您可以将MongoDB Vector Search 和MongoDB Search 查询组合成混合搜索,以获得统一结果。
本教程演示如何对 sample_mflix.embedded_movies 集合运行混合搜索,其中包含有关电影的详细信息。具体来说,本教程将指导您完成以下步骤:
在
plot_embedding_voyage_4_large字段上创建 MongoDB 向量搜索索引。该字段包含使用 Voyage AI 的voyage-4-large嵌入模型创建的向量嵌入(2048 维),用于表示电影情节的摘要。在
sample_mflix.embedded_movies集合上创建MongoDB Search索引。使用以下技术运行查询以合并
$vectorSearch查询和$search查询的结果:语义提升
倒数秩融合
分数融合
为什么选择混合搜索?
混合搜索是针对相同查询条件的不同搜索方法(如全文搜索和语义搜索)的聚合。虽然全文搜索对于查询词的精确匹配很有效,但语义搜索还提供了一个额外好处,即使文档不包含精确的查询词,也能识别语义相似的文档。这确保了同义匹配和上下文相似的匹配项也包含在两种搜索方法的组合结果中。
相反,如果数据集中有专有名词或特定关键词的词元,这些词元在数据集中使用的上下文相同,您不希望在培训嵌入模型时考虑这些词元,则向量搜索可能会受益于与全文搜索相结合。
您还可以为每个查询的每种搜索方法设立权重。根据全文或语义搜索结果是否与查询最相关且最合适,您可以增加每个查询的搜索方法的权重。
您可以应用以下技术来实现混合搜索:
技术 | 语义提升 | 倒数排名融合 | 相对分数融合 | |||
用途 | 通过提升与向量搜索匹配的文档来提高全文搜索结果的准确性。在检索非常大的结果集时很有用。 | 通过计算结果中文档的倒数排名,将不同搜索方法的结果合并到单个排名结果设立。 | 通过计算结果中文档的评分,将不同搜索方法的结果合并到单个排名结果设立。 | |||
排序方法 |
|
|
| |||
评分方法 | 通过加权向量搜索搜索分数来提高与向量搜索结果匹配的文档的全文结果分数。 | 使用以下公式计算分数: 然后,对于每种搜索方法应用不同的权重 ( | 使用以下公式计算分数: | |||
搜索功能 |
| 支持在后续聚合阶段(例如 | 支持在后续聚合阶段(例如 | |||
输出 | 单个结果设立,其中包含以下文档: | 包含来自两种搜索方法的文档的单个结果设立。 | 包含来自两种搜索方法的文档的单个结果设立。 |
先决条件
在开始之前,您必须具备以下条件:
MongoDB版本为 v8.0 或更高版本的Atlas 集群。
注意
确保您的Atlas 集群有足够的内存来存储MongoDB Search 和MongoDB Vector Search 索引并运行高性能查询。
将 sample_mflix 数据加载到 Atlas 集群。
mongosh对Atlas 集群运行查询:Project Data Access Admin访问权限用于创建MongoDB Vector Search 和MongoDB Search 索引的项目。
创建MongoDB Vector Search 和MongoDB Search 索引
本部分演示如何在sample_mflix.embedded_moviescollection中的字段上创建以下索引:
plot_embedding_voyage_4_large字段上的MongoDB Vector Search索引,用于针对该字段运行向量查询。MongoDB Search 索引,可对所有可动态索引的字段进行动态索引,以对这些字段运行全文搜索。
使用mongosh 连接到集群。
要学习;了解更多信息,请参阅通过mongosh连接到集群。
定义MongoDB Vector Search索引。
运行以下命令。查询集合时,此索引定义将 plot_embedding_voyage_4_large字段作为MongoDB Vector Search字段进行索引。
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 );
运行混合搜索查询
本节将演示如何分别使用 和$vectorSearch$search 管道阶段,在 和 字段中查询sample_mflix.embedded_movies 集合中的 charming animal 数据。plot_embedding_voyage_4_largefullplot该查询通过使用相同文档的 分数提升全文分数,从而提高了$search $vectorSearch查询的相关性。
语义提升查询
为嵌入创建文件。
创建一个名为
query-embeddings.js的文件。touch query-embeddings.js 将以下嵌入复制并粘贴到该文件中。
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使用 mongosh 连接到您的集群。
在终端窗口中打开mongosh并连接到您的集群。有关连接的详细说明,请参阅通过mongosh连接到集群。
针对 embedded_movies集合运行以下MongoDB搜索查询。
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 } ]
关于查询
示例查询会根据$search 结果分数提升$vectorSearch 结果,以返回最相关的文档。对于语义提升,请执行以下步骤:
运行
$vectorSearch查询。使用 over 请求值指定要考虑的候选数量超过指定限制。通过over请求,您可以完成以下操作:
在初始搜索中考虑大量且广泛的文档。
完善后续阶段的评分计算。
该查询使用以下计算来确定向量搜索期间要考虑的候选数量:
numCandidates = limit * over request 结果根据最低分数阈值 (
vectorCutoff) 进行筛选。缩放向量搜索分数以调整向量搜索结果对文档评分和排名的影响。
使用
vectorWeight参数设立权重,并将向量搜索分数乘以vectorWeight。这控制了向量搜索结果的重要性,并确保只考虑语义上最相关的文档。运行
$search查询并提高与向量搜索结果匹配的文档的分数。
示例查询定义了以下变量:
vectorWeight增加向量搜索分数的权重,数字越小,权重越高。vectorCutoff设立要提升结果的最小向量分数。numResults以指定所需的搜索结果数量numCandidates来计算初始搜索期间要考虑的候选数量。它使用以下公式计算候选数量:numCandidates = numResults x overRequestFactor
该示例查询使用以下流水线阶段对文档集进行语义搜索,并检索结果中文档的对等排序:
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搜索 fullplot 字段中包含术语 charming animal 的电影。对于结果中与向量搜索结果中的 |
倒数排名融合查询
您可以运行查询,从语义搜索和全文搜索中检索排序后的搜索结果,并根据结果数组中的位置为结果中的文档分配倒数排名分数。要了解有关倒数排名融合技术以及如何运行倒数排名融合查询,请参阅 执行混合向量和全文搜索。
相对分数融合查询
您可以运行查询,从语义和全文搜索中检索评分搜索结果,并在将管道中的结果合并为每个文档的单个聚合分数之前应用sigmoid表达式对分数进行规范化。要了解有关分数熔合技术以及如何运行分数熔合查询的更多信息,请参阅执行混合向量和全文搜索。