ビルダを用いた操作
項目一覧
Overview
このガイドでは、操作で使用する型を作成するために .NET/C# ドライバーが提供するヘルパー クラス、つまり ビルダ について学習できます。ビルダを使用すると、コンパイル時にエラーを識別し、実行時にエラーを回避することができます。このガイドでは、次のタスクに使用できるビルダ クラスに関する情報を提供します。
フィルター定義の作成
プロジェクションの作成
ソート順序の定義
アップデート操作の定義
インデックス キーの選択
Tip
MongoDB C# Analyzer
C# Analzyer は、ビルダーの定義を分析し、.NET/C# コードが MongoDB クエリ API にどのように変換されるかを理解するのに役立つツールです。詳細とインストール手順については、 C# Analzyer リファレンス ページを参照してください。
ビルダを使用して定義を構築し、構文をビルドする方法について詳しはは、こちらのガイドをお読みください。
サンプル クラス
このガイドのコード例は、ビルダを使用してサンプルコレクション plants.flowers内のドキュメントを操作するための型を作成する方法を示しています。このコレクション内のドキュメントは、以下の Flower クラスによってモデル化されます。
public class Flower { public ObjectId Id { get; set; } public string Name { get; set; } public string Category { get; set; } public double Price { get; set; } public List<string> Season { get; set; } public double Stock { get; set; } public string Description { get; set; } }
各ビルダ クラスには、操作するドキュメントのタイプを表すジェネリック型パラメーター TDocument があります。このガイドでは、 Flower クラスは各ビルダ クラスの例で使用されるドキュメント タイプです。
フィルターを構築する
FilterDefinitionBuilder クラスは、クエリをビルドするための型セーフなインターフェースを提供します。次の条件に一致するドキュメントをコレクション内で照会するとします。
Priceフィールド値は 20 未満Categoryフィールド値は「Perennial」
ビルダを使用して、型指定されたバリアントを持つフィルター定義を作成します。
var builder = Builders<Flower>.Filter; var filter = builder.Lt(f => f.Price, 20) & builder.Eq(f => f.Category, "Perennial");
型指定されたバリアント形式を使用すると、コンパイル時の安全性が確保されます。さらに、IDE はリファクタリングのサポートを提供できます。
あるいは、文字列ベースのフィールド名を使用してフィルターを構築することもできます。
var builder = Builders<Flower>.Filter; var filter = builder.Lt("Price", 20) & builder.Eq("Category", "Perennial");
配列演算子
ドキュメントに配列にシリアル化されるプロパティまたはフィールドがある場合は、AnyEq() や AnyLt() など、Any で始まるメソッドを使用して、配列全体を単一のアイテムと比較できます。
ビルダを使用して、コレクション内のどのドキュメントに「winter」を含む Season 配列があるかを確認します。
var builder = Builders<Flower>.Filter; var filter = builder.AnyEq(f => f.Season, "winter");
プロジェクションを作成する
ProjectionDefinitionBuilder クラスは、プロジェクションを定義するための型セーフなインターフェースを提供します。Name フィールドと Price フィールドにプロジェクションを作成し、Id フィールドを除外するとします。
ビルダを使用して、型指定されたバリアントを持つプロジェクション定義を作成します。
var builder = Builders<Flower>.Projection; var projection = builder.Include(f => f.Name).Include(f => f.Price).Exclude(f => f.Id);
文字列ベースのフィールド名を使用してプロジェクションを定義することもできます。
var builder = Builders<Flower>.Projection; var projection = builder.Include("Name").Include("Price").Exclude("Id");
最後に、Expression() メソッドを使用してプロジェクションを定義します。
var builder = Builders<Flower>.Projection; var projection = builder.Expression(f => new { Name = f.Name, Price = f.Price });
この定義の戻り値の型は ProjectionDefinition<TDocument,
TProjection> ですが、他の定義は ProjectionDefinition<TDocument> を返します。
Lambda 式
ドライバーは、Lambda を使用してプロジェクションをレンダリングすることをサポートしています。Expression() メソッドで Find() プロジェクションを定義してラムダ式を作成すると、ドライバーは式を調べてどのフィールドが参照されているかを判断し、それらのフィールドのみを返すサーバー側プロジェクションを自動的に構築します。
ラムダ式を使用して、ドキュメント内の値に対して操作を実行し、新しいフィールドを作成することもできます。次の例は、ラムダ式を使用して Price フィールドと Stock フィールドを使用して新しい Profit フィールドをプロジェクションする方法を表したものです。
var builder = Builders<Flower>.Projection; var projection = builder.Expression(f => new { Profit = f.Price * f.Stock });
注意
ID フィールドの除外
ラムダ式を使用してプロジェクションを作成すると、プロジェクション フィールドとして明示的に含めない限り、出力では Id フィールドが自動的に除外されます。
ソートを定義する
SortDefinitionBuilder クラスは、ソート構文を構築するための型セーフなインターフェースを提供します。次の順序でソートを定義するとします。
昇順基準:
Price降順基準:
Category
ビルダを使用して、型指定されたバリアントでソート定義を作成します。
var builder = Builders<Flower>.Sort; var sort = builder.Ascending(f => f.Price).Descending(f => f.Category);
あるいは、文字列ベースのフィールド名を使用してソートを定義することもできます。
var builder = Builders<Flower>.Sort; var sort = builder.Ascending("Price").Descending("Category");
アップデートを定義する
UpdateDefinitionBuilder クラスは、アップデート仕様を構築するための型セーフなインターフェースを提供します。次の基準でアップデート仕様を作成するとします。
新しいフィールドを作成する
SunRequirementPriceフィールド値を 0.9 倍します
ビルダを使用して、型指定されたバリアントを含むアップデート仕様を作成します。
var builder = Builders<Flower>.Update; var update = builder.Set(f => f.SunRequirement, "Full sun").Mul(f => f.Price, 0.9);
あるいは、文字列ベースのフィールド名を使用して更新を定義することもできます。
var builder = Builders<Flower>.Update; var update = builder.Set("SunRequirement", "Full sun").Mul("Price", 0.9);
インデックス キーを定義する
IndexKeysDefinitionBuilder クラスは、インデックス キーを定義するための型セーフなインターフェースを提供します。昇順のインデックス キーとして Category を選択するとします。
ビルダを使用して、型指定されたバリアントを持つインデックス キーを選択します。
var builder = Builders<Flower>.IndexKeys; var keys = builder.Ascending(f => f.Category);
あるいは、文字列ベースのフィールド名を使用してインデックス キーを選択することもできます。
var builder = Builders<BsonDocument>.IndexKeys; var keys = builder.Ascending("Category");
IndexKeysDefinitionBuilder クラスには、ワイルドカード インデックスを構築するメソッドも用意されています。All field paths または A
single field path を使用してワイルドカード インデックスを作成できます（この場合は Category を使用します）。
var builder = Builders<Flower>.IndexKeys; var keys = builder.Wildcard();
var builder = Builders<Flower>.IndexKeys; // Using the typed variant var keys = builder.Wildcard(f => f.Category); // Using string-based field names var keys = builder.Wildcard("Category");
ワイルドカード インデックスの使用方法の詳細については、「ワイルドカード インデックス 」を参照してください。
Aggregation Pipeline をビルドする
PipelineDefinitionBuilder クラスでは、集計パイプラインを定義するためのタイプセーフ インターフェースが提供されます。集計パイプラインは、ドキュメントを変換するために使用される一連のステージです。次の操作を実行するパイプラインを作成するとします。
Seasonフィールドに「spring」が含まれるすべてのドキュメントに一致します結果を
Categoryフィールドでソートしますドキュメントをカテゴリ別にグループ化し、そのカテゴリ内のすべてのドキュメントの平均価格と合計を表示します
パイプラインを構築するには、PipelineDefinitionBuilder クラスを使用します。
var sortBuilder = Builders<Flower>.Sort.Ascending(f => f.Category); var matchFilter = Builders<Flower>.Filter.AnyEq(f => f.Season, "spring"); var pipeline = new EmptyPipelineDefinition<Flower>() .Match(matchFilter) .Sort(sortBuilder) .Group(f => f.Category, g => new { name = g.Key, avgPrice = g.Average(f => f.Price), totalAvailable = g.Sum(f => f.Stock) } );
上記の例では、次のパイプラインが作成されます。
[{ "$match" : { "season" : "spring" } }, { "$sort" : { "category" : 1 } }, { "$group" : { "_id" : "$category", "avgPrice" : { "$avg" : "$price" }, "totalAvailable" : { "$sum" : "$stock" } } }]
クエリを BsonDocument として AppendStage() メソッドに提供することで、PipelineDefinitionBuilder インターフェースに対応するタイプセーフ メソッドがないステージをパイプラインに追加できます。
var pipeline = new EmptyPipelineDefinition<BsonDocument>().AppendStage<BsonDocument, BsonDocument, BsonDocument>("{ $set: { field1: '$field2' } }");
注意
BsonDocument を使用してパイプライン ステージを定義する場合、ドライバーは BsonClassMap、シリアル化属性、またはシリアル化規則を考慮しません。BsonDocument で使用されるフィールド名は、サーバー上に保存されているフィールド名と一致する必要があります。
クエリを BsonDocument として提供する方法の詳細については、 FAQ ページをご覧ください。
Aggregation Pipeline の詳細については、 マニュアルの「Aggregation Pipeline サーバー」ページを参照してください。
パイプライン結果のコレクションへの書き込み
集計パイプラインの最後に$outステージを作成することで、集計パイプラインから返されたドキュメントをコレクションに書き込むことができます。 $outステージを作成するには、 PipelineStageDefinitionBuilderでOut()メソッドを呼び出します。 Out()メソッドには、ドキュメントを書き込むコレクションの名前が必要です。
次の例では、 seasonフィールドの値が"Spring"であるすべてのドキュメントに一致する集計パイプラインを構築し、それらをspringFlowersコレクションに出力します。
var outputCollection = database.GetCollection("springFlowers"); var matchFilter = Builders<Flower>.Filter.AnyEq(f => f.Season, "spring"); // Creates an aggregation pipeline and outputs resulting documents to a new collection. var pipeline = new EmptyPipelineDefinition<Flower>() .Match(matchFilter) .Out(outputCollection);
TimeSeriesOptionオブジェクトを指定し、それを 2 番目のパラメータとしてOut()メソッドに渡すことで、集計パイプラインの結果を時系列コレクションに書き込むことができます。
plants.flowersコレクション内のドキュメントには、BSON 日付値を保持するdatePlantedフィールドが含まれているとします。 このコレクション内のドキュメントを時系列コレクションに保存するには、 datePlantedフィールドを時間フィールドとして使用します。
次の例では、 TimeSeriesOptionsオブジェクトを作成し、 timeFieldとしてdatePlantedを指定しています。 次に、 seasonフィールド値が"Spring"であるすべてのドキュメントに一致する集計パイプラインを構築し、それらをspringFlowerTimesという時系列コレクションに出力します。
var timeSeriesOptions = new TimeSeriesOptions("datePlanted"); var collectionName = "springFlowerTimes" var matchFilter = Builders<Flower>.Filter.AnyEq(f => f.Season, "spring"); // Creates an aggregation pipeline and outputs resulting documents to a time series collection. var pipeline = new EmptyPipelineDefinition<Flower>() .Match(matchFilter) .Out(collectionName, timeSeriesOptions);
時系列コレクションの詳細については、「時系列コレクション 」を参照してください。
Atlas 検索クエリをビルドする
Search クラスは、$search パイプライン ステージを作成するための型セーフなインターフェースを提供します。
Searchクラスを使用して検索クエリを構築する方法については、「Atlas Search」を参照してください。
Atlas Vector Search を実行する
ビルダーを使用して $vectorSearch 集計パイプライン ステージを作成し、指定されたフィールド内のベクトルに対して近似最近傍探索を実行できます。データに対してベクトル検索を実行する前に、コレクションに定義された Atlas Vector Search インデックスが必要です。
Tip
次の例で使用されるサンプル データセットを取得するには、「クイック スタート」を参照してください。 次の例で使用されるサンプル Atlas Vector Search インデックスを作成するには、Atlas マニュアルの「Atlas Vector Search インデックスの作成」を参照してください。
sample_mflix データベースの embedded_movies コレクションを検討します。$vectorSearch ステージを使用して、コレクション内のドキュメントの plot_embedding フィールドでセマンティック検索を実行できます。
以下の例では、ビルダーを使って集計パイプラインを生成し、以下の操作を実行する方法について説明しています。
文字列
"time travel"のベクトル埋め込みを使用して、plot_embeddingフィールドの Atlas Vector Search インデックスでベクトル検索を実行する方法ベクトル検索で見つかったドキュメントから
TitleフィールドとPlotフィールドを取得します
// Defines vector embeddings for the string "time travel" var vector = new[] 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// Specifies that the vector search will consider the 150 nearest neighbors // in the specified index var options = new VectorSearchOptions<EmbeddedMovie>() { IndexName = "vector_index", NumberOfCandidates = 150 }; // Builds aggregation pipeline and specifies that the $vectorSearch stage // returns 10 results var pipeline = new EmptyPipelineDefinition<EmbeddedMovie>() .VectorSearch(m => m.Embedding, vector, 10, options) .Project(Builders<EmbeddedMovie>.Projection .Include(m => m.Title) .Include(m => m.Plot));
前の例の結果には、次のドキュメントが含まれています。
{ "_id" : ObjectId("573a13a0f29313caabd04a4f"), "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" } { "_id" : ObjectId("573a13d8f29313caabda6557"), "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" } { "_id" : ObjectId("573a13a5f29313caabd13b4b"), "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" } { "_id" : ObjectId("573a13aef29313caabd2e2d7"), "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" } { "_id" : ObjectId("573a1399f29313caabceec0e"), "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" } { "_id" : ObjectId("573a1399f29313caabcee36f"), "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." } { "_id" : ObjectId("573a13c6f29313caabd715d3"), "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" } { "_id" : ObjectId("573a13d4f29313caabd98c13"), "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" } { "_id" : ObjectId("573a13b6f29313caabd477fa"), "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" } { "_id" : ObjectId("573a13e5f29313caabdc40c9"), "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" }
Atlas Vector Search の詳細については、Atlas マニュアルの「Atlas Vector Search の概要」を参照してください。
詳細情報
さまざまな操作でビルダを使用して実行可能な例については、「使用例」を参照してください。
API ドキュメント
このガイドで説明したメソッドや型の詳細については、次の API ドキュメントを参照してください。