knnBeta
Atlas Search knnVector 字段类型和 knnBeta 操作符现已弃用。相反，我们建议您使用 vectorSearch 索引类型和 $vectorSearch 管道阶段。要了解详情，请参阅执行向量搜索。
定义
knnBetaknnBeta操作符使用分层可导航小世界算法来执行语义搜索。您可以使用 Atlas Search 对 kNN 查询的支持来搜索与所选产品相似的产品、搜索图片等。
语法
knnBeta 通过以下语法实现：
1 { 2 $search: { 3 "index": "<index name>", // optional, defaults to "default" 4 "knnBeta": { 5 "vector": [<array-of-numbers>], 6 "path": "<field-to-search>", 7 "filter": {<filter-specification>}, 8 "k": <number>, 9 "score": {<options>} 10 } 11 } 12 }
选项
行为
只能对索引为 Atlas Search 类型 knnVector 的字段运行 kNN 查询。
您可以在 阶段之后使用$limit $search来限制knnBeta 查询结果中的文档数量。我们建议将 的值设置为高于k $limit的值。这种过度请求模式是在近似最近邻搜索中平衡延迟和召回的主要方法。根据经验，我们发现5 -10 的乘数对于许多使用案例效果良好，但我们建议根据特定数据集进行调整。
例子
以下查询查找与该查询最近的 150 个邻居，并将剩余结果数限制为 50。
1 db.<collection>.aggregate({ 2 "$search": { 3 "knnBeta": { 4 "vector": <array-of-numbers-to-search>, 5 "path": <indexed-field-to-search>, 6 "k": 150 7 } 8 } 9 }, 10 { 11 "$limit": 50 12 })
性能
要提高查询性能，请使用$project阶段选择要在结果中返回的字段，除非您需要结果中的所有字段。我们建议在$project阶段排除向量字段。
评分
您可以在score searchScore阶段将$project 字段与 $meta 表达式 结合使用，以返回结果中文档的分数。
Atlas Search 仅在从 0 到 1 的固定范围内对 kNN 查询结果进行评分。对于 cosine 和 dotProduct 的相似度，Atlas Search 使用以下算法对分数进行归一化：
score = (1 + cosine/dot_product(v1,v2)) / 2
限制
knnBeta 操作符必须是查询中的顶级操作符，因此，不能在以下情况使用 knnBeta 操作符：
embeddedDocument 操作符
compound 运算符
分面收集器
不能使用 knnBeta 操作符查询使用 vectorSearch 类型索引的字段。不能将 $search 排序选项与 knnBeta 操作符结合使用。
举例
以下查询使用 knnBeta 操作符搜索样本 sample_mflix.embedded_movies 集合。查询搜索 plot_embedding 字段，其中包含使用 OpenAI 的 text-embedding-ada-002 嵌入模型创建的嵌入。如果已将样本集合添加到 Atlas 集群，并为该集合创建了样本索引定义，则可以切换到 sample_mflix 数据库并对该集合运行以下查询。
以下查询使用knnBeta操作符在plot_embedding字段中搜索vector维度，并请求结果中的最多5个最近邻。该查询还指定了$project阶段以：
在结果中排除
_id字段并且包含plot和title字段。在结果中添加名为
score的字段。
1 db.embedded_movies.aggregate([ 2 { 3 "$search": { 4 "index": "default", 5 "knnBeta": { 6 "vector": 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7 "path": "plot_embedding", 8 "k": 5 9 } 10 } 11 }, 12 { 13 "$project": { 14 "_id": 0, 15 "plot": 1, 16 "title": 1, 17 "score": { $meta: "searchScore" } 18 } 19 } 20 ])
1 [ 2 { 3 plot: 'When two girls move to the country to be near their ailing mother, they have adventures with the wonderous forest spirits who live nearby.', 4 title: 'My Neighbor Totoro', 5 score: 0.9999986886978149 6 }, 7 { 8 plot: "To escape a war, a girl flees to a remote farmhouse and becomes part of an expansive family's unusual, perhaps even supernatural lifestyle.", 9 title: 'Black Moon', 10 score: 0.8282386660575867 11 }, 12 { 13 plot: 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.', 14 title: 'Forest Warrior', 15 score: 0.8196926712989807 16 }, 17 { 18 plot: 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.', 19 title: 'Forest Warrior', 20 score: 0.8196901082992554 21 }, 22 { 23 plot: 'An adventurous girl finds another world that is a strangely idealized version of her frustrating home, but it has sinister secrets.', 24 title: 'Coraline', 25 score: 0.815956711769104 26 } 27 ]
以下查询筛选文档以查找在 6 月1971 ( 1971-06-30 ) ( ≤ ) 30之前或之前上映的电影，然后在筛选后的文档中的plot_embedding字段中搜索vector维度，并请求结果中最多5个最近邻。该查询还指定了$project阶段以：
结果中排除
_id字段，仅包含plot、title和released字段。在结果中添加名为
score的字段。
1 db.embedded_movies.aggregate([ 2 { 3 "$search": { 4 "index": "default", 5 "knnBeta": { 6 "vector": 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7 "path": "plot_embedding", 8 "filter": { 9 "range": { 10 "lte": ISODate("1971-06-30 00:27:59.177000000"), 11 "path": "released" 12 } 13 }, 14 "k": 5 15 } 16 } 17 }, 18 { 19 "$project": { 20 "_id": 0, 21 "title": 1, 22 "plot": 1, 23 "released": 1, 24 "score": { $meta: "searchScore" } 25 } 26 } 27 ])
1 [ 2 { 3 plot: 'A poor boy wins the opportunity to tour the most eccentric and wonderful candy factory of all.', 4 title: 'Willy Wonka & the Chocolate Factory', 5 released: ISODate("1971-06-30T00:00:00.000Z"), 6 score: 0.9999985694885254 7 }, 8 { 9 plot: 'A down-on-his-luck inventor turns a broken-down Grand Prix car into a fancy vehicle for his children, and then they go off on a magical fantasy adventure to save their grandfather in a far-off land.', 10 title: 'Chitty Chitty Bang Bang', 11 released: ISODate("1968-12-18T00:00:00.000Z"), 12 score: 0.7576897740364075 13 }, 14 { 15 plot: 'A red balloon with a life of its own follows a little boy around the streets of Paris.', 16 title: 'The Red Balloon', 17 released: ISODate("1957-03-11T00:00:00.000Z"), 18 score: 0.7515948414802551 19 }, 20 { 21 plot: 'While hearing the story of "Gulliver's Travels", a young boy dreams he is the title character on the island of Lilliput .', 22 title: 'The New Gulliver', 23 released: ISODate("1935-11-03T00:00:00.000Z"), 24 score: 0.7495509386062622 25 }, 26 { 27 plot: 'A living puppet, with the help of a cricket as his conscience, must prove himself worthy to become a real boy.', 28 title: 'Pinocchio', 29 released: ISODate("1940-02-23T00:00:00.000Z"), 30 score: 0.7472590804100037 31 } 32 ]
Atlas Search 根据小于或等于1971-06-30的released字段值筛选文档。它对标题为Willy Wonka & the Chocolate Factory的文档得分较高，因为它与filter选项中的搜索条件以及查询中的vector维度匹配。