: expected %d results, got %d", testCaseNum, len(testCase.expectedResults), len(res.Hits)) + } + for i, hit := range res.Hits { + var expectedHit testResult + var ok bool + if expectedHit, ok = testCase.expectedResults[hit.ID]; !ok { + t.Fatalf("testcase %d failed: unexpected result %s", testCaseNum, hit.ID) + } + // Truncate to 6 decimal places + actualScore := truncateScore(hit.Score) + expectScore := truncateScore(expectedHit.score) + if !randomizeDocuments && expectScore != actualScore { + t.Fatalf("testcase %d failed: expected hit %d to have score %f, got %f", testCaseNum, i, expectedHit.score, hit.Score) + } + if len(hit.ScoreBreakdown) != len(expectedHit.scoreBreakdown) { + t.Fatalf("testcase %d failed: expected hit %d to have %d score breakdowns, got %d", testCaseNum, i, len(expectedHit.scoreBreakdown), len(hit.ScoreBreakdown)) + } + if !randomizeDocuments { + actualScore := truncateScore(hit.ScoreBreakdown[0]) + expectScore := truncateScore(expectedHit.scoreBreakdown[0]) + if expectScore != actualScore { + t.Fatalf("testcase %d failed: expected hit %d to have score breakdown %f, got %f", testCaseNum, i, expectedHit.scoreBreakdown[0], hit.ScoreBreakdown[0]) + } + } + for j := 1; j < len(hit.ScoreBreakdown); j++ { + // Truncate to 6 decimal places + actualScore := truncateScore(hit.ScoreBreakdown[j]) + expectScore := truncateScore(expectedHit.scoreBreakdown[j]) + if expectScore != actualScore { + t.Fatalf("testcase %d failed: expected hit %d to have score breakdown %f, got %f", testCaseNum, i, expectedHit.scoreBreakdown[j], hit.ScoreBreakdown[j]) + } + } + } + cleanUp(t, indexPaths, index.indexes...) + } +} diff --git a/search/scorer/scorer_conjunction.go b/search/scorer/scorer_conjunction.go index f3c81a78c..771aba9b7 100644 --- a/search/scorer/scorer_conjunction.go +++ b/search/scorer/scorer_conjunction.go @@ -48,9 +48,10 @@ func (s *ConjunctionQueryScorer) Score(ctx *search.SearchContext, constituents [ if s.options.Explain { childrenExplanations = make([]*search.Explanation, len(constituents)) } - + scoreBreakdown := make([]float64, len(constituents)) for i, docMatch := range constituents { sum += docMatch.Score + scoreBreakdown[i] = docMatch.Score if s.options.Explain { childrenExplanations[i] = docMatch.Expl } @@ -65,6 +66,7 @@ func (s *ConjunctionQueryScorer) Score(ctx *search.SearchContext, constituents [ rv := constituents[0] rv.Score = newScore rv.Expl = newExpl + rv.ScoreBreakdown = scoreBreakdown rv.FieldTermLocations = search.MergeFieldTermLocations( rv.FieldTermLocations, constituents[1:]) diff --git a/search/scorer/scorer_disjunction.go b/search/scorer/scorer_disjunction.go index 054e76fd4..db79025ff 100644 --- a/search/scorer/scorer_disjunction.go +++ b/search/scorer/scorer_disjunction.go @@ -43,15 +43,22 @@ func NewDisjunctionQueryScorer(options search.SearcherOptions) *DisjunctionQuery } } -func (s *DisjunctionQueryScorer) Score(ctx *search.SearchContext, constituents []*search.DocumentMatch, countMatch, countTotal int) *search.DocumentMatch { +func (s *DisjunctionQueryScorer) Score(ctx *search.SearchContext, constituents []*search.DocumentMatch, countMatch, countTotal int, + matchingIdxs []int, originalPositions []int) *search.DocumentMatch { + var sum float64 var childrenExplanations []*search.Explanation if s.options.Explain { childrenExplanations = make([]*search.Explanation, len(constituents)) } - + scoreBreakdown := make([]float64, countTotal) for i, docMatch := range constituents { sum += docMatch.Score + if originalPositions != nil { + scoreBreakdown[originalPositions[matchingIdxs[i]]] = docMatch.Score + } else { + scoreBreakdown[matchingIdxs[i]] = docMatch.Score + } if s.options.Explain { childrenExplanations[i] = docMatch.Expl } @@ -75,6 +82,7 @@ func (s *DisjunctionQueryScorer) Score(ctx *search.SearchContext, constituents [ // reuse constituents[0] as the return value rv := constituents[0] rv.Score = newScore + rv.ScoreBreakdown = scoreBreakdown rv.Expl = newExpl rv.FieldTermLocations = search.MergeFieldTermLocations( rv.FieldTermLocations, constituents[1:]) diff --git a/search/scorer/scorer_knn.go b/search/scorer/scorer_knn.go index 511a47ecb..ae50c77d5 100644 --- a/search/scorer/scorer_knn.go +++ b/search/scorer/scorer_knn.go @@ -18,6 +18,7 @@ package scorer import ( + "math" "reflect" "github.com/blevesearch/bleve/v2/search" @@ -27,6 +28,8 @@ import ( var reflectStaticSizeKNNQueryScorer int +const MaxAllowedScore = 10000.0 + func init() { var sqs KNNQueryScorer reflectStaticSizeKNNQueryScorer = int(reflect.TypeOf(sqs).Size()) @@ -80,6 +83,11 @@ func (sqs *KNNQueryScorer) Score(ctx *search.SearchContext, } if sqs.includeScore { + if math.IsInf(score, 1) { + score = MaxAllowedScore // MAX ALLOWED SCORE + } else if math.IsInf(score, -1) { + score = 0.0 + } rv.Score = score } diff --git a/search/search.go b/search/search.go index b7a3c42ae..aa38a2283 100644 --- a/search/search.go +++ b/search/search.go @@ -173,6 +173,8 @@ type DocumentMatch struct { // not all sub-queries matched // if false, all the sub-queries matched PartialMatch bool `json:"partial_match,omitempty"` + + ScoreBreakdown []float64 `json:"score_breakdown,omitempty"` } func (dm *DocumentMatch) AddFieldValue(name string, value interface{}) { diff --git a/search/searcher/ordered_searchers_list.go b/search/searcher/ordered_searchers_list.go index f3e646e9d..4e9409224 100644 --- a/search/searcher/ordered_searchers_list.go +++ b/search/searcher/ordered_searchers_list.go @@ -18,18 +18,22 @@ import ( "github.com/blevesearch/bleve/v2/search" ) -type OrderedSearcherList []search.Searcher +type OrderedSearcherList struct { + searchers []search.Searcher + index []int +} // sort.Interface func (otrl OrderedSearcherList) Len() int { - return len(otrl) + return len(otrl.searchers) } func (otrl OrderedSearcherList) Less(i, j int) bool { - return otrl[i].Count() < otrl[j].Count() + return otrl.searchers[i].Count() < otrl.searchers[j].Count() } func (otrl OrderedSearcherList) Swap(i, j int) { - otrl[i], otrl[j] = otrl[j], otrl[i] + otrl.searchers[i], otrl.searchers[j] = otrl.searchers[j], otrl.searchers[i] + otrl.index[i], otrl.index[j] = otrl.index[j], otrl.index[i] } diff --git a/search/searcher/search_conjunction.go b/search/searcher/search_conjunction.go index 19ef199ac..e0ae2c349 100644 --- a/search/searcher/search_conjunction.go +++ b/search/searcher/search_conjunction.go @@ -35,7 +35,7 @@ func init() { type ConjunctionSearcher struct { indexReader index.IndexReader - searchers OrderedSearcherList + searchers []search.Searcher queryNorm float64 currs []*search.DocumentMatch maxIDIdx int @@ -49,11 +49,16 @@ func NewConjunctionSearcher(ctx context.Context, indexReader index.IndexReader, qsearchers []search.Searcher, options search.SearcherOptions) ( search.Searcher, error) { // build the sorted downstream searchers - searchers := make(OrderedSearcherList, len(qsearchers)) + sortedSearchers := &OrderedSearcherList{ + searchers: make([]search.Searcher, len(qsearchers)), + index: make([]int, len(qsearchers)), + } for i, searcher := range qsearchers { - searchers[i] = searcher + sortedSearchers.searchers[i] = searcher + sortedSearchers.index[i] = i } - sort.Sort(searchers) + sort.Sort(sortedSearchers) + searchers := sortedSearchers.searchers // attempt the "unadorned" conjunction optimization only when we // do not need extra information like freq-norm's or term vectors diff --git a/search/searcher/search_disjunction_heap.go b/search/searcher/search_disjunction_heap.go index d36e30131..af5915934 100644 --- a/search/searcher/search_disjunction_heap.go +++ b/search/searcher/search_disjunction_heap.go @@ -39,8 +39,9 @@ func init() { } type SearcherCurr struct { - searcher search.Searcher - curr *search.DocumentMatch + searcher search.Searcher + curr *search.DocumentMatch + matchingIdx int } type DisjunctionHeapSearcher struct { @@ -55,6 +56,7 @@ type DisjunctionHeapSearcher struct { heap []*SearcherCurr matching []*search.DocumentMatch + matchingIdxs []int matchingCurrs []*SearcherCurr bytesRead uint64 @@ -77,6 +79,7 @@ func newDisjunctionHeapSearcher(ctx context.Context, indexReader index.IndexRead min: int(min), matching: make([]*search.DocumentMatch, len(searchers)), matchingCurrs: make([]*SearcherCurr, len(searchers)), + matchingIdxs: make([]int, len(searchers)), heap: make([]*SearcherCurr, 0, len(searchers)), } rv.computeQueryNorm() @@ -101,6 +104,7 @@ func (s *DisjunctionHeapSearcher) Size() int { // since searchers and document matches already counted above sizeInBytes += len(s.matchingCurrs) * reflectStaticSizeSearcherCurr sizeInBytes += len(s.heap) * reflectStaticSizeSearcherCurr + sizeInBytes += len(s.matchingIdxs) * size.SizeOfInt return sizeInBytes } @@ -132,6 +136,7 @@ func (s *DisjunctionHeapSearcher) initSearchers(ctx *search.SearchContext) error if curr != nil { block[i].searcher = searcher block[i].curr = curr + block[i].matchingIdx = i heap.Push(s, &block[i]) } } @@ -147,6 +152,7 @@ func (s *DisjunctionHeapSearcher) initSearchers(ctx *search.SearchContext) error func (s *DisjunctionHeapSearcher) updateMatches() error { matching := s.matching[:0] matchingCurrs := s.matchingCurrs[:0] + matchingIdxs := s.matchingIdxs[:0] if len(s.heap) > 0 { @@ -154,17 +160,20 @@ func (s *DisjunctionHeapSearcher) updateMatches() error { next := heap.Pop(s).(*SearcherCurr) matching = append(matching, next.curr) matchingCurrs = append(matchingCurrs, next) + matchingIdxs = append(matchingIdxs, next.matchingIdx) // now as long as top of heap matches, keep popping for len(s.heap) > 0 && bytes.Compare(next.curr.IndexInternalID, s.heap[0].curr.IndexInternalID) == 0 { next = heap.Pop(s).(*SearcherCurr) matching = append(matching, next.curr) matchingCurrs = append(matchingCurrs, next) + matchingIdxs = append(matchingIdxs, next.matchingIdx) } } s.matching = matching s.matchingCurrs = matchingCurrs + s.matchingIdxs = matchingIdxs return nil } @@ -199,7 +208,7 @@ func (s *DisjunctionHeapSearcher) Next(ctx *search.SearchContext) ( found = true partialMatch := len(s.matching) != len(s.searchers) // score this match - rv = s.scorer.Score(ctx, s.matching, len(s.matching), s.numSearchers) + rv = s.scorer.Score(ctx, s.matching, len(s.matching), s.numSearchers, s.matchingIdxs, nil) rv.PartialMatch = partialMatch } diff --git a/search/searcher/search_disjunction_slice.go b/search/searcher/search_disjunction_slice.go index 0969c8cf3..fb9f7bab9 100644 --- a/search/searcher/search_disjunction_slice.go +++ b/search/searcher/search_disjunction_slice.go @@ -35,7 +35,8 @@ func init() { type DisjunctionSliceSearcher struct { indexReader index.IndexReader - searchers OrderedSearcherList + searchers []search.Searcher + originalPos []int numSearchers int queryNorm float64 currs []*search.DocumentMatch @@ -55,16 +56,24 @@ func newDisjunctionSliceSearcher(ctx context.Context, indexReader index.IndexRea return nil, tooManyClausesErr("", len(qsearchers)) } // build the downstream searchers - searchers := make(OrderedSearcherList, len(qsearchers)) + sortedSearchers := &OrderedSearcherList{ + searchers: make([]search.Searcher, len(qsearchers)), + index: make([]int, len(qsearchers)), + } for i, searcher := range qsearchers { - searchers[i] = searcher + sortedSearchers.searchers[i] = searcher + sortedSearchers.index[i] = i } // sort the searchers - sort.Sort(sort.Reverse(searchers)) + sort.Sort(sort.Reverse(sortedSearchers)) // build our searcher + searchers := sortedSearchers.searchers + originalPos := sortedSearchers.index + rv := DisjunctionSliceSearcher{ indexReader: indexReader, searchers: searchers, + originalPos: originalPos, numSearchers: len(searchers), currs: make([]*search.DocumentMatch, len(searchers)), scorer: scorer.NewDisjunctionQueryScorer(options), @@ -199,7 +208,7 @@ func (s *DisjunctionSliceSearcher) Next(ctx *search.SearchContext) ( found = true partialMatch := len(s.matching) != len(s.searchers) // score this match - rv = s.scorer.Score(ctx, s.matching, len(s.matching), s.numSearchers) + rv = s.scorer.Score(ctx, s.matching, len(s.matching), s.numSearchers, s.matchingIdxs, s.originalPos) rv.PartialMatch = partialMatch } diff --git a/search/util.go b/search/util.go index b2cb62a2d..92301cf9d 100644 --- a/search/util.go +++ b/search/util.go @@ -106,6 +106,7 @@ const ( const SearchIncrementalCostKey = "_search_incremental_cost_key" const QueryTypeKey = "_query_type_key" const FuzzyMatchPhraseKey = "_fuzzy_match_phrase_key" +const AliasPartitionedModeKey = "_alias_partitioned_mode_key" func RecordSearchCost(ctx context.Context, msg SearchIncrementalCostCallbackMsg, bytes uint64) { diff --git a/search_knn.go b/search_knn.go index a2f8d343c..260a1ded6 100644 --- a/search_knn.go +++ b/search_knn.go @@ -18,6 +18,7 @@ package bleve import ( + "container/heap" "encoding/json" "sort" @@ -163,3 +164,95 @@ func disjunctQueryWithKNN(req *SearchRequest) query.Query { } return req.Query } + +func mergeKNNResults(req *SearchRequest, sr *SearchResult) { + if len(req.KNN) > 0 { + mergeKNN(req, sr) + } +} + +// heap impl +type scoreHeap struct { + scoreBreakdown []*[]float64 + sortIndex int +} + +func (s *scoreHeap) Len() int { return len(s.scoreBreakdown) } + +func (s *scoreHeap) Less(i, j int) bool { + return (*s.scoreBreakdown[i])[s.sortIndex] > (*s.scoreBreakdown[j])[s.sortIndex] +} + +func (s *scoreHeap) Swap(i, j int) { + s.scoreBreakdown[i], s.scoreBreakdown[j] = s.scoreBreakdown[j], s.scoreBreakdown[i] +} + +func (s *scoreHeap) Push(x interface{}) { + s.scoreBreakdown = append(s.scoreBreakdown, x.(*[]float64)) +} + +func (s *scoreHeap) Pop() interface{} { + old := s.scoreBreakdown + n := len(old) + x := old[n-1] + s.scoreBreakdown = old[0 : n-1] + return x +} + +func mergeKNN(req *SearchRequest, sr *SearchResult) { + // index 0 of score breakdown is always tf-idf score + numKnnQuery := len(req.KNN) + maxHeap := &scoreHeap{ + scoreBreakdown: make([]*[]float64, 0), + } + for i := 0; i < numKnnQuery; i++ { + kVal := req.KNN[i].K + maxHeap.sortIndex = i + 1 + for _, hit := range sr.Hits { + heap.Push(maxHeap, &hit.ScoreBreakdown) + } + for maxHeap.Len() > 0 { + arr := heap.Pop(maxHeap).(*[]float64) + if kVal > 0 { + kVal-- + } else { + (*arr)[maxHeap.sortIndex] = 0 + } + } + } + operator := 0 + if _, ok := req.Query.(*query.ConjunctionQuery); ok { + operator = 1 + } + nonZeroScoreHits := make([]*search.DocumentMatch, 0, len(sr.Hits)) + maxScore := 0.0 + for _, hit := range sr.Hits { + newScore := recomputeTotalScore(operator, hit) + if newScore > 0 { + hit.Score = newScore + if newScore > maxScore { + maxScore = newScore + } + nonZeroScoreHits = append(nonZeroScoreHits, hit) + } + } + sr.Hits = nonZeroScoreHits + sr.MaxScore = maxScore + sr.Total = uint64(len(nonZeroScoreHits)) +} + +func recomputeTotalScore(operator int, hit *search.DocumentMatch) float64 { + totalScore := 0.0 + numNonZero := 0 + for _, score := range hit.ScoreBreakdown { + if score != 0 { + numNonZero += 1 + } + totalScore += score + } + if operator == 0 { + coord := float64(numNonZero) / float64(len(hit.ScoreBreakdown)) + totalScore = totalScore * coord + } + return totalScore +} diff --git a/search_no_knn.go b/search_no_knn.go index fb3814911..2e5107d0a 100644 --- a/search_no_knn.go +++ b/search_no_knn.go @@ -147,3 +147,6 @@ func copySearchRequest(req *SearchRequest) *SearchRequest { func disjunctQueryWithKNN(req *SearchRequest) query.Query { return req.Query } + +func mergeKNNResults(req *SearchRequest, sr *SearchResult) { +} diff --git a/test/tests/knn/dataset-30-docs.json b/test/tests/knn/dataset-30-docs.json new file mode 100644 index 000000000..e4d2c0b16 --- /dev/null +++ b/test/tests/knn/dataset-30-docs.json @@ -0,0 +1,11702 @@ +[ + { + "id": "doc1", + "content": "kathmandu the capital of nepal", + "vector": [ + 0.051617808640003204, + 0.07110562175512314, + -0.03424040600657463, + 0.1106891930103302, + 0.0018261136719956994, + -0.03148188441991806, + -0.01251516304910183, + -0.025826703757047653, + 0.004383699968457222, + 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0.04584376886487007, + 0.06740041822195053, + 0.014297358691692352, + 0.04067673534154892, + -0.08439884334802628, + -0.00020757854508701712, + 0.04320551082491875, + -0.11509723961353302, + -0.013486680574715137, + 0.05385909229516983, + 0.044806573539972305, + 0.01236815471202135, + -0.00783816259354353, + 0.038527775555849075, + 0.008104070089757442, + -0.006389702670276165, + 0.03476865589618683, + -0.010482197627425194, + 0.009332793764770031, + -0.10519538074731827, + 0.06614545732736588, + 0.019741922616958618, + 0.0753885954618454, + -0.12896087765693665, + -0.05029158666729927, + -0.03900384157896042, + 0.05102210491895676, + 0.01108368206769228, + 0.004489126615226269, + -0.021631181240081787, + -0.086960069835186, + -0.03269509971141815, + -0.015351544134318829, + 0.03236338123679161, + 0.021678868681192398, + -0.1128092035651207, + -0.09387856721878052, + 0.07662507891654968 + ], + "k":2 + }] + } +] + + From 8f0d8c1c6727b099485dff868b81e8d74bcb7027 Mon Sep 17 00:00:00 2001 From: CascadingRadium Date: Fri, 17 Nov 2023 13:28:37 +0530 Subject: [PATCH 02/10] fix scoring --- knn_test.go | 185 ++++++++++-------- search/searcher/search_conjunction.go | 34 +--- search/searcher/search_disjunction_heap.go | 30 +-- search/searcher/search_disjunction_slice.go | 40 ++-- search/searcher/search_knn_util.go | 72 +++++++ search/searcher/search_no_knn_util.go | 62 ++++++ .../knn_dataset.json} | 0 .../small-query.json => knn/knn_queries.json} | 6 +- 8 files changed, 273 insertions(+), 156 deletions(-) create mode 100644 search/searcher/search_knn_util.go create mode 100644 search/searcher/search_no_knn_util.go rename test/{tests/knn/dataset-30-docs.json => knn/knn_dataset.json} (100%) rename test/{tests/knn/small-query.json => knn/knn_queries.json} (99%) diff --git a/knn_test.go b/knn_test.go index 8efd6144c..b19b7005d 100644 --- a/knn_test.go +++ b/knn_test.go @@ -26,13 +26,11 @@ import ( "github.com/blevesearch/bleve/v2/mapping" ) -const testDatasetFileName = "test/tests/knn/dataset-30-docs.json" -const testQueryFileName = "test/tests/knn/small-query.json" +const testDatasetFileName = "test/knn/knn_dataset.json" +const testQueryFileName = "test/knn/knn_queries.json" const testDatasetDims = 384 -const randomizeDocuments = false - type testDocument struct { ID string `json:"id"` Content string `json:"content"` @@ -93,7 +91,17 @@ func createPartitionedIndex(documents []map[string]interface{}, index *indexAlia mapping mapping.IndexMapping, t *testing.T) []string { partitionSize := len(documents) / numPartitions + extraDocs := len(documents) % numPartitions + docsPerPartition := make([]int, numPartitions) + for i := 0; i < numPartitions; i++ { + docsPerPartition[i] = partitionSize + if extraDocs > 0 { + docsPerPartition[i]++ + extraDocs-- + } + } var rv []string + prevCutoff := 0 for i := 0; i < numPartitions; i++ { tmpIndexPath := createTmpIndexPath(t) rv = append(rv, tmpIndexPath) @@ -103,7 +111,7 @@ func createPartitionedIndex(documents []map[string]interface{}, index *indexAlia t.Fatal(err) } batch := childIndex.NewBatch() - for j := i * partitionSize; (j < (i+1)*partitionSize) && j < len(documents); j++ { + for j := prevCutoff; j < prevCutoff+docsPerPartition[i]; j++ { doc := documents[j] err := batch.Index(doc["id"].(string), doc) if err != nil { @@ -111,6 +119,7 @@ func createPartitionedIndex(documents []map[string]interface{}, index *indexAlia t.Fatal(err) } } + prevCutoff += docsPerPartition[i] err = childIndex.Batch(batch) if err != nil { cleanUp(t, rv) @@ -134,8 +143,15 @@ func truncateScore(score float64) float64 { return float64(int(score*1e6)) / 1e6 } -func TestSimilaritySearchQuery(t *testing.T) { +func TestSimilaritySearchRandomized(t *testing.T) { + runKNNTest(t, true) +} + +func TestSimilaritySearchNotRandomized(t *testing.T) { + runKNNTest(t, false) +} +func runKNNTest(t *testing.T, randomizeDocuments bool) { dataset, err := createVectorDataset(testDatasetFileName) if err != nil { t.Fatal(err) @@ -197,6 +213,10 @@ func TestSimilaritySearchQuery(t *testing.T) { queryIndex: 0, numIndexPartitions: 4, expectedResults: map[string]testResult{ + "doc29": { + score: 0.5547758085810349, + scoreBreakdown: []float64{0, 1.1095516171620698}, + }, "doc23": { score: 0.3817633037007331, scoreBreakdown: []float64{0, 0.7635266074014662}, @@ -205,10 +225,6 @@ func TestSimilaritySearchQuery(t *testing.T) { score: 0.33983667469689355, scoreBreakdown: []float64{0, 0.6796733493937871}, }, - "doc13": { - score: 0.3206958457835452, - scoreBreakdown: []float64{0, 0.6413916915670904}, - }, }, }, { @@ -233,29 +249,29 @@ func TestSimilaritySearchQuery(t *testing.T) { queryIndex: 1, numIndexPartitions: 1, expectedResults: map[string]testResult{ - "doc23": { - score: 1.304929, - scoreBreakdown: []float64{1.016928, 0.288001}, - }, "doc29": { - score: 1.137598, - scoreBreakdown: []float64{0.719076, 0.418521}, + score: 1.8859816084399936, + scoreBreakdown: []float64{0.7764299912779237, 1.1095516171620698}, + }, + "doc23": { + score: 1.8615644255330264, + scoreBreakdown: []float64{1.0980378181315602, 0.7635266074014662}, }, "doc27": { - score: 0.429730, - scoreBreakdown: []float64{0.859461, 0}, + score: 0.4640056648691007, + scoreBreakdown: []float64{0.9280113297382014, 0}, }, "doc28": { - score: 0.401976, - scoreBreakdown: []float64{0.803952, 0}, + score: 0.434037555556026, + scoreBreakdown: []float64{0.868075111112052, 0}, }, "doc30": { - score: 0.359538, - scoreBreakdown: []float64{0.719076, 0}, + score: 0.38821499563896184, + scoreBreakdown: []float64{0.7764299912779237, 0}, }, "doc24": { - score: 0.359538, - scoreBreakdown: []float64{0.719076, 0}, + score: 0.38821499563896184, + scoreBreakdown: []float64{0.7764299912779237, 0}, }, }, }, @@ -263,29 +279,29 @@ func TestSimilaritySearchQuery(t *testing.T) { queryIndex: 1, numIndexPartitions: 5, expectedResults: map[string]testResult{ - "doc29": { - score: 1.0019961733597083, - scoreBreakdown: []float64{0.28546778431249004, 0.7165283890472183}, - }, - "doc28": { - score: 0.758083452201489, - scoreBreakdown: []float64{0.3191626822375969, 0.4389207699638921}, - }, "doc23": { - score: 0.32598793043274804, - scoreBreakdown: []float64{0.6519758608654961, 0}, + score: 1.5207250366637521, + scoreBreakdown: []float64{0.7571984292622859, 0.7635266074014662}, + }, + "doc29": { + score: 1.4834345192674083, + scoreBreakdown: []float64{0.3738829021053385, 1.1095516171620698}, }, "doc24": { - score: 0.2305082774045959, - scoreBreakdown: []float64{0.4610165548091918, 0}, + score: 0.2677100734235977, + scoreBreakdown: []float64{0.5354201468471954, 0}, }, "doc27": { - score: 0.17059962977552257, - scoreBreakdown: []float64{0.34119925955104513, 0}, + score: 0.22343776840593196, + scoreBreakdown: []float64{0.4468755368118639, 0}, + }, + "doc28": { + score: 0.20900689401100958, + scoreBreakdown: []float64{0.41801378802201916, 0}, }, "doc30": { - score: 0.14273389215624502, - scoreBreakdown: []float64{0.28546778431249004, 0}, + score: 0.18694145105266924, + scoreBreakdown: []float64{0.3738829021053385, 0}, }, }, }, @@ -297,41 +313,41 @@ func TestSimilaritySearchQuery(t *testing.T) { score: 3333.333333333333, scoreBreakdown: []float64{0, 0, 10000}, }, - "doc23": { - score: 0.3234943403006508, - scoreBreakdown: []float64{0.30977843187823456, 0.1754630785727416, 0}, - }, "doc29": { - score: 0.31601878039486375, - scoreBreakdown: []float64{0.21904643099686824, 0.2549817395954274, 0}, + score: 0.6774608026082964, + scoreBreakdown: []float64{0.23161973134064517, 0.7845714725717996, 0}, + }, + "doc23": { + score: 0.5783030702431613, + scoreBreakdown: []float64{0.32755976365480655, 0.5398948417099355, 0}, }, "doc3": { - score: 0.24118912169729392, - scoreBreakdown: []float64{0.7235673650918818, 0, 0}, + score: 0.2550334160459894, + scoreBreakdown: []float64{0.7651002481379682, 0, 0}, }, "doc13": { - score: 0.20887591025526625, - scoreBreakdown: []float64{0.6266277307657988, 0, 0}, + score: 0.2208654210738964, + scoreBreakdown: []float64{0.6625962632216892, 0, 0}, + }, + "doc5": { + score: 0.21180931116413285, + scoreBreakdown: []float64{0, 0, 0.6354279334923986}, }, "doc27": { - score: 0.08727018618864227, - scoreBreakdown: []float64{0.26181055856592683, 0, 0}, + score: 0.09227950890170131, + scoreBreakdown: []float64{0.27683852670510395, 0, 0}, }, "doc28": { - score: 0.0816337841412418, - scoreBreakdown: []float64{0.2449013524237254, 0, 0}, - }, - "doc24": { - score: 0.07301547699895608, - scoreBreakdown: []float64{0.21904643099686824, 0, 0}, + score: 0.0863195764709126, + scoreBreakdown: []float64{0.2589587294127378, 0, 0}, }, "doc30": { - score: 0.07301547699895608, - scoreBreakdown: []float64{0.21904643099686824, 0, 0}, + score: 0.07720657711354839, + scoreBreakdown: []float64{0.23161973134064517, 0, 0}, }, - "doc5": { - score: 0.06883694922797147, - scoreBreakdown: []float64{0, 0, 0.20651084768391442}, + "doc24": { + score: 0.07720657711354839, + scoreBreakdown: []float64{0.23161973134064517, 0, 0}, }, }, }, @@ -343,33 +359,41 @@ func TestSimilaritySearchQuery(t *testing.T) { score: 3333.333333333333, scoreBreakdown: []float64{0, 0, 10000}, }, + "doc29": { + score: 0.567426591648309, + scoreBreakdown: []float64{0.06656841490066398, 0.7845714725717996, 0}, + }, "doc23": { - score: 0.2195946458144798, - scoreBreakdown: []float64{0.11312710434186327, 0.21626486437985648, 0}, + score: 0.5639255136185979, + scoreBreakdown: []float64{0.3059934287179615, 0.5398948417099355, 0}, }, - "doc28": { - score: 0.18796580117926376, - scoreBreakdown: []float64{0.08943482824521586, 0.1925138735236798, 0}, + "doc5": { + score: 0.21180931116413285, + scoreBreakdown: []float64{0, 0, 0.6354279334923986}, }, "doc3": { - score: 0.12303621410516037, - scoreBreakdown: []float64{0.36910864231548113, 0, 0}, + score: 0.14064944169372873, + scoreBreakdown: []float64{0.42194832508118624, 0, 0}, }, "doc13": { - score: 0.10655248891295889, - scoreBreakdown: []float64{0.3196574667388767, 0, 0}, - }, - "doc5": { - score: 0.07546992065969621, - scoreBreakdown: []float64{0, 0, 0.22640976197908863}, + score: 0.12180599172106943, + scoreBreakdown: []float64{0.3654179751632083, 0, 0}, }, "doc27": { - score: 0.03186995104545246, - scoreBreakdown: []float64{0.09560985313635739, 0, 0}, + score: 0.026521491065731144, + scoreBreakdown: []float64{0.07956447319719344, 0, 0}, + }, + "doc28": { + score: 0.024808583220893122, + scoreBreakdown: []float64{0.07442574966267937, 0, 0}, + }, + "doc30": { + score: 0.02218947163355466, + scoreBreakdown: []float64{0.06656841490066398, 0, 0}, }, "doc24": { - score: 0.02666431434541773, - scoreBreakdown: []float64{0.07999294303625319, 0, 0}, + score: 0.02218947163355466, + scoreBreakdown: []float64{0.06656841490066398, 0, 0}, }, }, }, @@ -419,4 +443,5 @@ func TestSimilaritySearchQuery(t *testing.T) { } cleanUp(t, indexPaths, index.indexes...) } + } diff --git a/search/searcher/search_conjunction.go b/search/searcher/search_conjunction.go index e0ae2c349..21fcf696a 100644 --- a/search/searcher/search_conjunction.go +++ b/search/searcher/search_conjunction.go @@ -16,7 +16,6 @@ package searcher import ( "context" - "math" "reflect" "sort" @@ -34,15 +33,16 @@ func init() { } type ConjunctionSearcher struct { - indexReader index.IndexReader - searchers []search.Searcher - queryNorm float64 - currs []*search.DocumentMatch - maxIDIdx int - scorer *scorer.ConjunctionQueryScorer - initialized bool - options search.SearcherOptions - bytesRead uint64 + indexReader index.IndexReader + searchers []search.Searcher + queryNorm float64 + queryNormForKNN float64 + currs []*search.DocumentMatch + maxIDIdx int + scorer *scorer.ConjunctionQueryScorer + initialized bool + options search.SearcherOptions + bytesRead uint64 } func NewConjunctionSearcher(ctx context.Context, indexReader index.IndexReader, @@ -110,20 +110,6 @@ func (s *ConjunctionSearcher) Size() int { return sizeInBytes } -func (s *ConjunctionSearcher) computeQueryNorm() { - // first calculate sum of squared weights - sumOfSquaredWeights := 0.0 - for _, searcher := range s.searchers { - sumOfSquaredWeights += searcher.Weight() - } - // now compute query norm from this - s.queryNorm = 1.0 / math.Sqrt(sumOfSquaredWeights) - // finally tell all the downstream searchers the norm - for _, searcher := range s.searchers { - searcher.SetQueryNorm(s.queryNorm) - } -} - func (s *ConjunctionSearcher) initSearchers(ctx *search.SearchContext) error { var err error // get all searchers pointing at their first match diff --git a/search/searcher/search_disjunction_heap.go b/search/searcher/search_disjunction_heap.go index af5915934..51e210804 100644 --- a/search/searcher/search_disjunction_heap.go +++ b/search/searcher/search_disjunction_heap.go @@ -18,7 +18,6 @@ import ( "bytes" "container/heap" "context" - "math" "reflect" "github.com/blevesearch/bleve/v2/search" @@ -47,13 +46,14 @@ type SearcherCurr struct { type DisjunctionHeapSearcher struct { indexReader index.IndexReader - numSearchers int - scorer *scorer.DisjunctionQueryScorer - min int - queryNorm float64 - initialized bool - searchers []search.Searcher - heap []*SearcherCurr + numSearchers int + scorer *scorer.DisjunctionQueryScorer + min int + queryNorm float64 + queryNormForKNN float64 + initialized bool + searchers []search.Searcher + heap []*SearcherCurr matching []*search.DocumentMatch matchingIdxs []int @@ -109,20 +109,6 @@ func (s *DisjunctionHeapSearcher) Size() int { return sizeInBytes } -func (s *DisjunctionHeapSearcher) computeQueryNorm() { - // first calculate sum of squared weights - sumOfSquaredWeights := 0.0 - for _, searcher := range s.searchers { - sumOfSquaredWeights += searcher.Weight() - } - // now compute query norm from this - s.queryNorm = 1.0 / math.Sqrt(sumOfSquaredWeights) - // finally tell all the downstream searchers the norm - for _, searcher := range s.searchers { - searcher.SetQueryNorm(s.queryNorm) - } -} - func (s *DisjunctionHeapSearcher) initSearchers(ctx *search.SearchContext) error { // alloc a single block of SearcherCurrs block := make([]SearcherCurr, len(s.searchers)) diff --git a/search/searcher/search_disjunction_slice.go b/search/searcher/search_disjunction_slice.go index fb9f7bab9..251463e6a 100644 --- a/search/searcher/search_disjunction_slice.go +++ b/search/searcher/search_disjunction_slice.go @@ -16,7 +16,6 @@ package searcher import ( "context" - "math" "reflect" "sort" @@ -34,18 +33,19 @@ func init() { } type DisjunctionSliceSearcher struct { - indexReader index.IndexReader - searchers []search.Searcher - originalPos []int - numSearchers int - queryNorm float64 - currs []*search.DocumentMatch - scorer *scorer.DisjunctionQueryScorer - min int - matching []*search.DocumentMatch - matchingIdxs []int - initialized bool - bytesRead uint64 + indexReader index.IndexReader + searchers []search.Searcher + originalPos []int + numSearchers int + queryNorm float64 + queryNormForKNN float64 + currs []*search.DocumentMatch + scorer *scorer.DisjunctionQueryScorer + min int + matching []*search.DocumentMatch + matchingIdxs []int + initialized bool + bytesRead uint64 } func newDisjunctionSliceSearcher(ctx context.Context, indexReader index.IndexReader, @@ -110,20 +110,6 @@ func (s *DisjunctionSliceSearcher) Size() int { return sizeInBytes } -func (s *DisjunctionSliceSearcher) computeQueryNorm() { - // first calculate sum of squared weights - sumOfSquaredWeights := 0.0 - for _, searcher := range s.searchers { - sumOfSquaredWeights += searcher.Weight() - } - // now compute query norm from this - s.queryNorm = 1.0 / math.Sqrt(sumOfSquaredWeights) - // finally tell all the downstream searchers the norm - for _, searcher := range s.searchers { - searcher.SetQueryNorm(s.queryNorm) - } -} - func (s *DisjunctionSliceSearcher) initSearchers(ctx *search.SearchContext) error { var err error // get all searchers pointing at their first match diff --git a/search/searcher/search_knn_util.go b/search/searcher/search_knn_util.go new file mode 100644 index 000000000..dabc61c54 --- /dev/null +++ b/search/searcher/search_knn_util.go @@ -0,0 +1,72 @@ +// Copyright (c) 2023 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. + +//go:build vectors +// +build vectors + +package searcher + +import ( + "math" + + "github.com/blevesearch/bleve/v2/search" +) + +// util func used by both disjunction and conjunction searchers +// to compute the query norm. +// This follows a separate code path from the non-knn version +// because we need to separate out the weights from the KNN searchers +// and the rest of the searchers to make the knn +// score completely independent of tf-idf. +// the sumOfSquaredWeights depends on the tf-idf weights +// and using the same value for knn searchers will make the +// knn score dependent on tf-idf. +func computeQueryNorm(searchers []search.Searcher) (float64, float64) { + // first calculate sum of squared weights + sumOfSquaredWeights := 0.0 + + sumOfSquaredWeightsForKNN := 0.0 + + for _, searcher := range searchers { + if knnSearcher, ok := searcher.(*KNNSearcher); ok { + sumOfSquaredWeightsForKNN += knnSearcher.Weight() + } else { + sumOfSquaredWeights += searcher.Weight() + } + } + // now compute query norm from this + queryNorm := 1.0 / math.Sqrt(sumOfSquaredWeights) + queryNormForKNN := 1.0 / math.Sqrt(sumOfSquaredWeightsForKNN) + // finally tell all the downstream searchers the norm + for _, searcher := range searchers { + if knnSearcher, ok := searcher.(*KNNSearcher); ok { + knnSearcher.SetQueryNorm(queryNormForKNN) + } else { + searcher.SetQueryNorm(queryNorm) + } + } + return queryNorm, queryNormForKNN +} + +func (s *DisjunctionSliceSearcher) computeQueryNorm() { + s.queryNorm, s.queryNormForKNN = computeQueryNorm(s.searchers) +} + +func (s *DisjunctionHeapSearcher) computeQueryNorm() { + s.queryNorm, s.queryNormForKNN = computeQueryNorm(s.searchers) +} + +func (s *ConjunctionSearcher) computeQueryNorm() { + s.queryNorm, s.queryNormForKNN = computeQueryNorm(s.searchers) +} diff --git a/search/searcher/search_no_knn_util.go b/search/searcher/search_no_knn_util.go new file mode 100644 index 000000000..abf7a32d8 --- /dev/null +++ b/search/searcher/search_no_knn_util.go @@ -0,0 +1,62 @@ +// Copyright (c) 2023 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. + +//go:build !vectors +// +build !vectors + +package searcher + +import "math" + +func (s *DisjunctionSliceSearcher) computeQueryNorm() { + // first calculate sum of squared weights + sumOfSquaredWeights := 0.0 + for _, searcher := range s.searchers { + sumOfSquaredWeights += searcher.Weight() + } + // now compute query norm from this + s.queryNorm = 1.0 / math.Sqrt(sumOfSquaredWeights) + // finally tell all the downstream searchers the norm + for _, searcher := range s.searchers { + searcher.SetQueryNorm(s.queryNorm) + } +} + +func (s *DisjunctionHeapSearcher) computeQueryNorm() { + // first calculate sum of squared weights + sumOfSquaredWeights := 0.0 + for _, searcher := range s.searchers { + sumOfSquaredWeights += searcher.Weight() + } + // now compute query norm from this + s.queryNorm = 1.0 / math.Sqrt(sumOfSquaredWeights) + // finally tell all the downstream searchers the norm + for _, searcher := range s.searchers { + searcher.SetQueryNorm(s.queryNorm) + } +} + +func (s *ConjunctionSearcher) computeQueryNorm() { + // first calculate sum of squared weights + sumOfSquaredWeights := 0.0 + for _, searcher := range s.searchers { + sumOfSquaredWeights += searcher.Weight() + } + // now compute query norm from this + s.queryNorm = 1.0 / math.Sqrt(sumOfSquaredWeights) + // finally tell all the downstream searchers the norm + for _, searcher := range s.searchers { + searcher.SetQueryNorm(s.queryNorm) + } +} diff --git a/test/tests/knn/dataset-30-docs.json b/test/knn/knn_dataset.json similarity index 100% rename from test/tests/knn/dataset-30-docs.json rename to test/knn/knn_dataset.json diff --git a/test/tests/knn/small-query.json b/test/knn/knn_queries.json similarity index 99% rename from test/tests/knn/small-query.json rename to test/knn/knn_queries.json index 8bafde6e6..2304a96c1 100644 --- a/test/tests/knn/small-query.json +++ b/test/knn/knn_queries.json @@ -8,7 +8,7 @@ "content" ], "from":0, - "size":10, + "size":30, "knn":[{ "field":"vector", "vector":[ @@ -410,7 +410,7 @@ "content" ], "from":0, - "size":10, + "size":30, "knn":[{ "field":"vector", "vector":[ @@ -820,7 +820,7 @@ "content" ], "from":0, - "size":20, + "size":30, "knn":[{ "field":"vector", "vector":[ From a58fd7f4e19ed59cda6d5b15337fe84ab915a035 Mon Sep 17 00:00:00 2001 From: CascadingRadium Date: Fri, 17 Nov 2023 13:47:20 +0530 Subject: [PATCH 03/10] fix divide-by-zero error in knn scoring --- knn_test.go | 8 ++++---- search/scorer/scorer_knn.go | 15 +++++++-------- 2 files changed, 11 insertions(+), 12 deletions(-) diff --git a/knn_test.go b/knn_test.go index b19b7005d..f2d14edf4 100644 --- a/knn_test.go +++ b/knn_test.go @@ -310,8 +310,8 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { numIndexPartitions: 1, expectedResults: map[string]testResult{ "doc7": { - score: 3333.333333333333, - scoreBreakdown: []float64{0, 0, 10000}, + score: 2357.022603955158, + scoreBreakdown: []float64{0, 0, 7071.067811865475}, }, "doc29": { score: 0.6774608026082964, @@ -356,8 +356,8 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { numIndexPartitions: 4, expectedResults: map[string]testResult{ "doc7": { - score: 3333.333333333333, - scoreBreakdown: []float64{0, 0, 10000}, + score: 2357.022603955158, + scoreBreakdown: []float64{0, 0, 7071.067811865475}, }, "doc29": { score: 0.567426591648309, diff --git a/search/scorer/scorer_knn.go b/search/scorer/scorer_knn.go index ae50c77d5..6d8653693 100644 --- a/search/scorer/scorer_knn.go +++ b/search/scorer/scorer_knn.go @@ -18,7 +18,6 @@ package scorer import ( - "math" "reflect" "github.com/blevesearch/bleve/v2/search" @@ -71,8 +70,13 @@ func (sqs *KNNQueryScorer) Score(ctx *search.SearchContext, if sqs.includeScore || sqs.options.Explain { var scoreExplanation *search.Explanation score := knnMatch.Score - if sqs.similarityMetric == util.EuclideanDistance { - // eucliden distances need to be inverted to work + if score == 0.0 { + // the vector is found to be exactly same as the query vector + // this is a perfect match, so return the max score + score = MaxAllowedScore + } else if sqs.similarityMetric == util.EuclideanDistance { + // safeguard from divide-by-zero + // euclidean distances need to be inverted to work // tf-idf scoring score = 1.0 / score } @@ -83,11 +87,6 @@ func (sqs *KNNQueryScorer) Score(ctx *search.SearchContext, } if sqs.includeScore { - if math.IsInf(score, 1) { - score = MaxAllowedScore // MAX ALLOWED SCORE - } else if math.IsInf(score, -1) { - score = 0.0 - } rv.Score = score } From ae5eaeb095eb3627c0700e4968a963600d812c8b Mon Sep 17 00:00:00 2001 From: CascadingRadium Date: Fri, 17 Nov 2023 16:57:11 +0530 Subject: [PATCH 04/10] merge KNN results from multiple segments --- index_alias_impl.go | 4 +- index_impl.go | 30 ++++- knn_test.go | 304 ++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 333 insertions(+), 5 deletions(-) diff --git a/index_alias_impl.go b/index_alias_impl.go index a2e1392d4..e126febea 100644 --- a/index_alias_impl.go +++ b/index_alias_impl.go @@ -171,8 +171,8 @@ func (i *indexAliasImpl) SearchInContext(ctx context.Context, req *SearchRequest return i.indexes[0].SearchInContext(ctx, req) } - ctx = context.WithValue(ctx, search.AliasPartitionedModeKey, i.partitionedMode) - return MultiSearch(ctx, req, i.indexes...) + nctx := context.WithValue(ctx, search.AliasPartitionedModeKey, i.partitionedMode) + return MultiSearch(nctx, req, i.indexes...) } func (i *indexAliasImpl) Fields() ([]string, error) { diff --git a/index_impl.go b/index_impl.go index fe3a62e9e..241b42f84 100644 --- a/index_impl.go +++ b/index_impl.go @@ -496,7 +496,6 @@ func (i *indexImpl) SearchInContext(ctx context.Context, req *SearchRequest) (sr ctx = context.WithValue(ctx, search.GeoBufferPoolCallbackKey, search.GeoBufferPoolCallbackFunc(getBufferPool)) - // Using a disjunction query to get union of results from KNN query // and the original query searchQuery := disjunctQueryWithKNN(req) @@ -643,7 +642,7 @@ func (i *indexImpl) SearchInContext(ctx context.Context, req *SearchRequest) (sr req.SearchAfter = nil } - return &SearchResult{ + rv := &SearchResult{ Status: &SearchStatus{ Total: 1, Successful: 1, @@ -654,7 +653,32 @@ func (i *indexImpl) SearchInContext(ctx context.Context, req *SearchRequest) (sr MaxScore: coll.MaxScore(), Took: searchDuration, Facets: coll.FacetResults(), - }, nil + } + // if AliasPartitionedModeKey is true + // -> this is a child index in an alias for a partitioned index + // -> do not merge the KNN results now, as we need to merge them + // with the results from the other child indexes in the alias + // -> the merge will happen in the top-level MultiSearch + // else if false + // -> this is child index in an user alias for multiple different indexes + // -> NOT a child index in an alias for a partitioned index + // -> merge the KNN results now + // else if not present + // -> this is a regular index + // -> merge the KNN results now + if mode := ctx.Value(search.AliasPartitionedModeKey); mode != nil { + aliasForPartitionedIndex, ok := mode.(bool) + if ok && !aliasForPartitionedIndex { + // this is NOT a child index in an alias for a partitioned index, + // so we can merge the KNN results now. This merge is required + // as the top k results are from each segment, resulting in + // k * numSegments results. + mergeKNNResults(req, rv) + } + } else { + mergeKNNResults(req, rv) + } + return rv, nil } func LoadAndHighlightFields(hit *search.DocumentMatch, req *SearchRequest, diff --git a/knn_test.go b/knn_test.go index f2d14edf4..c38e845a5 100644 --- a/knn_test.go +++ b/knn_test.go @@ -130,6 +130,43 @@ func createPartitionedIndex(documents []map[string]interface{}, index *indexAlia return rv } +func createMultipleSegmentsIndex(documents []map[string]interface{}, index Index, numSegments int) error { + // create multiple batches to simulate more than one segment + numBatches := numSegments + + batches := make([]*Batch, numBatches) + numDocsPerBatch := len(documents) / numBatches + extraDocs := len(documents) % numBatches + + docsPerBatch := make([]int, numBatches) + for i := 0; i < numBatches; i++ { + docsPerBatch[i] = numDocsPerBatch + if extraDocs > 0 { + docsPerBatch[i]++ + extraDocs-- + } + } + prevCutoff := 0 + for i := 0; i < numBatches; i++ { + batches[i] = index.NewBatch() + for j := prevCutoff; j < prevCutoff+docsPerBatch[i]; j++ { + doc := documents[j] + err := batches[i].Index(doc["id"].(string), doc) + if err != nil { + return err + } + } + prevCutoff += docsPerBatch[i] + } + for _, batch := range batches { + err = index.Batch(batch) + if err != nil { + return err + } + } + return nil +} + // Fisher-Yates shuffle func shuffleDocuments(documents []map[string]interface{}) []map[string]interface{} { for i := range documents { @@ -443,5 +480,272 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { } cleanUp(t, indexPaths, index.indexes...) } +} + +func TestSimilaritySearchMultipleSegments(t *testing.T) { + dataset, err := createVectorDataset(testDatasetFileName) + if err != nil { + t.Fatal(err) + } + documents := makeDatasetIntoDocuments(dataset) + searchRequests, err := getSearchRequests(testQueryFileName) + if err != nil { + t.Fatal(err) + } + + indexMapping := NewIndexMapping() + contentFieldMapping := NewTextFieldMapping() + contentFieldMapping.Analyzer = "en" + vecFieldMapping := mapping.NewVectorFieldMapping() + vecFieldMapping.Dims = testDatasetDims + vecFieldMapping.Similarity = "l2_norm" + + indexMapping.DefaultMapping.AddFieldMappingsAt("content", contentFieldMapping) + indexMapping.DefaultMapping.AddFieldMappingsAt("vector", vecFieldMapping) + + type testResult struct { + score float64 + scoreBreakdown []float64 + } + + testCases := []struct { + numSegments int + queryIndex int + expectedResults map[string]testResult + }{ + { + numSegments: 1, + queryIndex: 0, + expectedResults: map[string]testResult{ + "doc29": { + score: 0.5547758085810349, + scoreBreakdown: []float64{0, 1.1095516171620698}, + }, + "doc23": { + score: 0.3817633037007331, + scoreBreakdown: []float64{0, 0.7635266074014662}, + }, + "doc28": { + score: 0.33983667469689355, + scoreBreakdown: []float64{0, 0.6796733493937871}, + }, + }, + }, + { + numSegments: 6, + queryIndex: 0, + expectedResults: map[string]testResult{ + "doc29": { + score: 0.5547758085810349, + scoreBreakdown: []float64{0, 1.1095516171620698}, + }, + "doc23": { + score: 0.3817633037007331, + scoreBreakdown: []float64{0, 0.7635266074014662}, + }, + "doc28": { + score: 0.33983667469689355, + scoreBreakdown: []float64{0, 0.6796733493937871}, + }, + }, + }, + { + numSegments: 1, + queryIndex: 1, + expectedResults: map[string]testResult{ + "doc29": { + score: 1.8859816084399936, + scoreBreakdown: []float64{0.7764299912779237, 1.1095516171620698}, + }, + "doc23": { + score: 1.8615644255330264, + scoreBreakdown: []float64{1.0980378181315602, 0.7635266074014662}, + }, + "doc27": { + score: 0.4640056648691007, + scoreBreakdown: []float64{0.9280113297382014, 0}, + }, + "doc28": { + score: 0.434037555556026, + scoreBreakdown: []float64{0.868075111112052, 0}, + }, + "doc30": { + score: 0.38821499563896184, + scoreBreakdown: []float64{0.7764299912779237, 0}, + }, + "doc24": { + score: 0.38821499563896184, + scoreBreakdown: []float64{0.7764299912779237, 0}, + }, + }, + }, + { + numSegments: 7, + queryIndex: 1, + expectedResults: map[string]testResult{ + "doc29": { + score: 1.8859816084399936, + scoreBreakdown: []float64{0.7764299912779237, 1.1095516171620698}, + }, + "doc23": { + score: 1.8615644255330264, + scoreBreakdown: []float64{1.0980378181315602, 0.7635266074014662}, + }, + "doc27": { + score: 0.4640056648691007, + scoreBreakdown: []float64{0.9280113297382014, 0}, + }, + "doc28": { + score: 0.434037555556026, + scoreBreakdown: []float64{0.868075111112052, 0}, + }, + "doc30": { + score: 0.38821499563896184, + scoreBreakdown: []float64{0.7764299912779237, 0}, + }, + "doc24": { + score: 0.38821499563896184, + scoreBreakdown: []float64{0.7764299912779237, 0}, + }, + }, + }, + { + numSegments: 1, + queryIndex: 2, + expectedResults: map[string]testResult{ + "doc7": { + score: 2357.022603955158, + scoreBreakdown: []float64{0, 0, 7071.067811865475}, + }, + "doc29": { + score: 0.6774608026082964, + scoreBreakdown: []float64{0.23161973134064517, 0.7845714725717996, 0}, + }, + "doc23": { + score: 0.5783030702431613, + scoreBreakdown: []float64{0.32755976365480655, 0.5398948417099355, 0}, + }, + "doc3": { + score: 0.2550334160459894, + scoreBreakdown: []float64{0.7651002481379682, 0, 0}, + }, + "doc13": { + score: 0.2208654210738964, + scoreBreakdown: []float64{0.6625962632216892, 0, 0}, + }, + "doc5": { + score: 0.21180931116413285, + scoreBreakdown: []float64{0, 0, 0.6354279334923986}, + }, + "doc27": { + score: 0.09227950890170131, + scoreBreakdown: []float64{0.27683852670510395, 0, 0}, + }, + "doc28": { + score: 0.0863195764709126, + scoreBreakdown: []float64{0.2589587294127378, 0, 0}, + }, + "doc30": { + score: 0.07720657711354839, + scoreBreakdown: []float64{0.23161973134064517, 0, 0}, + }, + "doc24": { + score: 0.07720657711354839, + scoreBreakdown: []float64{0.23161973134064517, 0, 0}, + }, + }, + }, + { + numSegments: 6, + queryIndex: 2, + expectedResults: map[string]testResult{ + "doc7": { + score: 2357.022603955158, + scoreBreakdown: []float64{0, 0, 7071.067811865475}, + }, + "doc29": { + score: 0.6774608026082964, + scoreBreakdown: []float64{0.23161973134064517, 0.7845714725717996, 0}, + }, + "doc23": { + score: 0.5783030702431613, + scoreBreakdown: []float64{0.32755976365480655, 0.5398948417099355, 0}, + }, + "doc3": { + score: 0.2550334160459894, + scoreBreakdown: []float64{0.7651002481379682, 0, 0}, + }, + "doc13": { + score: 0.2208654210738964, + scoreBreakdown: []float64{0.6625962632216892, 0, 0}, + }, + "doc5": { + score: 0.21180931116413285, + scoreBreakdown: []float64{0, 0, 0.6354279334923986}, + }, + "doc27": { + score: 0.09227950890170131, + scoreBreakdown: []float64{0.27683852670510395, 0, 0}, + }, + "doc28": { + score: 0.0863195764709126, + scoreBreakdown: []float64{0.2589587294127378, 0, 0}, + }, + "doc30": { + score: 0.07720657711354839, + scoreBreakdown: []float64{0.23161973134064517, 0, 0}, + }, + "doc24": { + score: 0.07720657711354839, + scoreBreakdown: []float64{0.23161973134064517, 0, 0}, + }, + }, + }, + } + for testCaseNum, testCase := range testCases { + tmpIndexPath := createTmpIndexPath(t) + index, err := New(tmpIndexPath, indexMapping) + if err != nil { + t.Fatal(err) + } + query := searchRequests[testCase.queryIndex] + err = createMultipleSegmentsIndex(documents, index, testCase.numSegments) + if err != nil { + t.Fatal(err) + } + res, err := index.Search(query) + if err != nil { + t.Fatal(err) + } + for i, hit := range res.Hits { + var expectedHit testResult + var ok bool + if expectedHit, ok = testCase.expectedResults[hit.ID]; !ok { + t.Fatalf("testcase %d failed: unexpected result %s", testCaseNum, hit.ID) + } + // Truncate to 6 decimal places + actualScore := truncateScore(hit.Score) + expectScore := truncateScore(expectedHit.score) + if expectScore != actualScore { + t.Fatalf("testcase %d failed: expected hit %d to have score %f, got %f", testCaseNum, i, expectedHit.score, hit.Score) + } + if len(hit.ScoreBreakdown) != len(expectedHit.scoreBreakdown) { + t.Fatalf("testcase %d failed: expected hit %d to have %d score breakdowns, got %d", testCaseNum, i, len(expectedHit.scoreBreakdown), len(hit.ScoreBreakdown)) + } + for j := 0; j < len(hit.ScoreBreakdown); j++ { + // Truncate to 6 decimal places + actualScore := truncateScore(hit.ScoreBreakdown[j]) + expectScore := truncateScore(expectedHit.scoreBreakdown[j]) + if expectScore != actualScore { + t.Fatalf("testcase %d failed: expected hit %d to have score breakdown %f, got %f", testCaseNum, i, expectedHit.scoreBreakdown[j], hit.ScoreBreakdown[j]) + } + } + } + err = index.Close() + if err != nil { + t.Fatal(err) + } + cleanupTmpIndexPath(t, tmpIndexPath) + } } From 18cb8949f738cac42cab22e16cdf2ed718680810 Mon Sep 17 00:00:00 2001 From: CascadingRadium Date: Mon, 20 Nov 2023 13:54:20 +0530 Subject: [PATCH 05/10] compressed dataset --- knn_test.go | 66 +- test/knn/knn_dataset.json | 11702 ----------------------------- test/knn/knn_dataset_queries.zip | Bin 0 -> 127480 bytes test/knn/knn_queries.json | 1606 ---- 4 files changed, 32 insertions(+), 13342 deletions(-) delete mode 100644 test/knn/knn_dataset.json create mode 100644 test/knn/knn_dataset_queries.zip delete mode 100644 test/knn/knn_queries.json diff --git a/knn_test.go b/knn_test.go index c38e845a5..5964799e3 100644 --- a/knn_test.go +++ b/knn_test.go @@ -18,16 +18,17 @@ package bleve import ( + "archive/zip" "encoding/json" "math/rand" - "os" "testing" "github.com/blevesearch/bleve/v2/mapping" ) -const testDatasetFileName = "test/knn/knn_dataset.json" -const testQueryFileName = "test/knn/knn_queries.json" +const testInputCompressedFile = "test/knn/knn_dataset_queries.zip" +const testDatasetFileName = "knn_dataset.json" +const testQueryFileName = "knn_queries.json" const testDatasetDims = 384 @@ -37,17 +38,35 @@ type testDocument struct { Vector []float64 `json:"vector"` } -func createVectorDataset(datasetFileName string) ([]testDocument, error) { - var dataset []testDocument - datasetFileData, err := os.ReadFile(datasetFileName) +func readDatasetAndQueries(fileName string) ([]testDocument, []*SearchRequest, error) { + // Open the zip archive for reading + r, err := zip.OpenReader(fileName) if err != nil { - return nil, err + return nil, nil, err } - err = json.Unmarshal(datasetFileData, &dataset) - if err != nil { - return nil, err + var dataset []testDocument + var queries []*SearchRequest + + defer r.Close() + for _, f := range r.File { + jsonFile, err := f.Open() + if err != nil { + return nil, nil, err + } + defer jsonFile.Close() + if f.Name == testDatasetFileName { + err = json.NewDecoder(jsonFile).Decode(&dataset) + if err != nil { + return nil, nil, err + } + } else if f.Name == testQueryFileName { + err = json.NewDecoder(jsonFile).Decode(&queries) + if err != nil { + return nil, nil, err + } + } } - return dataset, nil + return dataset, queries, nil } func makeDatasetIntoDocuments(dataset []testDocument) []map[string]interface{} { @@ -62,19 +81,6 @@ func makeDatasetIntoDocuments(dataset []testDocument) []map[string]interface{} { return documents } -func getSearchRequests(queryFileName string) ([]*SearchRequest, error) { - var reqArr []*SearchRequest - queryFileData, err := os.ReadFile(queryFileName) - if err != nil { - return nil, err - } - err = json.Unmarshal(queryFileData, &reqArr) - if err != nil { - return nil, err - } - return reqArr, nil -} - func cleanUp(t *testing.T, indexPaths []string, indexes ...Index) { for _, childIndex := range indexes { err := childIndex.Close() @@ -189,7 +195,7 @@ func TestSimilaritySearchNotRandomized(t *testing.T) { } func runKNNTest(t *testing.T, randomizeDocuments bool) { - dataset, err := createVectorDataset(testDatasetFileName) + dataset, searchRequests, err := readDatasetAndQueries(testInputCompressedFile) if err != nil { t.Fatal(err) } @@ -197,10 +203,6 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { if randomizeDocuments { documents = shuffleDocuments(documents) } - searchRequests, err := getSearchRequests(testQueryFileName) - if err != nil { - t.Fatal(err) - } indexMapping := NewIndexMapping() contentFieldMapping := NewTextFieldMapping() @@ -483,15 +485,11 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { } func TestSimilaritySearchMultipleSegments(t *testing.T) { - dataset, err := createVectorDataset(testDatasetFileName) + dataset, searchRequests, err := readDatasetAndQueries(testInputCompressedFile) if err != nil { t.Fatal(err) } documents := makeDatasetIntoDocuments(dataset) - searchRequests, err := getSearchRequests(testQueryFileName) - if err != nil { - t.Fatal(err) - } indexMapping := NewIndexMapping() contentFieldMapping := NewTextFieldMapping() diff --git a/test/knn/knn_dataset.json b/test/knn/knn_dataset.json deleted file mode 100644 index e4d2c0b16..000000000 --- a/test/knn/knn_dataset.json +++ /dev/null @@ -1,11702 +0,0 @@ -[ - { - "id": "doc1", - "content": "kathmandu the capital of nepal", - "vector": [ - 0.051617808640003204, - 0.07110562175512314, - -0.03424040600657463, - 0.1106891930103302, - 0.0018261136719956994, - -0.03148188441991806, - -0.01251516304910183, - -0.025826703757047653, - 0.004383699968457222, - -0.03891494497656822, - 0.0272526815533638, - -0.13677167892456055, - 0.03383525460958481, - -0.05666087940335274, - 0.042943671345710754, - -0.006899841595441103, - 0.006128854118287563, - -0.02948644757270813, - -0.013789803721010685, - 0.004112833645194769, - 0.04524744674563408, - 0.00237236893735826, - -0.026674099266529083, - -0.06116340681910515, - 0.031624335795640945, - 0.04654698446393013, - 0.01139751449227333, - -0.10183016955852509, - 0.054570261389017105, - -0.04146449640393257, - 0.01431590598076582, - -0.1127229854464531, - -0.024298951029777527, - 0.03649073466658592, - 0.005020954180508852, - 0.0989784225821495, - -0.09598291665315628, - 0.058288976550102234, - 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originalSize := req.Size + if mode := ctx.Value(search.AliasPartitionedModeKey); mode != nil { + aliasForPartitionedIndex, ok := mode.(bool) + if ok && aliasForPartitionedIndex && len(indexes) > 1 { + // this is an alias for a partitioned index, where each child index + // is a partition of a larger index. + // when knn queries are present we need to modify the + // size property of the request to ensure that the pagination works + // correctly, irrespective of the number of partitions. + // i.e if sum of all k is K and there are N partitions, + // then the top K hits from each partition is returned, resulting in + // N*K hits (worst case). If the size of the request < N*K, then the ordering + // of the hits will be different from the ordering of the hits when + // size >= N*K, upon merging since complete information is not available + // hence we need to modify the size to be N*K. + modifyRequestSize(req, len(indexes)) + } + } // run search on each index in separate go routine var waitGroup sync.WaitGroup @@ -497,6 +515,7 @@ func MultiSearch(ctx context.Context, req *SearchRequest, indexes ...Index) (*Se indexErrors[asr.Name] = asr.Err } } + req.Size = originalSize // merge just concatenated all the hits // now lets clean it up diff --git a/knn_test.go b/knn_test.go index 5964799e3..42687fa65 100644 --- a/knn_test.go +++ b/knn_test.go @@ -224,6 +224,7 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { } type testCase struct { + testType string queryIndex int numIndexPartitions int expectedResults map[string]testResult @@ -231,6 +232,7 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { testCases := []testCase{ { + testType: "single_partition:match_none:oneKNNreq:k=3", queryIndex: 0, numIndexPartitions: 1, expectedResults: map[string]testResult{ @@ -249,6 +251,7 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { }, }, { + testType: "multi_partition:match_none:oneKNNreq:k=3", queryIndex: 0, numIndexPartitions: 4, expectedResults: map[string]testResult{ @@ -267,6 +270,7 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { }, }, { + testType: "multi_partition:match_none:oneKNNreq:k=2", queryIndex: 0, numIndexPartitions: 10, expectedResults: map[string]testResult{ @@ -285,6 +289,7 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { }, }, { + testType: "single_partition:match:oneKNNreq:k=2", queryIndex: 1, numIndexPartitions: 1, expectedResults: map[string]testResult{ @@ -315,6 +320,7 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { }, }, { + testType: "multi_partition:match:oneKNNreq:k=2", queryIndex: 1, numIndexPartitions: 5, expectedResults: map[string]testResult{ @@ -345,6 +351,7 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { }, }, { + testType: "single_partition:disjunction:twoKNNreq:k=2,2", queryIndex: 2, numIndexPartitions: 1, expectedResults: map[string]testResult{ @@ -391,6 +398,7 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { }, }, { + testType: "multi_partition:disjunction:twoKNNreq:k=2,2", queryIndex: 2, numIndexPartitions: 4, expectedResults: map[string]testResult{ @@ -436,6 +444,91 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { }, }, }, + { + // control: + // from = 0 + // size = 8 + testType: "pagination", + queryIndex: 3, + numIndexPartitions: 4, + expectedResults: map[string]testResult{ + "doc24": { + score: 1.22027994094805, + scoreBreakdown: []float64{0.027736154383370196, 0.3471022633855392, 0.5085619451465123, 0.33687957803262836}, + }, + "doc17": { + score: 0.7851856993753307, + scoreBreakdown: []float64{0.3367753689069724, 0, 0.3892791754255179, 0.320859721501284}, + }, + "doc21": { + score: 0.5927148028393034, + scoreBreakdown: []float64{0.06974846263723515, 0, 0.3914133076090359, 0.3291246335394669}, + }, + "doc14": { + score: 0.45680756875853035, + scoreBreakdown: []float64{0.5968461853543279, 0, 0, 0.31676895216273276}, + }, + "doc25": { + score: 0.292014972318407, + scoreBreakdown: []float64{0.17861510907524708, 0, 0.405414835561567, 0}, + }, + "doc23": { + score: 0.24706850662359503, + scoreBreakdown: []float64{0.09761951136424651, 0, 0.39651750188294355, 0}, + }, + "doc15": { + score: 0.24489276164017085, + scoreBreakdown: []float64{0.17216818679645968, 0, 0, 0.317617336483882}, + }, + "doc5": { + score: 0.10331722282971788, + scoreBreakdown: []float64{0, 0.4132688913188715, 0, 0}, + }, + }, + }, + { + // experimental: + // from = 0 + // size = 3 + testType: "pagination", + queryIndex: 4, + numIndexPartitions: 4, + expectedResults: map[string]testResult{ + "doc24": { + score: 1.22027994094805, + scoreBreakdown: []float64{0.027736154383370196, 0.3471022633855392, 0.5085619451465123, 0.33687957803262836}, + }, + "doc17": { + score: 0.7851856993753307, + scoreBreakdown: []float64{0.3367753689069724, 0, 0.3892791754255179, 0.320859721501284}, + }, + "doc21": { + score: 0.5927148028393034, + scoreBreakdown: []float64{0.06974846263723515, 0, 0.3914133076090359, 0.3291246335394669}, + }, + }, + }, + { + // from = 3 + // size = 3 + testType: "pagination", + queryIndex: 5, + numIndexPartitions: 4, + expectedResults: map[string]testResult{ + "doc14": { + score: 0.45680756875853035, + scoreBreakdown: []float64{0.5968461853543279, 0, 0, 0.31676895216273276}, + }, + "doc25": { + score: 0.292014972318407, + scoreBreakdown: []float64{0.17861510907524708, 0, 0.405414835561567, 0}, + }, + "doc23": { + score: 0.24706850662359503, + scoreBreakdown: []float64{0.09761951136424651, 0, 0.39651750188294355, 0}, + }, + }, + }, } for testCaseNum, testCase := range testCases { @@ -449,6 +542,10 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { if len(res.Hits) != len(testCase.expectedResults) { t.Fatalf("testcase %d failed: expected %d results, got %d", testCaseNum, len(testCase.expectedResults), len(res.Hits)) } + if randomizeDocuments && testCase.testType == "pagination" { + // pagination is not deterministic when documents are randomized + continue + } for i, hit := range res.Hits { var expectedHit testResult var ok bool diff --git a/search_knn.go b/search_knn.go index 48563e10a..f47f24b6a 100644 --- a/search_knn.go +++ b/search_knn.go @@ -181,6 +181,19 @@ func mergeKNNResults(req *SearchRequest, sr *SearchResult) { } } +func modifyRequestSize(req *SearchRequest, numPartitions int) { + if len(req.KNN) > 0 { + var minSizeReq int64 + for _, knn := range req.KNN { + minSizeReq += knn.K + } + minSizeReq *= int64(numPartitions) + if int64(req.Size) < minSizeReq { + req.Size = int(minSizeReq) + } + } +} + // heap impl type scoreHeap struct { scoreBreakdown []*[]float64 diff --git a/search_no_knn.go b/search_no_knn.go index cd7b4153a..5b8366288 100644 --- a/search_no_knn.go +++ b/search_no_knn.go @@ -154,3 +154,6 @@ func validateKNN(req *SearchRequest) error { func mergeKNNResults(req *SearchRequest, sr *SearchResult) { } + +func modifyRequestSize(req *SearchRequest, numPartitions int) { +} diff --git a/test/knn/knn_dataset_queries.zip b/test/knn/knn_dataset_queries.zip index 43be9c858f5a00d02e439c6f4b317a1c9a527fc7..d840ded2f4ce2658ca1224e9f712f13f96252cac 100644 GIT binary patch delta 31469 zcma%hbxa-6w=Ql)iaQi{cXxMp*WymmQz-84?heIWin|uq0tY!b99%BHoBPL2-h0WL zWM-0`_3fqKnq<~~+=q`!L`)EXVzCJlY7v4QnnnxC@X&$ypUd4ID*fvWBmqFd)WAyR z^A@u)u=4!z1p*QV3<&`NgY_wQ*0V9gH0oLEW1{lAp?*3xMq(tWUY(U7X^QzbRU&Po zU4i9N*TbVVaGiXb&#QBextQ>g%AmDJpY(m4clEu; ztL*fC2z(r~^u0Wx0bWG_fsfbWmv^%tM{ffkujLOWuh%ah_oE^p006ki@^Sa^`rak- zF{zT@`&QrgSSa%PI5@lWc6D3+Li%7SE+?5c>oURCEm z51$8gtd={AyzT6~?H!SRJfGwTzMZ_O0G=LJ`r>9~NM!^-Y%74@aqKoPXqKvW$Q}&W}_w({gyi)l2Xza-i?XA##v*J4%ayDhpFDhdmqIB 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zTJlz6a6CS$R6A^h136j1zc2%Oqx( z!VOZ#R_-EYW}zhMCKB+f@R77p-yyS2Tx5Va$2Rc&nc+9-Nqa}MRm3VkfXe`}!i6Mk zJ!{CdemXauC->ben;DKPrP^0_!<^C%!nsuo2#3W6*|y8d3iJkw=aUBaT~lZJ>(nfE z)%0rFi7<%HE9n*Kc+&PWHE2ZQpPW~$sax6^C8gk$r%W;KVzI^xIuw|!= zg3D^r#>jN4OCe79U(Bs0WtG^)>x0jn&1)#EmA~s*c=ERmPQFQIc?9KCiJ>d-zl_fq>Y!r)F@b2$ io~{v3Kgj>|2y0<*1OET$O^%}$1`7`7+0*0=+W!Hn`xTo2 From 54685ca13b48c7d1c75c77ce6ac5415bf72fd3f9 Mon Sep 17 00:00:00 2001 From: CascadingRadium Date: Mon, 20 Nov 2023 23:41:12 +0530 Subject: [PATCH 07/10] revert partitioned flag --- index_alias_impl.go | 52 ++++++++------------------------------------- index_impl.go | 25 +--------------------- knn_test.go | 1 - search/search.go | 7 ++++++ search_knn.go | 4 ++-- 5 files changed, 19 insertions(+), 70 deletions(-) diff --git a/index_alias_impl.go b/index_alias_impl.go index 394b10e95..9225d2ddf 100644 --- a/index_alias_impl.go +++ b/index_alias_impl.go @@ -25,11 +25,10 @@ import ( ) type indexAliasImpl struct { - name string - indexes []Index - mutex sync.RWMutex - open bool - partitionedMode bool + name string + indexes []Index + mutex sync.RWMutex + open bool } // NewIndexAlias creates a new IndexAlias over the provided @@ -42,10 +41,6 @@ func NewIndexAlias(indexes ...Index) *indexAliasImpl { } } -func (i *indexAliasImpl) SetPartitionedMode(partitionedMode bool) { - i.partitionedMode = partitionedMode -} - // VisitIndexes invokes the visit callback on every // indexes included in the index alias. func (i *indexAliasImpl) VisitIndexes(visit func(Index)) { @@ -170,9 +165,7 @@ func (i *indexAliasImpl) SearchInContext(ctx context.Context, req *SearchRequest if len(i.indexes) == 1 { return i.indexes[0].SearchInContext(ctx, req) } - - nctx := context.WithValue(ctx, search.AliasPartitionedModeKey, i.partitionedMode) - return MultiSearch(nctx, req, i.indexes...) + return MultiSearch(ctx, req, i.indexes...) } func (i *indexAliasImpl) Fields() ([]string, error) { @@ -460,22 +453,8 @@ func MultiSearch(ctx context.Context, req *SearchRequest, indexes ...Index) (*Se req.SearchBefore = nil } originalSize := req.Size - if mode := ctx.Value(search.AliasPartitionedModeKey); mode != nil { - aliasForPartitionedIndex, ok := mode.(bool) - if ok && aliasForPartitionedIndex && len(indexes) > 1 { - // this is an alias for a partitioned index, where each child index - // is a partition of a larger index. - // when knn queries are present we need to modify the - // size property of the request to ensure that the pagination works - // correctly, irrespective of the number of partitions. - // i.e if sum of all k is K and there are N partitions, - // then the top K hits from each partition is returned, resulting in - // N*K hits (worst case). If the size of the request < N*K, then the ordering - // of the hits will be different from the ordering of the hits when - // size >= N*K, upon merging since complete information is not available - // hence we need to modify the size to be N*K. - modifyRequestSize(req, len(indexes)) - } + if len(indexes) > 1 { + modifyRequestSize(req, len(indexes)) } // run search on each index in separate go routine @@ -529,21 +508,8 @@ func MultiSearch(ctx context.Context, req *SearchRequest, indexes ...Index) (*Se } } - if mode := ctx.Value(search.AliasPartitionedModeKey); mode != nil { - aliasForPartitionedIndex, ok := mode.(bool) - if ok && aliasForPartitionedIndex && len(indexes) > 1 { - // this is an alias for a partitioned index, where each child index - // is a partition of a larger index. - // when knn queries are present we need to perform - // a special merge of the hits to ensure that hits corresponding to the - // knn queries are representative of the entire index, not just the - // partition that was searched. If k is 2 and there are 3 partitions, - // then the top 2 hits from each partition is returned, resulting in - // 6 hits in total. This is incorrect because k=2 should return the - // top 2 hits from the entire index, not the top 2 hits from each - // partition. - mergeKNNResults(req, sr) - } + if len(indexes) > 1 { + mergeKNNResults(req, sr) } sortFunc := req.SortFunc() diff --git a/index_impl.go b/index_impl.go index 252a330d6..bda58b7c4 100644 --- a/index_impl.go +++ b/index_impl.go @@ -654,30 +654,7 @@ func (i *indexImpl) SearchInContext(ctx context.Context, req *SearchRequest) (sr Took: searchDuration, Facets: coll.FacetResults(), } - // if AliasPartitionedModeKey is true - // -> this is a child index in an alias for a partitioned index - // -> do not merge the KNN results now, as we need to merge them - // with the results from the other child indexes in the alias - // -> the merge will happen in the top-level MultiSearch - // else if false - // -> this is child index in an user alias for multiple different indexes - // -> NOT a child index in an alias for a partitioned index - // -> merge the KNN results now - // else if not present - // -> this is a regular index - // -> merge the KNN results now - if mode := ctx.Value(search.AliasPartitionedModeKey); mode != nil { - aliasForPartitionedIndex, ok := mode.(bool) - if ok && !aliasForPartitionedIndex { - // this is NOT a child index in an alias for a partitioned index, - // so we can merge the KNN results now. This merge is required - // as the top k results are from each segment, resulting in - // k * numSegments results. - mergeKNNResults(req, rv) - } - } else { - mergeKNNResults(req, rv) - } + mergeKNNResults(req, rv) return rv, nil } diff --git a/knn_test.go b/knn_test.go index 42687fa65..4accb8032 100644 --- a/knn_test.go +++ b/knn_test.go @@ -216,7 +216,6 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { indexMapping.DefaultMapping.AddFieldMappingsAt("vector", vecFieldMapping) index := NewIndexAlias() - index.SetPartitionedMode(true) type testResult struct { score float64 diff --git a/search/search.go b/search/search.go index aa38a2283..9b77251cf 100644 --- a/search/search.go +++ b/search/search.go @@ -174,6 +174,13 @@ type DocumentMatch struct { // if false, all the sub-queries matched PartialMatch bool `json:"partial_match,omitempty"` + // used to indicate the sub-scores that combined to form the + // final score for this document match. This is only populated + // when the search request's query is a DisjunctionQuery + // or a ConjunctionQuery. The length of this slice will be + // the same as the number of sub-queries in the query. + // the order of the scores will match the order of the sub-queries + // in the query. ScoreBreakdown []float64 `json:"score_breakdown,omitempty"` } diff --git a/search_knn.go b/search_knn.go index f47f24b6a..c3bc18033 100644 --- a/search_knn.go +++ b/search_knn.go @@ -181,13 +181,13 @@ func mergeKNNResults(req *SearchRequest, sr *SearchResult) { } } -func modifyRequestSize(req *SearchRequest, numPartitions int) { +func modifyRequestSize(req *SearchRequest, numIndexes int) { if len(req.KNN) > 0 { var minSizeReq int64 for _, knn := range req.KNN { minSizeReq += knn.K } - minSizeReq *= int64(numPartitions) + minSizeReq *= int64(numIndexes) if int64(req.Size) < minSizeReq { req.Size = int(minSizeReq) } From 0ef2e33a1865e042d3dd9ce19f7acb53e8a1ae8c Mon Sep 17 00:00:00 2001 From: Abhinav Dangeti Date: Mon, 20 Nov 2023 13:21:06 -0700 Subject: [PATCH 08/10] Refactor API name: modifyRequestSize -> adjustRequestSizeForKNN, etc. --- index_alias_impl.go | 2 +- search/scorer/scorer_knn.go | 24 ++++++++++--------- .../{search_knn_util.go => util_knn.go} | 0 .../{search_no_knn_util.go => util_no_knn.go} | 0 search/util.go | 1 - search_knn.go | 23 +++++++++++------- search_no_knn.go | 7 +++++- 7 files changed, 34 insertions(+), 23 deletions(-) rename search/searcher/{search_knn_util.go => util_knn.go} (100%) rename search/searcher/{search_no_knn_util.go => util_no_knn.go} (100%) diff --git a/index_alias_impl.go b/index_alias_impl.go index 9225d2ddf..4942eb1ab 100644 --- a/index_alias_impl.go +++ b/index_alias_impl.go @@ -454,7 +454,7 @@ func MultiSearch(ctx context.Context, req *SearchRequest, indexes ...Index) (*Se } originalSize := req.Size if len(indexes) > 1 { - modifyRequestSize(req, len(indexes)) + req.Size = adjustRequestSizeForKNN(req, len(indexes)) } // run search on each index in separate go routine diff --git a/search/scorer/scorer_knn.go b/search/scorer/scorer_knn.go index 9a83773bc..4a93633f9 100644 --- a/search/scorer/scorer_knn.go +++ b/search/scorer/scorer_knn.go @@ -26,8 +26,6 @@ import ( var reflectStaticSizeKNNQueryScorer int -const MaxAllowedScore = 10000.0 - func init() { var sqs KNNQueryScorer reflectStaticSizeKNNQueryScorer = int(reflect.TypeOf(sqs).Size()) @@ -62,6 +60,9 @@ func NewKNNQueryScorer(queryVector []float32, queryField string, queryBoost floa } } +// TODO: Better value needed here? +const maxEuclideanDistance = 10000.0 + func (sqs *KNNQueryScorer) Score(ctx *search.SearchContext, knnMatch *index.VectorDoc) *search.DocumentMatch { rv := ctx.DocumentMatchPool.Get() @@ -69,15 +70,16 @@ func (sqs *KNNQueryScorer) Score(ctx *search.SearchContext, if sqs.includeScore || sqs.options.Explain { var scoreExplanation *search.Explanation score := knnMatch.Score - if score == 0.0 { - // the vector is found to be exactly same as the query vector - // this is a perfect match, so return the max score - score = MaxAllowedScore - } else if sqs.similarityMetric == index.EuclideanDistance { - // safeguard from divide-by-zero - // euclidean distances need to be inverted to work - // tf-idf scoring - score = 1.0 / score + if sqs.similarityMetric == index.EuclideanDistance { + // in case of euclidean distance being the distance metric, + // an exact vector (perfect match), would return distance = 0 + if score == 0 { + score = maxEuclideanDistance + } else { + // euclidean distances need to be inverted to work with + // tf-idf scoring + score = 1.0 / score + } } // if the query weight isn't 1, multiply diff --git a/search/searcher/search_knn_util.go b/search/searcher/util_knn.go similarity index 100% rename from search/searcher/search_knn_util.go rename to search/searcher/util_knn.go diff --git a/search/searcher/search_no_knn_util.go b/search/searcher/util_no_knn.go similarity index 100% rename from search/searcher/search_no_knn_util.go rename to search/searcher/util_no_knn.go diff --git a/search/util.go b/search/util.go index 92301cf9d..b2cb62a2d 100644 --- a/search/util.go +++ b/search/util.go @@ -106,7 +106,6 @@ const ( const SearchIncrementalCostKey = "_search_incremental_cost_key" const QueryTypeKey = "_query_type_key" const FuzzyMatchPhraseKey = "_fuzzy_match_phrase_key" -const AliasPartitionedModeKey = "_alias_partitioned_mode_key" func RecordSearchCost(ctx context.Context, msg SearchIncrementalCostCallbackMsg, bytes uint64) { diff --git a/search_knn.go b/search_knn.go index c3bc18033..53e8829de 100644 --- a/search_knn.go +++ b/search_knn.go @@ -181,17 +181,22 @@ func mergeKNNResults(req *SearchRequest, sr *SearchResult) { } } -func modifyRequestSize(req *SearchRequest, numIndexes int) { - if len(req.KNN) > 0 { - var minSizeReq int64 - for _, knn := range req.KNN { - minSizeReq += knn.K - } - minSizeReq *= int64(numIndexes) - if int64(req.Size) < minSizeReq { - req.Size = int(minSizeReq) +func adjustRequestSizeForKNN(req *SearchRequest, numIndexPartitions int) int { + var adjustedSize int + if req != nil { + adjustedSize = req.Size + if len(req.KNN) > 0 { + var minSizeReq int64 + for _, knn := range req.KNN { + minSizeReq += knn.K + } + minSizeReq *= int64(numIndexPartitions) + if int64(adjustedSize) < minSizeReq { + adjustedSize = int(minSizeReq) + } } } + return adjustedSize } // heap impl diff --git a/search_no_knn.go b/search_no_knn.go index 5b8366288..d4751279a 100644 --- a/search_no_knn.go +++ b/search_no_knn.go @@ -153,7 +153,12 @@ func validateKNN(req *SearchRequest) error { } func mergeKNNResults(req *SearchRequest, sr *SearchResult) { + // no-op } -func modifyRequestSize(req *SearchRequest, numPartitions int) { +func adjustRequestSizeForKNN(req *SearchRequest, numIndexPartitions int) int { + if req != nil { + return req.Size + } + return 0 } From 0ee7015feadc14de974d163b9ec19dd1988601eb Mon Sep 17 00:00:00 2001 From: CascadingRadium Date: Tue, 21 Nov 2023 12:32:32 +0530 Subject: [PATCH 09/10] add conjunction support --- search/scorer/scorer_conjunction.go | 16 +- search/searcher/search_boolean.go | 8 +- search/searcher/search_conjunction.go | 7 +- search/searcher/search_disjunction_slice.go | 1 + search/searcher/util_knn.go | 10 +- search_test.go | 174 ++++++++++++++++++++ 6 files changed, 207 insertions(+), 9 deletions(-) diff --git a/search/scorer/scorer_conjunction.go b/search/scorer/scorer_conjunction.go index 771aba9b7..c94aeebb8 100644 --- a/search/scorer/scorer_conjunction.go +++ b/search/scorer/scorer_conjunction.go @@ -42,7 +42,7 @@ func NewConjunctionQueryScorer(options search.SearcherOptions) *ConjunctionQuery } } -func (s *ConjunctionQueryScorer) Score(ctx *search.SearchContext, constituents []*search.DocumentMatch) *search.DocumentMatch { +func (s *ConjunctionQueryScorer) Score(ctx *search.SearchContext, constituents []*search.DocumentMatch, originalPositions []int) *search.DocumentMatch { var sum float64 var childrenExplanations []*search.Explanation if s.options.Explain { @@ -51,7 +51,19 @@ func (s *ConjunctionQueryScorer) Score(ctx *search.SearchContext, constituents [ scoreBreakdown := make([]float64, len(constituents)) for i, docMatch := range constituents { sum += docMatch.Score - scoreBreakdown[i] = docMatch.Score + if originalPositions != nil { + // for use in conjunction searcher + // the originalPositions are the positions of the searchers + // pre sort, since conjunction searcher sorts the searchers + // in order of their Count(). + scoreBreakdown[originalPositions[i]] = docMatch.Score + } else { + // the indexes of searchers are the original searcher positions + // eg boolean searcher also uses the conjunction scorer, + // with index 0 being the must (conjunction) searcher + // and index 1 being the should (disjunction) searcher + scoreBreakdown[i] = docMatch.Score + } if s.options.Explain { childrenExplanations[i] = docMatch.Expl } diff --git a/search/searcher/search_boolean.go b/search/searcher/search_boolean.go index bf207f810..5f2c7893e 100644 --- a/search/searcher/search_boolean.go +++ b/search/searcher/search_boolean.go @@ -274,7 +274,7 @@ func (s *BooleanSearcher) Next(ctx *search.SearchContext) (*search.DocumentMatch cons = s.matches[0:1] cons[0] = s.currShould } - rv = s.scorer.Score(ctx, cons) + rv = s.scorer.Score(ctx, cons, nil) err = s.advanceNextMust(ctx, rv) if err != nil { return nil, err @@ -284,7 +284,7 @@ func (s *BooleanSearcher) Next(ctx *search.SearchContext) (*search.DocumentMatch // match is OK anyway cons := s.matches[0:1] cons[0] = s.currMust - rv = s.scorer.Score(ctx, cons) + rv = s.scorer.Score(ctx, cons, nil) err = s.advanceNextMust(ctx, rv) if err != nil { return nil, err @@ -302,7 +302,7 @@ func (s *BooleanSearcher) Next(ctx *search.SearchContext) (*search.DocumentMatch cons = s.matches[0:1] cons[0] = s.currShould } - rv = s.scorer.Score(ctx, cons) + rv = s.scorer.Score(ctx, cons, nil) err = s.advanceNextMust(ctx, rv) if err != nil { return nil, err @@ -312,7 +312,7 @@ func (s *BooleanSearcher) Next(ctx *search.SearchContext) (*search.DocumentMatch // match is OK anyway cons := s.matches[0:1] cons[0] = s.currMust - rv = s.scorer.Score(ctx, cons) + rv = s.scorer.Score(ctx, cons, nil) err = s.advanceNextMust(ctx, rv) if err != nil { return nil, err diff --git a/search/searcher/search_conjunction.go b/search/searcher/search_conjunction.go index 21fcf696a..89a441d1e 100644 --- a/search/searcher/search_conjunction.go +++ b/search/searcher/search_conjunction.go @@ -35,6 +35,7 @@ func init() { type ConjunctionSearcher struct { indexReader index.IndexReader searchers []search.Searcher + originalPos []int queryNorm float64 queryNormForKNN float64 currs []*search.DocumentMatch @@ -59,6 +60,7 @@ func NewConjunctionSearcher(ctx context.Context, indexReader index.IndexReader, } sort.Sort(sortedSearchers) searchers := sortedSearchers.searchers + originalPos := sortedSearchers.index // attempt the "unadorned" conjunction optimization only when we // do not need extra information like freq-norm's or term vectors @@ -75,6 +77,7 @@ func NewConjunctionSearcher(ctx context.Context, indexReader index.IndexReader, rv := ConjunctionSearcher{ indexReader: indexReader, options: options, + originalPos: originalPos, searchers: searchers, currs: make([]*search.DocumentMatch, len(searchers)), scorer: scorer.NewConjunctionQueryScorer(options), @@ -107,6 +110,8 @@ func (s *ConjunctionSearcher) Size() int { } } + sizeInBytes += len(s.originalPos) * size.SizeOfInt + return sizeInBytes } @@ -198,7 +203,7 @@ OUTER: } // if we get here, a doc matched all readers, so score and add it - rv = s.scorer.Score(ctx, s.currs) + rv = s.scorer.Score(ctx, s.currs, s.originalPos) // we know all the searchers are pointing at the same thing // so they all need to be bumped diff --git a/search/searcher/search_disjunction_slice.go b/search/searcher/search_disjunction_slice.go index 251463e6a..e14598409 100644 --- a/search/searcher/search_disjunction_slice.go +++ b/search/searcher/search_disjunction_slice.go @@ -106,6 +106,7 @@ func (s *DisjunctionSliceSearcher) Size() int { } sizeInBytes += len(s.matchingIdxs) * size.SizeOfInt + sizeInBytes += len(s.originalPos) * size.SizeOfInt return sizeInBytes } diff --git a/search/searcher/util_knn.go b/search/searcher/util_knn.go index dabc61c54..62f7f9b22 100644 --- a/search/searcher/util_knn.go +++ b/search/searcher/util_knn.go @@ -33,6 +33,8 @@ import ( // and using the same value for knn searchers will make the // knn score dependent on tf-idf. func computeQueryNorm(searchers []search.Searcher) (float64, float64) { + var queryNorm float64 + var queryNormForKNN float64 // first calculate sum of squared weights sumOfSquaredWeights := 0.0 @@ -46,8 +48,12 @@ func computeQueryNorm(searchers []search.Searcher) (float64, float64) { } } // now compute query norm from this - queryNorm := 1.0 / math.Sqrt(sumOfSquaredWeights) - queryNormForKNN := 1.0 / math.Sqrt(sumOfSquaredWeightsForKNN) + if sumOfSquaredWeights != 0.0 { + queryNorm = 1.0 / math.Sqrt(sumOfSquaredWeights) + } + if sumOfSquaredWeightsForKNN != 0.0 { + queryNormForKNN = 1.0 / math.Sqrt(sumOfSquaredWeightsForKNN) + } // finally tell all the downstream searchers the norm for _, searcher := range searchers { if knnSearcher, ok := searcher.(*KNNSearcher); ok { diff --git a/search_test.go b/search_test.go index 37da8da0a..fd56b0959 100644 --- a/search_test.go +++ b/search_test.go @@ -17,6 +17,7 @@ package bleve import ( "encoding/json" "fmt" + "math" "reflect" "strconv" "strings" @@ -26,6 +27,7 @@ import ( "github.com/blevesearch/bleve/v2/analysis" "github.com/blevesearch/bleve/v2/analysis/analyzer/custom" "github.com/blevesearch/bleve/v2/analysis/analyzer/keyword" + "github.com/blevesearch/bleve/v2/analysis/analyzer/simple" "github.com/blevesearch/bleve/v2/analysis/analyzer/standard" html_char_filter "github.com/blevesearch/bleve/v2/analysis/char/html" regexp_char_filter "github.com/blevesearch/bleve/v2/analysis/char/regexp" @@ -3376,3 +3378,175 @@ func TestPercentAndIsoStyleDates(t *testing.T) { } } } + +func roundToDecimalPlace(num float64, decimalPlaces int) float64 { + precision := math.Pow(10, float64(decimalPlaces)) + return math.Round(num*precision) / precision +} + +func TestScoreBreakdown(t *testing.T) { + tmpIndexPath := createTmpIndexPath(t) + defer cleanupTmpIndexPath(t, tmpIndexPath) + + imap := mapping.NewIndexMapping() + textField := mapping.NewTextFieldMapping() + textField.Analyzer = simple.Name + imap.DefaultMapping.AddFieldMappingsAt("text", textField) + + documents := map[string]map[string]interface{}{ + "doc1": { + "text": "lorem ipsum dolor sit amet consectetur adipiscing elit do eiusmod tempor", + }, + "doc2": { + "text": "lorem dolor amet adipiscing sed eiusmod", + }, + "doc3": { + "text": "ipsum sit consectetur elit do tempor", + }, + "doc4": { + "text": "lorem ipsum sit amet adipiscing elit do eiusmod", + }, + } + + idx, err := New(tmpIndexPath, imap) + if err != nil { + t.Fatal(err) + } + defer func() { + err = idx.Close() + if err != nil { + t.Fatal(err) + } + }() + + batch := idx.NewBatch() + for docID, doc := range documents { + err := batch.Index(docID, doc) + if err != nil { + t.Fatal(err) + } + } + err = idx.Batch(batch) + if err != nil { + t.Fatal(err) + } + + type testResult struct { + docID string // doc ID of the hit + score float64 + scoreBreakdown []float64 + } + type testStruct struct { + query string + operator int + expectHits []testResult + } + testQueries := []testStruct{ + { + // trigger conjunction searcher from match query with operator 1 + // expect dolor and tempor to have higher term score - since present in lesser docs and having same term freq + query: "lorem dolor amet adipiscing do tempor", + operator: 1, + expectHits: []testResult{ + { + docID: "doc1", + score: 0.815545, + scoreBreakdown: []float64{0.11147035536863306, 0.18483179634014485, 0.11147035536863306, 0.11147035536863306, 0.11147035536863306, 0.18483179634014485}, + }, + }, + }, + { + // trigger disjunction heap searcher from match query with operator 0 (>10 searchers) + // expect score breakdown to have a 0 at BLANK + query: "lorem BLANK ipsum BLANK BLANK dolor sit amet consectetur BLANK adipiscing BLANK elit sed do eiusmod tempor BLANK BLANK", + operator: 0, + expectHits: []testResult{ + { + docID: "doc1", + score: 0.3034548543819603, + scoreBreakdown: []float64{0.040398807605268316, 0, 0.040398807605268316, 0, 0, 0.0669862776967768, 0.040398807605268316, 0.040398807605268316, 0.0669862776967768, 0, 0.040398807605268316, 0, 0.040398807605268316, 0, 0.040398807605268316, 0.040398807605268316, 0.0669862776967768, 0, 0}, + }, + { + docID: "doc4", + score: 0.15956816751152955, + scoreBreakdown: []float64{0.04737179972998534, 0, 0.04737179972998534, 0, 0, 0, 0.04737179972998534, 0.04737179972998534, 0, 0, 0.04737179972998534, 0, 0.04737179972998534, 0, 0.04737179972998534, 0.04737179972998534, 0, 0, 0}, + }, + { + docID: "doc2", + score: 0.14725661652397853, + scoreBreakdown: []float64{0.05470024557900147, 0, 0, 0, 0, 0.09069985124905133, 0, 0.05470024557900147, 0, 0, 0.05470024557900147, 0, 0, 0.15681178542754148, 0, 0.05470024557900147, 0, 0, 0}, + }, + { + docID: "doc3", + score: 0.12637916362550797, + scoreBreakdown: []float64{0, 0, 0.05470024557900147, 0, 0, 0, 0.05470024557900147, 0, 0.09069985124905133, 0, 0, 0, 0.05470024557900147, 0, 0.05470024557900147, 0, 0.09069985124905133, 0, 0}, + }, + }, + }, + { + // trigger disjunction slice searcher from match query with operator 0 (< 10 searchers) + // expect BLANK to give a 0 in score breakdown + query: "BLANK lorem ipsum BLANK BLANK dolor sit BLANK", + operator: 0, + expectHits: []testResult{ + { + docID: "doc1", + score: 0.1340684440934241, + scoreBreakdown: []float64{0, 0.05756326446708409, 0.05756326446708409, 0, 0, 0.09544709478559595, 0.05756326446708409, 0}, + }, + { + docID: "doc4", + score: 0.07593627256602972, + scoreBreakdown: []float64{0, 0.06749890894758198, 0.06749890894758198, 0, 0, 0, 0.06749890894758198, 0}, + }, + { + docID: "doc2", + score: 0.05179425287147191, + scoreBreakdown: []float64{0, 0.0779410306721006, 0, 0, 0, 0.129235980813787, 0, 0}, + }, + { + docID: "doc3", + score: 0.0389705153360503, + scoreBreakdown: []float64{0, 0, 0.0779410306721006, 0, 0, 0, 0.0779410306721006, 0}, + }, + }, + }, + } + + for _, dtq := range testQueries { + + mq := NewMatchQuery(dtq.query) + mq.SetField("text") + mq.SetOperator(query.MatchQueryOperator(dtq.operator)) + sr := NewSearchRequest(mq) + sr.Explain = true + res, err := idx.Search(sr) + if err != nil { + t.Fatal(err) + } + if len(res.Hits) != len(dtq.expectHits) { + t.Fatalf("expected %d hits, got %d", len(dtq.expectHits), len(res.Hits)) + } + for i, hit := range res.Hits { + if hit.ID != dtq.expectHits[i].docID { + t.Fatalf("expected docID %s, got %s", dtq.expectHits[i].docID, hit.ID) + } + hit.Score = roundToDecimalPlace(hit.Score, 3) + expectScore := roundToDecimalPlace(dtq.expectHits[i].score, 3) + if hit.Score != expectScore { + t.Fatalf("expected score %f, got %f", dtq.expectHits[i].score, hit.Score) + } + if len(hit.ScoreBreakdown) != len(dtq.expectHits[i].scoreBreakdown) { + t.Fatalf("expected %d score breakdown, got %d", len(dtq.expectHits[i].scoreBreakdown), len(hit.ScoreBreakdown)) + } + for j, score := range hit.ScoreBreakdown { + actualScore := roundToDecimalPlace(score, 3) + expectScore := roundToDecimalPlace(dtq.expectHits[i].scoreBreakdown[j], 3) + if actualScore != expectScore { + t.Fatalf("expected score breakdown %f, got %f", dtq.expectHits[i].scoreBreakdown[j], score) + } + } + } + } + +} From 671df1849d7dcd035f6f2d8660a9b2f7fee5446e Mon Sep 17 00:00:00 2001 From: CascadingRadium Date: Tue, 21 Nov 2023 21:14:22 +0530 Subject: [PATCH 10/10] use maxKNNScore --- knn_test.go | 9 +++++---- search/scorer/scorer_knn.go | 26 +++++++++++++------------- 2 files changed, 18 insertions(+), 17 deletions(-) diff --git a/knn_test.go b/knn_test.go index 4accb8032..32e2ff62d 100644 --- a/knn_test.go +++ b/knn_test.go @@ -20,6 +20,7 @@ package bleve import ( "archive/zip" "encoding/json" + "math" "math/rand" "testing" @@ -355,8 +356,8 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { numIndexPartitions: 1, expectedResults: map[string]testResult{ "doc7": { - score: 2357.022603955158, - scoreBreakdown: []float64{0, 0, 7071.067811865475}, + score: math.MaxFloat64, + scoreBreakdown: []float64{0, 0, math.MaxFloat64 / 3.0}, }, "doc29": { score: 0.6774608026082964, @@ -402,8 +403,8 @@ func runKNNTest(t *testing.T, randomizeDocuments bool) { numIndexPartitions: 4, expectedResults: map[string]testResult{ "doc7": { - score: 2357.022603955158, - scoreBreakdown: []float64{0, 0, 7071.067811865475}, + score: math.MaxFloat64, + scoreBreakdown: []float64{0, 0, math.MaxFloat64 / 3.0}, }, "doc29": { score: 0.567426591648309, diff --git a/search/scorer/scorer_knn.go b/search/scorer/scorer_knn.go index 4a93633f9..7623fec46 100644 --- a/search/scorer/scorer_knn.go +++ b/search/scorer/scorer_knn.go @@ -18,6 +18,7 @@ package scorer import ( + "math" "reflect" "github.com/blevesearch/bleve/v2/search" @@ -60,8 +61,9 @@ func NewKNNQueryScorer(queryVector []float32, queryField string, queryBoost floa } } -// TODO: Better value needed here? -const maxEuclideanDistance = 10000.0 +// Score used when the knnMatch.Score = 0 -> +// the query and indexed vector are exactly the same. +const maxKNNScore = math.MaxFloat64 func (sqs *KNNQueryScorer) Score(ctx *search.SearchContext, knnMatch *index.VectorDoc) *search.DocumentMatch { @@ -70,20 +72,18 @@ func (sqs *KNNQueryScorer) Score(ctx *search.SearchContext, if sqs.includeScore || sqs.options.Explain { var scoreExplanation *search.Explanation score := knnMatch.Score - if sqs.similarityMetric == index.EuclideanDistance { - // in case of euclidean distance being the distance metric, - // an exact vector (perfect match), would return distance = 0 - if score == 0 { - score = maxEuclideanDistance - } else { - // euclidean distances need to be inverted to work with - // tf-idf scoring - score = 1.0 / score - } + // in case of euclidean distance being the distance metric, + // an exact vector (perfect match), would return distance = 0 + if score == 0 { + score = maxKNNScore + } else { + // euclidean distances need to be inverted to work with + // tf-idf scoring + score = 1.0 / score } // if the query weight isn't 1, multiply - if sqs.queryWeight != 1.0 { + if sqs.queryWeight != 1.0 && score != maxKNNScore { score = score * sqs.queryWeight }