MongoDB Search and MongoDB Vector Search Indexes

Overview

In this guide, you can learn how to create and manage MongoDB Search and MongoDB Vector Search indexes. These indexes allow you to use the following features:

• MongoDB Search: Perform fast, full-text searches

• MongoDB Vector Search: Perform semantic (similarity) searches on vector embeddings

MongoDB Search and MongoDB Vector Search indexes specify which fields to index, specify how these fields are indexed, and set other optional configurations.

This guide explains how to perform the following actions to manage your MongoDB Search and MongoDB Vector Search indexes:

• 検索インデックスモデルの作成

• 検索インデックスを作成

• 複数の検索インデックスの作成

• 検索インデックスをリストする

• 検索インデックスをアップデートする

• 検索インデックスを削除する

検索インデックスモデルの作成

To create a MongoDB Search or MongoDB Vector Search index, you must first build a CreateSearchIndexModel instance that sets your index specifications.

CreateSearchIndexModel には次のプロパティがあります。

To learn more about MongoDB Search field mappings, see Define Field Mappings in the Atlas documentation.

To learn more about defining MongoDB Vector Search indexes, see How to Index Fields for Vector Search in the Atlas documentation.

var def = new BsonDocument {
  { "mappings", new BsonDocument {
      { "dynamic", false },
      { "fields", new BsonDocument {
        { "title", new BsonDocument { {"type", "string" } } },
        { "released", new BsonDocument { { "type", "date" } } } } }
  } }
};
var indexModel = new CreateSearchIndexModel(
  "search_idx",
  SearchIndexType.Search,
  def
);

var def = new BsonDocument
{
    { "fields", new BsonArray
        {
            new BsonDocument
            {
                { "type", "vector" },
                { "path", "plot_embedding" },
                { "numDimensions", 1536 },
                { "similarity", "euclidean" }
            }
        }
    }
};
var indexModel = new CreateSearchIndexModel(
  "vs_idx",
  SearchIndexType.VectorSearch,
  def
);

検索インデックスを作成

You can create a MongoDB Search or MongoDB Vector Search index on a collection by calling the SearchIndexes.CreateOne() method on an IMongoCollection instance. This method accepts an index model as a parameter, specified in a CreateSearchIndexModel instance.

var indexModel = new CreateSearchIndexModel(
  "example_index",
  SearchIndexType.Search,
  new BsonDocument {
    { "mappings", new BsonDocument {
      { "dynamic", true },
    } }
  }
);
var result = movieCollection.SearchIndexes.CreateOne(indexModel);
Console.WriteLine("Created MongoDB Search index:\n{0}", result);

Created MongoDB Search index:
"example_index"

複数の検索インデックスの作成

You can create multiple MongoDB Search and MongoDB Vector Search indexes by calling the SearchIndexes.CreateMany() method on an IMongoCollection instance. This method accepts an IEnumerable of CreateSearchIndexModel instances as a parameter.

var searchModel = new CreateSearchIndexModel(
  "as_idx",
  SearchIndexType.Search,
  new BsonDocument {
    { "mappings", new BsonDocument {
      { "dynamic", true },
    } }
  }
);
var vectorModel = new CreateSearchIndexModel(
  "vs_idx",
  SearchIndexType.VectorSearch,
  new BsonDocument
  {
      { "fields", new BsonArray
          {
              new BsonDocument
              {
                  { "type", "vector" },
                  { "path", "plot_embedding" },
                  { "numDimensions", 1536 },
                  { "similarity", "euclidean" }
              }
          }
      }
  }
);
var models = new List<CreateSearchIndexModel> { searchModel, vectorModel };
var indexes = movieCollection.SearchIndexes.CreateMany(models);
Console.WriteLine("Created Search indexes:\n{0} {1}", indexes.ToArray());

Created Search indexes:
as_idx vs_idx

検索インデックスをリストする

You can access information about a collection's existing MongoDB Search and MongoDB Vector Search indexes by calling the SearchIndexes.List() method on the collection.

var indexesList = movieCollection.SearchIndexes.List().ToList();
foreach (var i in indexesList)
{
  Console.WriteLine(i);
}

{ "id": "...", "name": "as_idx", "status": "READY", "queryable":
true, "latestDefinitionVersion": {...}, "latestDefinition": {
"mappings": { "dynamic": true } }, "statusDetail": [...] }
{ "id": "...", "name": "vs_idx", "type": "vectorSearch", "status":
"READY", "queryable": true, ..., "latestDefinition": { "fields": [{
"type": "vector", "path": "plot_embedding", "numDimensions": 1536,
"similarity": "euclidean" }] }, "statusDetail": [...] }

検索インデックスをアップデートする

You can update a MongoDB Search or MongoDB Vector Search index by calling the SearchIndexes.Update() method on an IMongoCollection instance. This method accepts the following parameters:

• 更新するインデックスの名前

• 変更されたインデックス定義ドキュメント

var updatedDef = new BsonDocument
{
    { "fields", new BsonArray
        {
            new BsonDocument
            {
                { "type", "vector" },
                { "path", "plot_embedding" },
                { "numDimensions", 1536 },
                { "similarity", "dotProduct" }
            }
        }
    }
};
movieCollection.SearchIndexes.Update("vs_index", updatedDef);

検索インデックスを削除する

You can delete a MongoDB Search or MongoDB Vector Search index by calling the SearchIndexes.DropOne() method on an IMongoCollection instance. This method accepts the name of the index to delete as a parameter.

movieCollection.SearchIndexes.DropOne("example_index");

詳細情報

.NET/ C#ドライバーを使用して作成できるその他のインデックスの詳細については、インデックスの作成と管理ガイドを参照してください。

To learn more about MongoDB Search, see the following Atlas documentation:

• MongoDB Search Best Practices

• Tune MongoDB Search Performance

• MongoDB Search M0, M2, and M5 Limitations

• FAQ: MongoDB Search

To learn more about MongoDB Vector Search, see the following Atlas documentation:

• ベクトル検索のパフォーマンス向上

• MongoDB ベクトル検索クイック スタート

• クエリ結果の精度を測定する方法