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Fundamentals

Operaciones con Constructores

Overview

En esta guía, puedes aprender sobre las clases asistentes, o desarrolladores, que el driver .NET/C# provee para crear tipos usados en tus operaciones. Utilizar desarrolladores ayuda a identificar errores en tiempo de compilación y evitarlos en tiempo de ejecución. Esta guía proporciona información sobre las clases de generador que se pueden usar para las siguientes tareas:

  • Creación de una definición de filtro

  • Creando una proyección

  • Definir un orden de clasificación

  • Definir una operación de actualización

  • Seleccionar claves de índice

Tip

Analizador MongoDB C#

El C# Analyzer es una herramienta que te ayuda a analizar las definiciones de tus constructores y comprender cómo tu código .NET/C# se traduce a la API de Consultas de MongoDB. Para más información e instrucciones de instalación, consulte el Página de referencia del analizador de C#.

Debería leer esta guía si desea aprender más sobre cómo construir definiciones y desarrollar la sintaxis utilizando desarrolladores.

Muestra clase

Los ejemplos de código de esta guía demuestran cómo se pueden usar constructores para crear tipos para interactuar con documentos en la colección de muestra. plants.flowers. Los documentos de esta colección están modelados por la siguiente clase 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 clase de constructor toma un parámetro de tipo genérico TDocument que representa el tipo de documento con el que se trabaja. En esta guía, la clase Flower es el tipo de documento utilizado en cada ejemplo de clase de constructor.

Construir un filtro

La clase FilterDefinitionBuilder proporciona una interfaz segura en cuanto a tipos para desarrollar consultas. Suponga que quiere query su colección de documentos que cumplan los siguientes criterios:

  • Price valor del campo menor que 20

  • Category el valor del campo es "Perennial"

Utilice constructores para crear la definición de filtro con la variante tipificada:

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

Utilizar la forma variante tipada proporciona seguridad en tiempo de compilación. Además, tu IDE puede proporcionar soporte para la refactorización.

Alternativamente, puede usar nombres de campo basados en cadenas para construir el filtro:

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

Si estás usando LINQ, también puedes utilizar el método Inject() para aplicar el filtro a una query LINQ:

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

Operadores de arreglos

Si tu documento tiene propiedades o campos que se serializan a arreglos, puedes usar los métodos que comienzan con Any, como AnyEq() o AnyLt(), para comparar todo el arreglo con un solo elemento.

Utiliza desarrolladores para comprobar qué documentos de la colección tienen un arreglo Season que incluye "invierno":

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

Crear una Proyección

La clase ProjectionDefinitionBuilder proporciona una interfaz segura en cuanto a tipos para definir una proyección. Supongamos que deseas crear una proyección en los campos Name y Price, pero excluir el campo Id.

Utilice desarrolladores para crear la definición de proyección con la variante tipada:

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

También puedes usar nombres de campos basados en cadenas para definir la proyección:

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

Finalmente, puedes utilizar el método Expression() para definir la proyección:

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

Esta definición tiene un tipo de retorno de ProjectionDefinition<TDocument, TProjection>, mientras que los demás retornan un ProjectionDefinition<TDocument>.

Expresiones Lambda

El controlador admite el uso de expresiones Lambda para renderizar proyecciones. Cuando defines una Find() proyección con el método Expression() para crear una expresión lambda, el driver inspecciona la expresión para determinar qué campos se están haciendo referencia y construye automáticamente una proyección del lado del servidor para devolver solo esos campos.

También puede usar expresiones lambda para crear nuevos campos al realizar operaciones sobre los valores en sus documentos. El siguiente ejemplo muestra cómo se puede usar una expresión lambda para proyectar un nuevo campo Profit usando los campos Price y Stock.

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

Nota

Exclusión de campo ID

Cuando crea una proyección utilizando una expresión lambda, la salida excluye automáticamente el campo Id a menos que lo incluya explícitamente como un campo de proyección.

Definir una clasificación

La clase SortDefinitionBuilder proporciona una interfaz con seguridad de tipos para crear sintaxis de ordenamiento. Supongamos que desea definir un ordenamiento con el siguiente orden:

  • Ascendente en Price

  • Descendiendo en Category

Utilice constructores para crear la definición de ordenamiento con la variante tipificada:

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

Alternativamente, puedes utilizar nombres de campos basados en strings para definir la clasificación:

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

Definir actualizar

La clase UpdateDefinitionBuilder proporciona una interfaz type-safe para crear una especificación de actualización. Supongamos que desea crear una especificación de actualización con los siguientes criterios:

  • Cree el campo nuevo SunRequirement

  • Multiplica el valor del campo Price por 0.9

Utilice constructores para crear la especificación de actualización con la variante tipificada:

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

Alternativamente, puedes usar nombres de campos basados en cadenas para definir la actualización:

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

Definir claves de índice

La clase IndexKeysDefinitionBuilder proporciona una interfaz con seguridad de tipos para definir claves de índice. Supongamos que desea seleccionar Category como clave de índice ascendente.

Usar desarrolladores para seleccionar la clave de índice con la variante tipada:

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

Alternativamente, puedes usar nombres de campos basados en cadenas para seleccionar la clave de índice:

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

La clase IndexKeysDefinitionBuilder también proporciona métodos para generar un índice comodín. Puede crear un índice comodín utilizando All field paths o A single field path, en este 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 obtener más información sobre cómo utilizar índices comodín, consulte Índices comodín.

Compilar un pipeline de agregación

La clase PipelineDefinitionBuilder proporciona una interfaz segura en cuanto a tipos para definir un pipeline de agregación. Un pipeline de agregación es una serie de etapas que se utilizan para transformar un documento. Suponga que desea crear un pipeline que realice las siguientes operaciones:

  • Coincide con todos los documentos que contengan "spring" en el campo Season

  • Ordena los resultados por el campo Category

  • Agrupa los documentos por categoría y muestra el precio promedio y el total disponible para todos los documentos en esa categoría

Utiliza clases PipelineDefinitionBuilder para compilar el 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)
               }
          );

El ejemplo anterior crea la siguiente canalización:

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

Puedes añadir etapas a tu pipeline que no tengan métodos type-safe correspondientes en la interfaz PipelineDefinitionBuilder proporcionando tu query como un BsonDocument al método AppendStage().

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

Nota

Al usar un BsonDocument para definir la etapa de la canalización, el controlador no tiene en cuenta ningún BsonClassMap, atributo ni convención de serialización. Los nombres de campo usados ​​en el BsonDocument deben coincidir con los almacenados en el servidor.

Para obtener más información sobre cómo proporcionar una query como BsonDocument, consulta nuestro Página de preguntas frecuentes.

Para obtener más información sobre Aggregation Pipeline, consulte la página del manual del servidor Aggregation Pipeline.

Guardar resultados de pipeline en una colección

Puede escribir los documentos devueltos desde una canalización de agregación en una colección creando una etapa $out al final de la canalización. Para crear una etapa $out, llame al método Out() en un PipelineStageDefinitionBuilder. El método Out() requiere el nombre de la colección en la que desea escribir los documentos.

El siguiente ejemplo construye un pipeline de agregación que coincide con todos los documentos con un valor de campo season de "Spring" y los envía a una colección 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);

Puedes escribir los resultados de un pipeline de agregación en una colección de series de tiempo especificando un objeto TimeSeriesOption y pasándolo como segundo parámetro al método Out().

Imaginen que los documentos de la colección plants.flowers contienen un campo datePlanted que almacena valores de fecha de BSON. Puedes almacenar los documentos de esta colección en una colección de series de tiempo utilizando el campo datePlanted como el campo de tiempo.

El siguiente ejemplo crea un objeto TimeSeriesOptions y especifica datePlanted como el timeField. A continuación, construye un pipeline de agregación que coincide con todos los documentos con un valor de campo season de "Spring" y los muestra en una colección de series de tiempo denominada 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 obtener más información sobre las colecciones de series temporales, consulte Colecciones de series temporales.

Compilar una query de MongoDB Search

La clase Search proporciona una interfaz Type-Safe para crear una etapa de $search en el pipeline.

Para aprender a construir consultas de búsqueda con la Search clase, consulte Búsqueda de MongoDB.

Realizar una búsqueda vectorial de MongoDB

Puedes utilizar desarrolladores para crear una etapa de pipeline de agregación $vectorSearch para realizar una búsqueda ANN en un vector en el campo especificado. Tu colección debe tener un índice definido de MongoDB Vector Search antes de que puedas realizar una búsqueda vectorial en tus datos.

Tip

Para obtener el conjunto de datos de muestra utilizado en el siguiente ejemplo, consulta Inicio rápido. Para crear el índice de búsqueda vectorial de MongoDB de muestra utilizado en el siguiente ejemplo, consulta Crear un índice de búsqueda vectorial de MongoDB en el manual de Atlas.

Considera la colección embedded_movies en la base de datos sample_mflix. Se puede utilizar una etapa $vectorSearch para realizar una búsqueda semántica en el campo plot_embedding de los documentos en la colección.

El siguiente ejemplo muestra cómo utilizar los desarrolladores para generar una pipeline de agregación que realice las siguientes operaciones:

  • Realiza una búsqueda vectorial en el índice MongoDB Vector Search del campo plot_embedding utilizando incrustaciones vectoriales para el string "time travel"

  • Obtiene los campos Title y Plot de los documentos encontrados en la búsqueda vectorial

// 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));

Los resultados del ejemplo anterior contienen los siguientes 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 obtener más información sobre MongoDB Vector Search, consulte Descripción general de MongoDB Vector Search en el manual de Atlas.

Información Adicional

Encuentre ejemplos ejecutables que utilizan constructores para varias operaciones en Ejemplos de uso.

Documentación de la API

Para obtener más información sobre cualquiera de los métodos o tipos discutidos en esta guía, consultar la siguiente documentación de la API:

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