MongoDB ベクトル検索とMongoDB Search クエリをハイブリッド検索として使用すると、統合結果が得られます。
このチュートリアルでは、映画の詳細を含むsample_mflix.embedded_moviesコレクションでハイブリッド検索を実行する方法を説明します。 具体的には、このチュートリアルでは次の手順について説明します。
plot_embedding_voyage_4_largeフィールドにMongoDBベクトル検索インデックスを作成します。このフィールドには、映画のあらすじの要約を表現するベクトル埋め込み(Voyage AIのvoyage-4-large埋め込みモデルを使用して作成された2048次元のもの)が含まれています。sample_mflix.embedded_moviesコレクションにMongoDB Searchインデックスを作成します。次の方法を使用して、
$vectorSearchクエリと$searchクエリの結果を組み合わせてクエリを実行します。セマンティック ブースト
因果ランクの統合
スコアフュージョン
ハイブリッド検索を使用する理由
ハイブリッド検索とは、同じクエリ条件に対して全文検索やセマンティック検索などの異なる検索方法を集約したものです。 全文検索はクエリ用語の完全一致を見つけるのに効果的ですが、ドキュメントに完全なクエリ用語が含まれていない場合でも、セマンティック検索ではセマンティック類似ドキュメントを識別できるという追加の利点があります。 これにより、シノニムとコンテキストが類似する一致も、両方の検索方法の合計結果に含まれるようになります。
逆に、データセットで使用されるのと同じコンテキストで埋め込みモデルの訓練で考慮されることが予想されない場合は、ベクトル検索に次のことがメリットをもたらす可能性があります。全文検索と組み合わせて使用します。
クエリごとに、各検索方法の重みを設定することもできます。 全文検索結果とセマンティック検索結果がクエリに最も関連し、適切であるかどうかに基づいて、クエリごとのその検索方法の重みを増やすことができます。
ハイブリッド検索を実現するには、次の手法を適用できます。
手法 | セマンティック ブースト | 因果ランクの統合 | 相対スコア融合 | |||
目的 | ベクトル検索に一致するドキュメントを優先することで、全文検索結果の精度を向上させます。非常に大きな結果セットを検索する場合に便利です。 | 結果内のドキュメントの逆ランクを計算することにより、異なる検索メソッドの結果を単一のランク付けされた結果セットに結合します。 | 結果内のドキュメントのスコアを計算することにより、異なる検索メソッドの結果を単一のランク付けされた結果セットに結合します。 | |||
ランキング方法 |
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スコアリング方法 | ベクトル検索の結果に一致するドキュメントの全文結果スコアを、重み付きベクトル検索スコアでブーストします。 | 次の式を使用してスコアを計算します。 次に、検索方法ごとに異なる重み( | 次の式を使用してスコアを計算します。 | |||
検索機能 |
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出力 | のドキュメントを含む単一の結果セット | 両方の検索方法のドキュメントを含む単一の結果セット。 | 両方の検索方法のドキュメントを含む単一の結果セット。 |
前提条件
始める前に、以下のものを用意してください。
MongoDBバージョン v8.0 以上を搭載した Atlas クラスター。
注意
MongoDB Search とMongoDB ベクトル検索インデックスの両方を保存し、パフォーマンス クエリを実行するのに十分なメモリがあることを Atlas クラスターに確認してください。
Atlas クラスターにロードされたsample_mflix データ。
mongoshAtlas クラスターでクエリを実行するには、次の手順に従います。Project Data Access Adminプロジェクトにアクセスして、 MongoDB ベクトル検索とMongoDB Search インデックスを作成します。
MongoDB ベクトル検索とMongoDB Search インデックスの作成
このセクションでは、 sample_mflix.embedded_moviesコレクションのフィールドに次のインデックスを作成する方法について説明します。
MongoDB ベクトル検索インデックス(そのフィールドに対してベクトルクエリを実行中ための
plot_embedding_voyage_4_largeフィールドの MongoDB Vector Searchインデックス。フィールドに対して全文検索を実行するために、ダイナミックにインデックス可能なすべてのフィールドをダイナミックにインデックスする MongoDB Search インデックス。
mongosh を使用してクラスターに接続します。
詳細については、 mongosh経由でクラスターに接続する を参照してください。
MongoDB ベクトル検索インデックスを定義します。
次のコマンドを実行します。このインデックス定義は、コレクションをクエリするときに、plot_embedding_voyage_4_largeフィールドをMongoDB ベクトル検索フィールドとしてインデックス化します。
1 db.embedded_movies.createSearchIndex( 2 "hybrid-vector-search", 3 "vectorSearch", 4 { 5 "fields": [ 6 { 7 "type": "vector", 8 "path": "plot_embedding_voyage_4_large", 9 "numDimensions": 2048, 10 "similarity": "dotProduct" 11 } 12 ] 13 } 14 );
ハイブリッド検索クエリの実行
このセクションでは、 および $vectorSearch$searchパイプラインステージを使用して、 コレクションのデータに対して および フィールドで charmingsample_mflix.embedded_movies animal をクエリする方法を説明します。plot_embedding_voyage_4_largefullplot$searchクエリは、同じドキュメントの$vectorSearch スコアを使用して全文スコアをブーストすることで、 クエリの関連性を向上させます。
セマンティック ブースト クエリ
埋め込み用のファイルを作成します。
query-embeddings.jsという名前のファイルを作成します。touch query-embeddings.js 次の埋め込みをコピーしてファイルに貼り付けます。
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mongosh を使用してクラスターに接続します。
ターミナルウィンドウで mongosh を開き、クラスターに接続します。接続の詳細な手順については、 mongosh経由でクラスターに接続する を参照してください。
embedded_moviesコレクションに対して次のMongoDB Search クエリを実行します。
1 vectorWeight = 1; 2 vectorCutoff = 0.7; 3 numResults = 20; 4 numCandidates = numResults * 10; 5 6 // Execute the vector search 7 vectorResults = db.embedded_movies.aggregate([ 8 { 9 $vectorSearch: { 10 "index": "hybrid-vector-search", 11 "path": "plot_embedding_voyage_4_large", 12 "queryVector": CHARMING_ANIMAL_EMBEDDING, 13 "numCandidates": numCandidates, 14 "limit": numResults 15 } 16 }, 17 { 18 $project: { 19 "_id": 1, 20 "title": 1, 21 "fullplot": 1, 22 "vectorScore": { $meta: "vectorSearchScore" } 23 } 24 }, 25 { 26 $match: { 27 "vectorScore": { $gte: vectorCutoff } 28 } 29 } 30 ]).toArray(); 31 32 // Create a map for fast lookup 33 vectorScoresMap = {}; 34 vectorResults.forEach(result => { 35 vectorScoresMap[result._id] = result.vectorScore * vectorWeight; 36 }); 37 38 // Execute the text search with boosting based just on ID 39 textResults = db.embedded_movies.aggregate([ 40 { 41 $search: { 42 "index": "hybrid-full-text-search", 43 "compound": { 44 "should": [ 45 { 46 "text": { 47 "query": "charming animal", 48 "path": "fullplot", 49 "fuzzy": {} 50 } 51 }, 52 ...Object.keys(vectorScoresMap).map(id => ({ 53 "equals": { 54 "path": "_id", 55 "value": id, 56 "score": { boost: { value: vectorScoresMap[id] } } 57 } 58 })) 59 ] 60 } 61 } 62 }, 63 { 64 $limit: 20 65 }, 66 { 67 $project: { 68 "_id": 1, 69 "title": 1, 70 "fullplot": 1, 71 "score": { $meta: "searchScore" } 72 } 73 } 74 ]).toArray();
[ { _id: ObjectId('573a13a3f29313caabd0d0a8'), fullplot: "Dr. John Dolittle the beloved doctor is back, but this time around he plays cupid to bumbling circus bear Archie as he's so smitten by a Pacific Western bear female, Ava. Dr. Dolittle must help a group of forest creatures to save their forest. But with the aid of his mangy, madcap animal friends, Dr. Dolittle must teach Archie the ways of true romance in time to save his species and his home before their habit is gone. So John held a meeting for every animal in the forest to not give up without a fight no matter what kind of animal expression they have and everyone agrees to do it and save their home.", title: 'Dr. Dolittle 2', score: 3.2186570167541504 }, { _id: ObjectId('573a13c5f29313caabd71215'), title: 'The Bannen Way', fullplot: 'A slick, sexy, action-packed show about Neal Bannen, a charming con-man with a police chief for a father, a mob boss for an uncle and a weakness for beautiful women, who wants to turn his life around and leave the criminal lifestyle forever.', score: 3.066267967224121 }, { _id: ObjectId('573a1394f29313caabce074d'), title: 'Perri', fullplot: 'This True Life Fantasy follows and shows how the life of a female squirrel, Perri, in the forest is filled with danger and fraught with peril. When not fleeing her natural enemy, the Marten, Perri finds time to fall in love with her prince-charming male squirrel.', score: 3.0323688983917236 }, { _id: ObjectId('573a139af29313caabcf0e1d'), title: 'Wild America', fullplot: 'Three brothers - Marshall, Marty and Mark dream of becoming naturalists and portraying animal life of America. One summer their dream comes true, they travel through America, filming alligators, bears and moose.', score: 2.9388742446899414 }, { _id: ObjectId('573a13e3f29313caabdc08f2'), title: 'Bang Bang', fullplot: "A chance encounter of the unassuming bank receptionist Harleen Sahni with the charming yet mysterious Rajveer Nanda, results in an on-rush of ditched planes, car chases, shoot-outs, bombing raids and general global mayhem. But as the transcontinental chase ensues with Rajveer convincing Harleen that he's the good guy, can she really trust him, and will trust matter when the bullets start flying?", score: 2.7579541206359863 }, { _id: ObjectId('573a1393f29313caabcdbe7c'), fullplot: "In this charming film based on the popular L. Frank Baum stories, Dorothy and her dog Toto are caught in a tornado's path and somehow end up in the land of Oz. Here she meets some memorable friends and foes in her journey to meet the Wizard of Oz who everyone says can help her return home and possibly grant her new friends their goals of a brain, heart and courage.", title: 'The Wizard of Oz', score: 2.703585147857666 }, { _id: ObjectId('573a1397f29313caabce80f6'), title: 'Gauche the Cellist', fullplot: 'A cellist in a small orchestra receives help from animals to help him practice his music.', score: 2.692498207092285 }, { _id: ObjectId('573a13bcf29313caabd55f51'), title: 'The Missing Lynx', fullplot: "A group of animals look for a way off of an eccentric billionaire's own personal Noah's Ark.", score: 2.6747734546661377 }, { _id: ObjectId('573a1397f29313caabce8aac'), title: 'The Grey Fox', fullplot: `Old West highwayman Bill Miner, known to Pinkertons as "The Gentleman Bandit," is released in 1901 after 33 years in prison, a genial and charming old man. He goes to Washington to live and work with his sister's family. But the world has changed much while he has been away, and he just can't adjust. So he goes to Canada and returns to the only thing familiar to him -- robbery (with stagecoaches changed to trains).`, score: 2.651318073272705 }, { _id: ObjectId('573a13c7f29313caabd75624'), fullplot: 'Extraordinary teen John Smith (Pettyfer) is a fugitive on the run from ruthless enemies sent to destroy him. Changing his identity, moving from town to town with his guardian Henri (Olyphant), John is always the new kid with no ties to his past. In the small Ohio town he now calls home, John encounters unexpected, life-changing events-his first love (Agron), powerful new abilities and a connection to the others who share his incredible destiny.', title: 'I Am Number Four', score: 2.6149134635925293 }, { _id: ObjectId('573a1392f29313caabcdb48b'), title: 'Snow White and the Seven Dwarfs', fullplot: 'The first, and by far most memorable full-length animated feature from the Disney Studios, "Snow White and the Seven Dwarfs" may have been superseded technically by many of the films that followed it. But its simple story of a charming little princess saved from the evil deeds of her wicked stepmother, the queen, by a group of seven adorable dwarfs made history when it was first released in December, 1937 and has since become an incomparable screen classic.', score: 2.6010334491729736 }, { _id: ObjectId('573a13b4f29313caabd4070d'), title: 'Paragraph 78', fullplot: 'This is a wonderful movie about a group of men frontier the Nashville area who like to make puppets out of real animals', score: 2.573139190673828 }, { _id: ObjectId('573a1393f29313caabcdc6e9'), title: 'Tom Dick and Harry', fullplot: "Working girl/telephone operator Janie is engaged to conservative, dull, but very reliable car salesman Tom, who offers her a safe, stable marriage. Then she meets unconventional slacker Harry, a philosophical car mechanic without much ambition although she does hear bells when they kiss. Through Harry, the fickle Janie meets Dick, a handsome and charming millionaire playboy, who embodies her greatest romantic fantasies, and after a champagne-filled overnight flight to Chicago, she thinks she's met her dream man, but has she?", score: 2.5526208877563477 }, { _id: ObjectId('573a13acf29313caabd28039'), title: 'The Science of Sleep', fullplot: 'Following the death of his father in Mexico, Stèphane Miroux, a shy insecure young man, agrees to come to Paris to draw closer to his widowed mother Christine. He lands a boring job at a calendar-making firm and falls in love with his charming neighbor Stèphanie. But conquering her is no bed of roses for the young man and the only solution he finds to put up with the difficulties he is going through is escape into a dream world...', score: 2.5526208877563477 }, { _id: ObjectId('573a13b3f29313caabd3b4e1'), fullplot: `Manny the woolly mammoth, Sid the sloth, Diego the saber-toothed tiger, and the hapless prehistoric squirrel/rat known as Scrat are still together and enjoying the perks of their now melting world. Manny may be ready to start a family, but nobody has seen another mammoth for a long time; Manny thinks he may be the last one. That is, until he miraculously finds Ellie, the only female mammoth left in the world. Their only problems: They can't stand each other--and Ellie somehow thinks she's a possum! Ellie comes with some excess baggage in the form of her two possum "brothers"-- Crash and Eddie, a couple of daredevil pranksters and cocky, loud-mouthed troublemakers. Manny, Sid and Diego quickly learn that the warming climate has one major drawback: A huge glacial dam holding off oceans of water is about to break, threatening the entire valley. The only chance of survival lies at the other end of the valley. So our three heroes, along with Ellie, Crash and Eddie, form the most unlikely family--in any "Age"-- as they embark on a mission across an ever-changing, increasingly dangerous landscape towards their salvation.`, title: 'Ice Age: The Meltdown', score: 2.518824338912964 }, { _id: ObjectId('573a1395f29313caabce1b5f'), title: 'Hatari!', fullplot: `John Wayne and his ensemble cast cavort over the African landscape filling orders from zoos for wild animals. Bruce Cabot plays "the Indian", a womanizing sharpshooter who is gored by a rhino in the opening scenes of the film. This becomes a running theme through the movie; their bad luck in catching rhinos, and provides the climactic ending chase. While Bruce is in the hospital, Elsa Martinelli shows up as a woman photographer from a Swiss zoo, and John wants to send her packing. She strongarms the Duke into letting her stay by promising that her zoo will buy most of their animals this season if she's allowed to go along on the hunts and take photos. Hardy Kruger, Gerard Blain, Michelle Girardon and Valentin de Vargas round out the group. They traipse over the African landscape capturing animals; Elsa also has a running gag where she collects baby elephants as the movie goes along. In the end she's acquired three of them.`, score: 2.4652297496795654 }, { _id: ObjectId('573a13c5f29313caabd6e7a4'), title: 'Merantau', fullplot: `In Minangkabau, West Sumatera, Yuda a skilled practitioner of Silat Harimau is in the final preparations to begin his "Merantau" a century's old rites-of-passage to be carried out by the community's young men that will see him leave the comforts of his idyllic farming village and make a name for himself in the bustling city of Jakarta. After a series of setbacks leave Yuda homeless and uncertain about his new future, a chance encounter results in him defending the orphaned Astri from becoming the latest victim of a European human trafficking ring led by the wildly psychotic, Ratger and his right-hand man Lars. With Ratger injured in the mèlèe and seeking both his "merchandise" and bloody retribution, Yuda's introduction to this bustling city is a baptism of fire as he is forced to go on the run with Astri and her younger brother Adit as all the pimps and gangsters that inhabit the night hound the streets chasing their every step. With escape seemingly beyond their grasp, Yuda has no choice but to face his attackers in an adrenaline charged, jaw-dropping finale.`, score: 2.4573898315429688 }, { _id: ObjectId('573a1398f29313caabceaddd'), title: 'Dead Heat', fullplot: 'Roger Mortis and Doug Bigelow are cops that are chasing crooks that are dead serious about crime. Or should I say they are chasing dead crooks perpetrating serious crimes? Seems some nutcase has learned how to bring back the dead and is sending them on crime sprees. Now these indestructable goons are in the way of officers Mortis and Bigelow. To even things up, when Mortis is killed (in the line of duty, of course) he gets a jump start from the Resurrection machine and takes the fight to the zombie bad guys.', score: 2.398913860321045 }, { _id: ObjectId('573a1393f29313caabcde3af'), title: 'Mighty Joe Young', fullplot: `In Africa, the girl Jill Young trades a baby gorilla with two natives and raises the animal. Twelve years later, the talkative and persuasive promoter Max O'Hara organizes a safari to Africa with the Oklahoma cowboy Gregg to bring attractions to his new night-club in Hollywood. They capture several lions and out of blue, they see a huge gorilla nearby their camping and they try to capture the animal. However, the teenager Jill Young stops the men that intended to kill her gorilla. Max seduces Jill with a fancy life in Hollywood and she signs a contract with him where the gorilla Joseph "Joe" Young would be the lead attraction. Soon she realizes that her dream is a nightmare to Joe and she asks Max to return to Africa. However he persuades her to stay a little longer in the show business. But when three alcoholic costumers give booze to Joe, the gorilla destroys the spot and is sentenced by the justice to be sacrificed. Will Jill, Gregg and Max succeed in saving Joe?`, score: 2.3978404998779297 }, { _id: ObjectId('573a13c7f29313caabd75592'), fullplot: 'FBI agent Malcolm Turner and his son, Trent, go undercover at an all-girls performing arts school after Trent witnesses a murder. Posing as Big Momma and Charmaine, they must find the murderer before he finds them.', title: 'Big Mommas: Like Father, Like Son', score: 2.3933444023132324 } ]
クエリについて
サンプルクエリは、 結果スコアに基づいて$search $vectorSearch結果をブーストし、最も関連性の高いドキュメントを返します。セマンティック ブーストでは、次の手順を実行します。
$vectorSearchクエリを実行します。指定された制限以上の候補数を指定して、考慮する必要がある値は、オーバーリクエスト値を使用します。オーバーリクエストを使用すると、次のことが実行できます。
考慮する必要がある多数のドキュメント プールを初期検索に含めます。
後続のステージでスコアリングの計算を調整します。
クエリは、次の計算を使用して、ベクトル検索中に考慮する候補の数を決定します。
numCandidates = limit * over request 結果は、最小スコアしきい値(
vectorCutoff)に基づいてフィルタリングされます。ベクトル検索スコアをスケーリングして、ドキュメントのスコアリングとランキングへのベクトル検索結果の影響を調整します。
vectorWeightパラメーターを使用して重みを設定し、ベクトル検索スコアにvectorWeightを掛けます。これによりベクトル検索結果の重要性が制御され、最もセマンティックに関連するドキュメントのみが考慮されるようになります。$searchクエリを実行し、ベクトル検索の結果に一致するドキュメントのスコアをブーストします。
サンプルクエリでは、次の変数を定義します。
vectorWeightベクトル検索スコアに重みを追加し、数値が低いほど重みが高くなります。vectorCutoff結果がブーストされるための最小ベクトルスコアを設定します。numResultsは、検索結果の数を指定しますnumCandidates初期検索中に考慮する候補の数を計算します。次の式を使用して、候補者の数を計算します。numCandidates = numResults x overRequestFactor
サンプル クエリでは、次のパイプライン ステージを使用して コレクションに対してセマンティック検索を実行し、結果内のドキュメントの逆ランクを検索します。
クエリの | |
fullplot フィールドに charming animal という用語を含む映画を検索します。ベクトル検索結果の |
相互ランクの統合クエリ
セマンティック検索と全文検索からソートされた検索結果を検索し、結果配列内のドキュメントの位置に基づいて結果内のドキュメントに逆数ランク スコアを割り当てるクエリを実行できます。逆数ランクフュージョン技術と逆数ランクフュージョン クエリの実行方法の詳細については、「ハイブリッド ベクトル検索と全文検索の実行」を参照してください。
相対スコアフュージョンクエリ
セマンティック検索と全文検索からスコア付き検索結果を取得し、sigmoid式を適用してスコアを正規化してから、パイプラインからの結果を結合して各ドキュメントの単一の集計スコアにするクエリを実行できます。スコアフュージョンの技術とスコアフュージョンクエリの実行方法の詳細については、「ハイブリッドベクトル検索と全文検索の実行」を参照してください。