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Operações com construtores

Nesta página

  • Visão geral
  • Classe de amostra
  • Construir um filtro
  • Operadores de array
  • Criar uma projeção
  • Expressões de Lambda
  • Definir uma classificação
  • Definir uma atualização
  • Definir chaves de índice
  • Criar um pipeline de agregação
  • Gravar resultados do pipeline em uma coleção
  • Construir uma Consulta de Pesquisa Atlas
  • Execute uma pesquisa do Atlas Vector
  • Informações adicionais
  • Documentação da API

Visão geral

Neste guia, você pode aprender sobre as classes auxiliares, ou construtores, que o .NET/C# Driver fornece para criar tipos usados em suas operações. A utilização de construtores ajuda você a identificar erros no tempo de compilação e evitá-los no tempo de execução. Este guia fornece informações sobre classes de construtores que você pode usar para as seguintes tarefas:

  • Criar uma definição de filtro

  • Criar uma projeção

  • Definir uma ordem de classificação

  • Definir uma operação de atualização

  • Selecionar chaves de índice

Dica

Analisador do MongoDB C#

O C# Analzyer é uma ferramenta que ajuda você a analisar as definições de seus construtores e entender como seu código .NET/C# é convertido na API de query do MongoDB. Para mais informações e instruções de instalação, consulte a página de referência do C# Analzyer.

Leia este guia se quiser saber mais sobre como construir definições e sintaxe usando construtores.

Classe de amostra

Os exemplos de código neste guia demonstram como você pode usar os construtores para criar tipos para interagir com documentos na coleção de amostra plants.flowers. Os documentos nesta coleção são modelados pela seguinte classe Flower:

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; }
}

Cada classe de construtor usa um parâmetro de tipo genérico TDocument, que representa o tipo de documento com o qual você está trabalhando. Neste guia, a classe Flower é o tipo de documento utilizado em cada exemplo de classe de construtor.

Construir um filtro

A classe FilterDefinitionBuilder fornece uma interface de tipo seguro para criar query. Suponha que você queira fazer query em sua coleção para documentos que correspondam aos seguintes critérios:

  • Price valor do campo inferior a 20

  • Category o valor do campo é "Perennial"

Use construtores para criar a definição de filtro com a variante digitada:

var builder = Builders<Flower>.Filter;
var filter = builder.Lt(f => f.Price, 20) & builder.Eq(f => f.Category, "Perennial");

Usar o formulário variante digitado fornece segurança em tempo de compilação. Além disso, seu IDE pode fornecer suporte à refatoração.

Opcionalmente, você pode usar nomes de campo baseados em cadeias de caracteres para criar o filtro:

var builder = Builders<Flower>.Filter;
var filter = builder.Lt("Price", 20) & builder.Eq("Category", "Perennial");

Operadores de array

Se o seu documento tiver propriedades ou campos que serializam para arrays, você poderá utilizar os métodos começando com Any, como AnyEq() ou AnyLt(), para comparar a array inteira com um único item.

Use construtores para verificar quais documentos na collection têm uma array Season que inclui "winter":

var builder = Builders<Flower>.Filter;
var filter = builder.AnyEq(f => f.Season, "winter");

Você também pode chamar o método ElemMatch() para localizar documentos que tenham um campo de array que contenha pelo menos um elemento que corresponda a um critério de pesquisa especificado. O exemplo a seguir retorna documentos que contêm o valor "Summer" em sua array Season:

var builder = Builders<Flower>.Filter;
var filter = builder.ElemMatch(f => f.Season, s => s == "Summer");

Para saber mais sobre operadores de array, consulte o guia Operadores de query de array no manual do MongoDB Server .

Criar uma projeção

A classe ProjectionDefinitionBuilder oferece uma interface segura por tipo para definir uma projeção. Suponha que você queira criar uma projeção nos campos Name e Price, mas excluir o campo Id.

Use construtores para criar a definição de projeção com a variante digitada:

var builder = Builders<Flower>.Projection;
var projection = builder.Include(f => f.Name).Include(f => f.Price).Exclude(f => f.Id);

Você também pode usar nomes de campos baseados em string para definir a projeção:

var builder = Builders<Flower>.Projection;
var projection = builder.Include("Name").Include("Price").Exclude("Id");

Finalmente, você pode utilizar o método Expression() para definir a projeção:

var builder = Builders<Flower>.Projection;
var projection = builder.Expression(f => new { Name = f.Name, Price = f.Price });

Esta definição tem um tipo de retorno de ProjectionDefinition<TDocument, TProjection> enquanto os outros retornam um ProjectionDefinition<TDocument>.

Expressões de Lambda

O driver é compatível com o uso de expressões lambda para renderizar projeções. Quando você define uma projeção Find() com o método Expression() para criar uma expressão lambda, o driver inspeciona a expressão para determinar quais campos são referenciados e constrói automaticamente uma projeção no lado do servidor para retornar somente esses campos.

Você também pode utilizar expressões lambda para criar novos campos executando operações em valores em seus documentos. O exemplo seguinte mostra como você pode utilizar uma expressão lambda para projetar um novo campo Profit utilizando os campos Price e Stock:

var builder = Builders<Flower>.Projection;
var projection = builder.Expression(f => new { Profit = f.Price * f.Stock });

Observação

Exclusão de campo de ID

Quando você cria uma projeção utilizando uma expressão lambda, a saída exclui automaticamente o campo Id a menos que você inclua explicitamente é como um campo de projeção.

Definir uma classificação

A classe SortDefinitionBuilder fornece uma interface segura por tipo para construir sintaxe de classificação. Suponha que você deseja definir uma classificação com a seguinte ordem:

  • Subindo Price

  • Descendo Category

Use construtores para criar a definição de classificação com a variante digitada:

var builder = Builders<Flower>.Sort;
var sort = builder.Ascending(f => f.Price).Descending(f => f.Category);

Como alternativa, você pode usar nomes de campo baseados em strings para definir a classificação:

var builder = Builders<Flower>.Sort;
var sort = builder.Ascending("Price").Descending("Category");

Definir uma atualização

A classe UpdateDefinitionBuilder fornece uma interface de tipo seguro para criar uma especificação de atualização. Suponha que você deseja criar uma especificação de atualização com os seguintes critérios:

  • Criar o novo campo SunRequirement

  • Multiplique o valor de campo Price por 0,9

Use construtores para criar a especificação de atualização com a variante digitada:

var builder = Builders<Flower>.Update;
var update = builder.Set(f => f.SunRequirement, "Full sun").Mul(f => f.Price, 0.9);

Alternativamente, você pode usar nomes de campos baseados em string para definir a atualização:

var builder = Builders<Flower>.Update;
var update = builder.Set("SunRequirement", "Full sun").Mul("Price", 0.9);

Definir chaves de índice

A classe IndexKeysDefinitionBuilder oferece uma interface segura por tipo para definir chaves de índice. Suponha que você queira selecionar Category como uma chave de índice ascendente.

Use construtores para selecionar a chave de índice com a variante digitada:

var builder = Builders<Flower>.IndexKeys;
var keys = builder.Ascending(f => f.Category);

Como alternativa, você pode usar nomes de campo baseados em strings para selecionar a chave de índice:

var builder = Builders<BsonDocument>.IndexKeys;
var keys = builder.Ascending("Category");

A classe IndexKeysDefinitionBuilder também fornece métodos para construir um índice curinga. Você pode criar um índice curinga utilizando All field paths ou A single field path, neste caso utilizando Category:

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");

Para obter mais informações sobre como utilizar índices curinga, consulte Índices curinga.

Criar um pipeline de agregação

A classe PipelineDefinitionBuilder fornece uma interface segura para definir um aggregation pipeline. Um pipeline de agregação é uma série de estágios usados para transformar um documento. Suponha que você queira criar um pipeline que execute as seguintes operações:

  • Corresponde a todos os documentos com "spring" no campo Season

  • Classifica os resultados pelo campo Category

  • Agrupa os documentos por categoria e mostra o preço médio e o total disponível para todos os documentos nessa categoria

Use PipelineDefinitionBuilder turmas para criar o pipeline:

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)
               }
          );

O exemplo anterior cria o seguinte pipeline:

[{ "$match" : { "season" : "spring" } }, { "$sort" : { "category" : 1 } }, { "$group" : { "_id" : "$category", "avgPrice" : { "$avg" : "$price" }, "totalAvailable" : { "$sum" : "$stock" } } }]

Você pode adicionar estágios ao pipeline que não tenham métodos seguros de tipo correspondente na PipelineDefinitionBuilder interface fornecendo sua consulta como um BsonDocument para o método AppendStage().

var pipeline = new EmptyPipelineDefinition<BsonDocument>().AppendStage<BsonDocument, BsonDocument, BsonDocument>("{ $set: { field1: '$field2' } }");

Observação

Se utilizar um BsonDocument para definir seu estágio de pipeline, o driver não levará em consideração nenhum BsonClassMap, atributos de serialização nem convenções de serialização. Os nomes de campo utilizados no BsonDocument devem corresponder àqueles armazenados no servidor.

Para obter mais informações sobre como fornecer uma query como BsonDocument, consulte nossa página de perguntas frequentes.

Para saber mais sobre o Pipeline de Agregação, consulte a página de manual do servidor de Pipeline de Agregação .

Gravar resultados do pipeline em uma coleção

Você pode gravar os documentos retornados de um pipeline de agregação em uma coleção criando um estágio $out no final do seu pipeline de agregação. Para criar um estágio $out, chame o método Out() em um PipelineStageDefinitionBuilder. O método Out() requer o nome da coleção na qual você deseja gravar os documentos.

O exemplo a seguir cria um pipeline de agregação que combina todos os documentos com um valor de campo season de "Spring" e os envia para uma coleção springFlowers:

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);

Você pode escrever os resultados de um pipeline de agregação para uma coleção de séries temporais especificando um objeto TimeSeriesOption e passando-o como o segundo parâmetro para o método Out().

Imagine que os documentos na coleção plants.flowers contêm um campo datePlanted que contém valores de data BSON. Você pode armazenar os documentos dessa coleção em uma coleção de séries temporais usando o campo datePlanted como o campo de tempo.

O exemplo a seguir cria um objeto TimeSeriesOptions e especifica datePlanted como timeField. Em seguida, ele cria um pipeline de agregação que combina todos os documentos com um valor de campo season de "Spring" e os envia para uma coleção de séries temporais chamada springFlowerTimes.

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);

Para saber mais sobre coleções de séries temporais, consulte Coleções de séries temporais.

Construir uma Consulta de Pesquisa Atlas

A classe Search fornece uma interface de tipo seguro para criar um estágio de pipeline $search.

Para aprender como construir consultas de pesquisa com a classe Search, consulte Pesquisa Atlas.

Execute uma pesquisa do Atlas Vector

Você pode usar construtores para criar um estágio de pipeline de agregação $vectorSearch para executar uma pesquisa aproximada de vizinho mais próximo em um vetor no campo especificado. Sua coleção deve ter um índice Atlas Vector Search definido para que você possa realizar uma pesquisa vetorial em seus dados.

Dica

Para obter o conjunto de dados de amostra usado no exemplo a seguir, consulte Início rápido. Para criar o índice de amostra do Atlas Vector Search usado no exemplo a seguir, consulte Criar um índice do Atlas Vector Search no manual do Atlas.

Considere a coleção embedded_movies no banco de dados sample_mflix. Você pode usar uma fase $vectorSearch para executar uma pesquisa semântica no campo plot_embedding dos documentos na coleção.

O exemplo a seguir mostra como usar construtores para gerar uma pipeline de agregação para executar as seguintes operações:

  • Executa uma pesquisa vetorial no índice de Pesquisa vetorial do Atlas do campo plot_embedding usando incorporações de vetor para a string "time travel"

  • Obtém os campos Title e Plot dos documentos encontrados na pesquisa vetorial

// Defines vector embeddings for the string "time travel"
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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));

Os resultados do exemplo anterior contêm os seguintes documentos:

{ "_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" }

Para saber mais sobre o Atlas Vector Search, consulte Visão geral do Atlas Vector Search no manual do Atlas.

Informações adicionais

Encontre exemplos executáveis utilizando construtores para várias operações em Exemplos de Uso.

Documentação da API

Para saber mais sobre qualquer um dos métodos ou tipos discutidos neste guia, consulte a seguinte documentação da API:

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