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Atlas Vector Search

使用 MongoDB 视图转换文档并过滤 Atlas Vector Search 的集合

在此页面上

您可以在 视图上创建 Atlas Vector Search 索引，以转换文档和集合，从而可以部分索引集合、支持不兼容的数据类型或数据模型等。

注意

将 MongoDB 视图与 Atlas Vector Search 结合使用是作为预览功能提供的。“预览”期间，功能和相应的文档可能随时更改。

以下示例使用 sample_mflix 示例数据库。

注意

消歧

本页讨论标准视图。要了解按需物化视图，请参阅按需物化视图。

要了解视图类型之间的差异，请参阅与按需物化视图的比较。

要求

您必须使用：

  • MongoDB 8.0 或更高版本。

在预览期间，您必须使用：

  • mongosh 或 Compass 来创建和管理 MongoDB 视图。

  • 使用 Atlas UI 和 Atlas Administration API 在视图上创建 Atlas Vector Search 索引。当该功能普遍可用时，将提供对mongosh、Compass和Drivers的支持。

要编辑视图，您必须拥有用户管理员角色，并使用 collMod 数据库命令。

限制

  • Atlas Vector Search 仅支持在以下阶段 $expr 的视图：

  • 索引名称在源集合及其所有视图中必须是唯一的。

  • Atlas Vector Search 不支持包含生成动态结果的变量（如 $$USER_ROLES 和 $random）的视图定义。

  • Atlas Vector Search 查询返回源集合中显示的原始文档。

示例：过滤文档

要创建视图，您必须拥有 createCollection 权限。

您可以使用过滤器筛选文档以对集合进行部分索引。以下示例在 sample_mflix.embedded_movies 集合上创建一个视图，以便仅对具有向量嵌入字段的文档进行索引。

1

使用 mongosh 连接到 Atlas 集群。

要了解更多信息，请参阅通过 mongosh 进行连接。

2

切换到 sample_mflix 数据库。

use sample_mflix
3

创建一个 moviesWithEmbeddings 视图。

db.createView(
  "moviesWithEmbeddings",
  "embedded_movies",
  [
    {
      "$match": {
        "$expr": {
          "$ne": [
            {
              "$type": "$plot_embedding"
            },
            "missing"
          ]
        }
      }
    }
  ]
)
4

AtlasGoClusters在Atlas中，Go项目的 页面。

  1. 如果尚未显示，请从导航栏上的 Organizations 菜单中选择包含所需项目的组织。

  2. 如果尚未显示，请从导航栏的Projects菜单中选择所需的项目。

  3. 如果尚未出现，请单击侧边栏中的 Clusters（集群）。

    会显示集群页面。

5

转到集群的 Atlas Search 页面。

您可以从侧边栏、 Data Explorer 或集群详细信息页面转到 Atlas Search 页面。

  1. 在侧边栏中，单击 Services 标题下的 Atlas Search。

    注意

    如果没有集群，则请单击 Create cluster 来创建一个。要了解更多信息，请参阅创建集群。

  2. 从 Select data source 下拉菜单中选择您的集群并单击 Go to Atlas Search。

    将显示 Atlas Search 页面。

  1. 单击集群的对应 Browse Collections 按钮。

  2. 展开数据库并选择集合。

  3. 单击该集合的 Search Indexes 标签页。

    将显示 Atlas Search 页面。

  1. 单击集群的名称。

  2. 单击 Atlas Search 标签页。

    将显示 Atlas Search 页面。

6

单击 Create Search Index（保存并关闭）。

7

单击 Create Search Index（保存并关闭）。

8

开始您的索引配置。

在页面上进行以下选择，然后单击 Next。

Search Type

选择 Atlas Vector Search 索引类型。

Index Name and Data Source

指定以下信息：

  • Index Name: embeddingsIndex

  • Database and Collection:

    • sample_mflix

    • moviesWithEmbeddings

Configuration Method

For a guided experience, select Visual Editor.

To edit the raw index definition, select JSON Editor.
9

指定索引定义。

  1. 请指定以下索引定义：

    {
      "fields": [
        {
          "type": "vector",
          "numDimensions": 1536,
          "path": "plot_embedding",
          "similarity": "cosine"
        }
      ]
    }

  2. 单击 Next（连接）。

10

单击 Create Vector Search Index（保存并关闭）。

Atlas 会显示一个模态窗口，让您知道您的索引正在构建中。

11

通过单击 Close（关闭）按钮关闭 You're All Set!（一切就绪！）模态窗口。

12

检查状态。

新创建的索引会显示在 Atlas Search 标签页上。在构建索引期间，Status 字段显示为 Build in Progress。索引构建完成后，Status 字段将显示为 Active。

注意

较大的集合需要较长的索引时间。索引构建完成后，您将收到电子邮件通知。

13

在 embeddingsIndex 部分索引上运行查询。

注意

以下示例通过对源集合 embedded_movies 运行 .aggregate 命令来查询 embeddingsIndex 索引。在预览期间，您必须使用 View 的源集合 (embedded_movies) 查询在 View 上创建的搜索索引。如果您查询视图 (moviesWithEmbeddings)，Atlas 矢量搜索将不返回任何结果。

use sample_mflix
1db.embedded_movies.aggregate([
2  {
3    "$vectorSearch": {
4      "index": "embeddingsIndex",
5      "path": "plot_embedding",
6      "queryVector": 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[
  {
    "plot" : "A reporter, learning of time travelers visiting 20th century disasters, tries to change the history they know by averting upcoming disasters.",
    "title" : "Thrill Seekers"
  },
  {
    "plot" : "At the age of 21, Tim discovers he can travel in time and change what happens and has happened in his own life. His decision to make his world a better place by getting a girlfriend turns out not to be as easy as you might think.",
    "title" : "About Time"
  },
  {
    "plot" : "Hoping to alter the events of the past, a 19th century inventor instead travels 800,000 years into the future, where he finds humankind divided into two warring races.",
    "title" : "The Time Machine"
  },
  {
    "plot" : "After using his mother's newly built time machine, Dolf gets stuck involuntary in the year 1212. He ends up in a children's crusade where he confronts his new friends with modern techniques...",
    "title" : "Crusade in Jeans"
  },
  {
    "plot" : "An officer for a security agency that regulates time travel, must fend for his life against a shady politician who has a tie to his past.",
    "title" : "Timecop"
  },
  {
    "plot" : "A time-travel experiment in which a robot probe is sent from the year 2073 to the year 1973 goes terribly wrong thrusting one of the project scientists, a man named Nicholas Sinclair into a...",
    "title" : "A.P.E.X."
  },
  {
    "plot" : "Agent J travels in time to M.I.B.'s early days in 1969 to stop an alien from assassinating his friend Agent K and changing history.",
    "title" : "Men in Black 3"
  },
  {
    "plot" : "Bound by a shared destiny, a teen bursting with scientific curiosity and a former boy-genius inventor embark on a mission to unearth the secrets of a place somewhere in time and space that exists in their collective memory.",
    "title" : "Tomorrowland"
  },
  {
    "plot" : "With the help of his uncle, a man travels to the future to try and bring his girlfriend back to life.",
    "title" : "Love Story 2050"
  },
  {
    "plot" : "A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...",
    "title" : "The Portal"
  }
]

故障排除

在以下场景中，索引会更改为 FAILED 状态：

  • 您在与 Atlas Vector Search 不兼容的视图上创建索引。

  • 您编辑视图的方式不符合 Atlas Vector Search 兼容性要求。

  • 您删除或更改视图的源集合。

    例如，如果一个视图是在另一个视图上创建的，并且将父视图源更改为另一个集合。

    注意

    如果一个视图是其他视图的后代，这一限制也同样适用。例如，您无法更改或移除所有后代所源自的源集合。

索引在以下情况下会停滞：

警告

如果在视图中定义的聚合管道与集合中的文档不兼容，搜索复制将失败。例如，如果 $toDouble 表达式对包含数组的文档字段进行操作，复制将失败。确保您的视图在处理集合中的所有文档时不会出错。

  • 如果视图定义在索引为 READY 时导致聚合失败，则索引将变为 STALE。在您解析文档或更改视图定义后，索引将返回到 READY，以确保不再失败。不过，在复制自动从 oplog. 删除之前，索引是可以查询的。

  • 如果视图定义在索引为 BUILDING 时导致聚合管道失败，则在修复文档之前，则索引生成将停滞。在您解析文档或更改视图定义后，索引将返回到 READY，以确保不再失败。

您可以在 Atlas 用户界面的索引状态详情页面查看索引状态。

索引流程

当您在视图上创建 Atlas Vector Search 索引时，mongot 进程执行的任务与在常规集合上创建 Atlas Vector Search 索引时相同。mongot 进程：

  1. 根据该集合的索引定义中的规则来创建 Atlas Vector Search 索引。

  2. 监控文档当前状态的变更流，以及已定义 Atlas Vector Search 索引的集合索引。

  3. 处理 Atlas Vector Search 查询，并将匹配文档的文档 ID 和其他搜索元数据返回给 mongod，然后执行完整的文档查找并将结果返回给客户端。

当您在视图上创建 Atlas Vector Search 索引时，视图定义将在步骤 1 和 2 期间应用，转换后的文档将存储在磁盘上的 Atlas Vector Search 索引中。

了解详情

要了解有关视图的更多信息，请参阅视图。

要在视图上创建 Atlas Vector Search 索引，请参阅使用 MongoDB 视图为 Atlas Vector Search 转换文档和过滤集合。

后退

解释查询结果

来年

矢量量化