linq

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LINQ Syntax for Aggregation Operations

Overview

In this guide you can learn how to use LINQ with the MongoDB .NET/C# Driver. LINQ allows you to construct queries against strongly typed collections of objects by using language keywords and operators. The .NET/C# Driver automatically translates LINQ queries into aggregation operations.

Important: Input Validation

Builder classes and LINQ queries pass values to the underlying MongoDB operation. By design, these APIs are not a security sanitization layer. Validate and sanitize untrusted input in your application before you pass it to a builder or a LINQ query.

The examples in this guide use the restaurants collection in the sample_restaurants database provided in the Atlas sample datasets. To learn how to create a free MongoDB Atlas cluster and load the sample datasets, see [Get Started with the .NET/C# Driver.](https://www.mongodb.com/docs/drivers/csharp/current/get-started.md#std-label-csharp-get-started

The following Restaurant, Address and GradeEntry classes model the documents in this collection:

public class Restaurant
{
    public ObjectId Id { get; set; }

    public string Name { get; set; }

    [BsonElement("restaurant_id")]
    public string RestaurantId { get; set; }

    public string Cuisine { get; set; }

    public Address Address { get; set; }

    public string Borough { get; set; }

    public List<GradeEntry> Grades { get; set; }

}

public class Address
{
    public string Building { get; set; }

    [BsonElement("coord")]
    public double[] Coordinates { get; set; }

    public string Street { get; set; }

    [BsonElement("zipcode")]
    public string ZipCode { get; set; }
}

public class GradeEntry
{
    public DateTime Date { get; set; }

    public string Grade { get; set; }

    public float Score { get; set; }
}

Note:

The documents in the restaurants collection use the snake-case naming convention. The examples in this guide use a ConventionPack to deserialize the fields in the collection into Pascal case and map them to the properties in the Restaurant class.

To learn more about custom serialization, see [Custom Serialization.](https://www.mongodb.com/docs/drivers/csharp/current/serialization/poco.md#std-label-csharp-custom-serialization

Important:

LINQ3 is the only LINQ provider available in the MongoDB .NET/C# Driver. If you have manually configured your project to use LINQ2, it will not compile.

Make A Collection Queryable

To use LINQ to query your collection, you must first create an an IQueryable object that links to the collection. To create the object, use the AsQueryable() method as follows:

var restaurantsDatabase = client.GetDatabase("sample_restaurants");
var restaurantsCollection = restaurantsDatabase.GetCollection<Restaurant>("restaurants");
var queryableCollection = restaurantsCollection.AsQueryable();

Once you have the queryable object, you can compose a query using method syntax. Some pipeline stages also support query comprehension syntax, which resembles SQL query syntax.

Select the Method Syntax or Query Syntax tab to see how to compose a query using LINQ:

Method Syntax

var query = queryableCollection
    .Where(r => r.Name == "The Movable Feast")
    .Select(r => new { r.Name, r.Address });

Accessing Query Results

To iterate synchronously over the results from the preceding example, use a foreach statement:

foreach (var restaurant in query)
{
    Console.WriteLine(restaurant.ToJson());
}

Output:

{ "name" : "The Movable Feast", "address" : { "building" : "284", "coord" : [-73.982923900000003, 40.6580753], "street" : "Prospect Park West", "zipcode" : "11215" } }

To turn the results into a list, use the ToList() method:

var results = query.ToList();

To turn the results into a cursor, use the ToCursor() method:

var results = query.ToCursor();

To iterate asynchronously over the results, use an await foreach statement with the ToAsyncEnumerable() method:

await foreach (var restaurant in query.ToAsyncEnumerable())
{
    Console.WriteLine(restaurant.ToJson());
}

Output:

{ "name" : "The Movable Feast", "address" : { "building" : "284", "coord" : [-73.982923900000003, 40.6580753], "street" : "Prospect Park West", "zipcode" : "11215" } }

Supported Aggregation Stages

You can use LINQ to create an aggregation pipeline. The .NET/C# Driver automatically translates each LINQ statement into the corresponding aggregation pipeline stages. In this section you can learn which aggregation pipeline stages are supported.

To learn more about the aggregation pipeline stages, see Aggregation Stages in the MongoDB Server manual.

$project

The $project aggregation stage returns a document containing only the specified fields.

Select the Method Syntax or Query Syntax tab to see how to generate a $project stage using LINQ:

Method Syntax

var query = queryableCollection
    .Select(r => new { r.Name, r.Address });

The result of the preceding example contains the following document:

{ "name" : "The Movable Feast", "address" : { "building" : "284", "coord" : [-73.982923900000003, 40.6580753], "street" : "Prospect Park West", "zipcode" : "11215" } }

Note: Excluding the _id Field

If you don't include the _id field in your LINQ projection, the .NET/C# Driver automatically excludes it from the results.

$match

The $match aggregation stage returns the documents that match a specified criteria.

Select the Method Syntax or Query Syntax tab to see how to generate a $match stage using LINQ:

Method Syntax

var query = queryableCollection
    .Where(r => r.Name == "The Movable Feast");

The result of the preceding example contains the following document:

 // Results Truncated

 { "_id" : ObjectId(...), "name" : "The Movable Feast", "restaurant_id" : "40361606", "cuisine" : "American", "address" : {...}, "borough" : "Brooklyn", "grades" : [...] }

$limit

The $limit aggregation stage limits the number of documents returned by the query. The following example shows how to generate a $limit stage using LINQ:

var query = queryableCollection
    .Where(r => r.Cuisine == "Italian")
    .Select(r => new {r.Name, r.Cuisine})
    .Take(5);

The result of the preceding example contains the following documents:

 { "name" : "Philadelhia Grille Express", "cuisine" : "Italian" }
 { "name" : "Isle Of Capri Resturant", "cuisine" : "Italian" }
 { "name" : "Marchis Restaurant", "cuisine" : "Italian" }
 { "name" : "Crystal Room", "cuisine" : "Italian" }
 { "name" : "Forlinis Restaurant", "cuisine" : "Italian" }

Limit on a Condition

You can use the TakeWhile() LINQ method in a Select() projection to return array field elements while a specified condition is true, then skip the remaining elements.

This example uses the following Student class to model documents that contain an array field Grades:

public class Student
{
    public ObjectId Id { get; set; }
    public string Name { get; set; }
    public int[] Grades { get; set; }
}

The following code shows how to use the TakeWhile() method to return any Grades array elements that are greater than 90 and skip the rest of the array:

var query = queryableCollection
    .Select(s => s.Grades.TakeWhile(g => g > 90).ToArray());

The results might resemble the following arrays:

[92, 97]
[100, 95, 91]

$sample

The $sample aggregation stage returns a random sample of documents from a collection. The following example shows how to generate a $sample stage by using LINQ:

var query = queryableCollection
    .Aggregate()
    .Sample(4)
    .ToList();

The result of the preceding example contains the following documents:

// Results Truncated

{ "name" : "Von Dolhens", "cuisine" : "Ice Cream, Gelato, Yogurt, Ices" }
{ "name" : "New York Mercantile Exchange", "cuisine" : "American" }
{ "name" : "Michaelangelo's Restaurant", "cuisine" : "Italian" }
{ "name" : "Charlie Palmer Steak", "cuisine" : "American" }

$skip

The $skip aggregation stage skips over a specified number of documents returned by a query, then returns the rest of the results. The following example shows how to generate a $skip stage using LINQ:

var query = queryableCollection
    .Where(r => r.Cuisine == "Italian")
    .Select(r => new {r.Name, r.Cuisine})
    .Skip(2);

The preceding example skips the first two restaurants that match the criteria, and returns the rest. The result contains the following documents:

// Results Truncated

{ "name" : "Marchis Restaurant", "cuisine" : "Italian" }
{ "name" : "Crystal Room", "cuisine" : "Italian" }
{ "name" : "Forlinis Restaurant", "cuisine" : "Italian" }
...

Skip on a Condition

You can use the SkipWhile() LINQ method in a Select() projection to skip array field elements while a specified condition is true, then return the remaining elements.

This example uses the following Student class to model documents that contain an array field Grades:

public class Student
{
    public ObjectId Id { get; set; }
    public string Name { get; set; }
    public int[] Grades { get; set; }
}

The following code shows how to use the SkipWhile() method to skip any Grades array elements that are less than 75 and return the rest of the array:

var query = queryableCollection
    .Select(s => s.Grades.SkipWhile(g => g < 75).ToArray());

The results might resemble the following arrays:

[80, 90, 70, 83]
[79, 100, 85, 73]

$unwind

The $unwind aggregation stage deconstructs a specified array field and returns a document for each element in that array.

Select the Method Syntax or Query Syntax tab to see how to generate an $unwind stage using LINQ:

Method Syntax

var query = queryableCollection
    .Where(r => r.Name == "The Movable Feast")
    .SelectMany(r => r.Grades);

The query in the preceding example finds the document where the Name field has the value “The Movable Feast.” Then, for each element in this document's Grades array, the query returns a new document. The result contains the following documents:

{ "date" : ISODate("2014-11-19T00:00:00Z"), "grade" : "A", "score" : 11 }
{ "date" : ISODate("2013-11-14T00:00:00Z"), "grade" : "A", "score" : 2 }
{ "date" : ISODate("2012-12-05T00:00:00Z"), "grade" : "A", "score" : 13 }
{ "date" : ISODate("2012-05-17T00:00:00Z"), "grade" : "A", "score" : 11 }

Nested Statements

You can chain or nest Select and SelectMany statements to unwind nested arrays. Consider a collection that contains documents with a new schema. These documents contain a restaurants field, which holds an array of documents represented by the Restaurant class. The documents within the array each have a grades field that holds an array of documents represented by the Grade class. The following code is an example of a single document in this collection:

{
   "_id": { "$oid": ... },
   "restaurants": [
      {
         "_id": { ... } ,
         "address": { ... },
         "name": "Tov Kosher Kitchen",
         "grades": [
            {
               "date" : ISODate("2014-11-24T00:00:00Z"),
               "grade" : "Z",
               "score" : 20.0
            },
            {
               "date" : ISODate("2013-01-17T00:00:00Z"),
               "grade" : "A",
               "score" : 13.0
            }
         ]
         ...
      },
      {
         "_id": { ... } ,
         "address": { ... },
         "name": "Harriet's Kitchen",
         "grades": [
            {
               "date" : ISODate("2014-04-19T00:00:00Z"),
               "grade" : "B",
               "score" : 12.0
            }
          ],
         ...
      },
      ...
   ]
}

You can nest SelectMany statements within SelectMany or Select statements. The following example nests a SelectMany statement within a Select statement to retrieve an array from each document in the collection. Each array holds all grade objects from all restaurants in each document.

var query = queryableCollection
    .Select(r => r.Restaurants.SelectMany(r => r.Grades));

Output:

// output for first document in collection
[
   { "date" : ISODate("2014-11-24T00:00:00Z"),
      "grade" : "Z",
      "score" : 20.0
   },
   { "date" : ISODate("2013-01-17T00:00:00Z"),
      "grade" : "A",
      "score" : 13.0
   },
   {
      "date" : ISODate("2014-04-19T00:00:00Z"),
      "grade" : "B",
      "score" : 12.0
   },
   ...
],
// output for second document in collection
[
   ...
]

$group

The $group aggregation stage separates documents into groups according to the criteria you specify.

Select the Method Syntax or Query Syntax tab to see how to generate a $group stage using LINQ:

Method Syntax

var query = queryableCollection
    .GroupBy(r => r.Cuisine)
    .Select(g => new { Cuisine = g.Key, Count = g.Count() });

The preceding example groups each document by the value in its Cuisine field, then counts how many documents have each Cuisine value. The result contains the following documents:

// Results Truncated

{ "cuisine" : "Caribbean", "count" : 657 }
{ "cuisine" : "Café/Coffee/Tea", "count" : 1214 }
{ "cuisine" : "Iranian", "count" : 2 }
{ "cuisine" : "Nuts/Confectionary", "count" : 6 }
{ "cuisine" : "Middle Eastern", "count" : 168 }
...

Note: Result Order

The preceding queries don't always return results in the same order. Running this example may return the results in a different order than shown above.

$sort

The $sort aggregation stage returns the results of your query in the order that you specify.

Select the Method Syntax or Query Syntax tab to see how to generate a $sort stage using LINQ:

Method Syntax

var query = queryableCollection
    .OrderBy(r => r.Name)
    .ThenByDescending(r => r.RestaurantId);

The preceding example returns the query results sorted alphabetically by the Name field, with a secondary descending sort on the RestaurantId field. The following is a subset of the documents contained in the returned results:

// Results Truncated

...
{ "_id" : ObjectId(...), "name" : "Aba Turkish Restaurant", "restaurant_id" : "41548686", "cuisine" : "Turkish", "address" : {...}, "borough" : "Manhattan", "grades" : [...] }
{ "_id" : ObjectId(...), "name" : "Abace Sushi", "restaurant_id" : "50006214", "cuisine" : "Japanese", "address" : { ... }, "borough" : "Manhattan", "grades" : [...] }
{ "_id" : ObjectId(...), "name" : "Abacky Potluck", "restaurant_id" : "50011222", "cuisine" : "Asian", "address" : { ... }, "borough" : "Manhattan", "grades" : [...] }
{ "_id" : ObjectId(...), "name" : "Abaleh", "restaurant_id" : "50009096", "cuisine" : "Mediterranean", "address" : { ... }, "borough" : "Manhattan", "grades" : [...] }
...

$lookup

The $lookup aggregation stage joins documents from one collection to documents from another collection in the same database. The $lookup stage adds a new array field to each input document. The new array field contains the matching documents from the “joined” collection.

Consider a second collection in the sample_restaurants database called reviews that has restaurant reviews. You can join documents from that collection to documents with the same name value in the restaurants collection using the $lookup stage.

The following Review class models the documents in the reviews collection:

public class Review
{
    public ObjectId Id { get; set; }

    [BsonElement("restaurant_name")]
    public string RestaurantName { get; set; }

    public string Reviewer { get; set; }

    [BsonElement("review_text")]
    public string ReviewText { get; set; }
}

You can specify a $lookup stage by calling the Lookup() method or the GroupJoin() method. The following sections show how to perform a $lookup by using each method.

Lookup()

The following code specifies a $lookup stage by using the Lookup() method. This example joins documents from the reviews collection to documents from the restaurants collection where the RestaurantName field in the reviews collection matches the Name field in the restaurants collection:

var lookupResult = restaurantsCollection.AsQueryable()
 .Lookup(reviewCollection,
     restaurant => restaurant.Name,
     review => review.RestaurantName);

The preceding example returns a list of LookupResult objects that each contain a joined document. To learn more about the LookupResult class, see the LookupResult API documentation.

You can also use a Lookup() method overload to specify additional criteria for the join. The following example joins documents from the restaurants collection to documents from the reviews collection where the RestaurantName field in the reviews collection matches the Name field in the restaurants collection and the ReviewText field in the reviews collection contains the name of the restaurant:

var lookupResult = restaurantsCollection.AsQueryable()
   .Lookup(reviewCollection,
      (restaurant, reviews) => reviews
         .Where(review => review.ReviewText.Contains(restaurant.Name)));

To view a full list of overloads for the Lookup() method, see the Lookup API documentation.

GroupJoin()

You can specify a $lookup stage by using the LINQ GroupJoin() method. To perform a GroupJoin() lookup, you must make both collections queryable by using the AsQueryable() method. To learn how to make a collection queryable, see [Make A Collection Queryable.](https://www.mongodb.com/docs/drivers/csharp/current/aggregation/linq.md#std-label-csharp-linq-queryable

Select the Method Syntax or Query Syntax tab to see how to generate a $lookup stage by using LINQ:

Method Syntax

var query = queryableCollection
    .GroupJoin(reviewCollection,
        restaurant => restaurant.Name,
        review => review.RestaurantName,
        (restaurant, reviews) =>
            new { Restaurant = restaurant, Reviews = reviews }
    );

The preceding example returns all documents from the restaurants collection. Each restaurant document has an added field called reviews, which contains all reviews for that restaurant. A review matches a restaurant if the value of the name field in the review document matches the name field of the restaurant document.

The following shows a subset of the returned results:

// Results Truncated

{
   "restaurant": {
      "_id": ObjectId("..."),
      "name": "The Movable Feast",
      "restaurant_id": "40361606",
      "cuisine": "American",
      "address": { ... },
      "borough": "Brooklyn",
      "grades": [ ... ]
   },
   "reviews": [
      {
         "_id": ObjectId("..."),
         "restaurant_name": "The Movable Feast",
         "reviewer": "Lazlo Cravensworth",
         "review_text": "Great restaurant! 12/10 stars!"
      },
      {
         "_id": ObjectId("..."),
         "restaurant_name": "The Movable Feast",
         "reviewer": "Michael Scarn",
         "review_text": "It really was a feast"
      }
   ]
}

$search

The $search aggregation stage performs a full-text search on fields in a collection. You must define a [MongoDB Search](https://www.mongodb.com/docs/drivers/csharp/current/atlas-search.md#std-label-csharp-atlas-search index on the field before you can perform a $search operation on your data.

To create the MongoDB Search index that you need for the following example, run the following code on the restaurants collection:

var index =  new CreateSearchIndexModel(
  "default", new BsonDocument
   {
     { "mappings", new BsonDocument
      {
        { "dynamic", true }
      }
   }
});

var result = collection.SearchIndexes.CreateOne(index);

To create a $search pipeline stage, use the Search() method. The Search() method accepts SearchDefinition and SearchOptions objects as parameters. The SearchDefinition object contains the field to search and the value to search for. You can use the SearchOptions object to configure your search operation.

The following code shows how to use LINQ to create a $search pipeline stage that performs the following operations:

• Searches for documents where the Name field contains “Deli” by using the default search index

• Returns the Name and Cuisine fields of the matching restaurant documents

var searchOptions = new SearchOptions<Restaurant>()
{
   IndexName = "default"
};

var searchDefinition = Builders<Restaurant>.Search
   .Text(x => x.Name, "Deli");

var results = queryableCollection
   .Search(searchDefinition, searchOptions)
   .Select(m => new { m.Name, m.Cuisine });

The results of the preceding example contain the following documents:

// Results Truncated

{ "Name" : "Mexico Lindo Y ! Q Rico! Deli", "Cuisine" : "Mexican" }
{ "Name" : "Cold Cut City Bunny Deli 2", "Cuisine" : "American" }
{ "Name" : "Blue Moon Chicken Deli & Pizza Corp", "Cuisine" : "Other" }
{ "Name" : "Little Michaels Deli And Sald Bar", "Cuisine" : "Delicatessen" }
{ "Name" : "La Esperanza Mexican Deli Grocery & Vegetables", "Cuisine" : "Mexican" }
{ "Name" : "El Sol De Mexico Deli Grocery", "Cuisine" : "Mexican" }
{ "Name" : "C & C Deli Coffee Shop & Pastry", "Cuisine" : "Delicatessen" }
{ "Name" : "Jennis Deli And Grill And Grocery", "Cuisine" : "Spanish" }
{ "Name" : "La Nueva Estrella Pizza And Deli Grocery", "Cuisine" : "Spanish" }
{ "Name" : "Blue Cafe/3 In 1 Deli Restaurant", "Cuisine" : "American" }

For more information about MongoDB Search, MongoDB Search indexes, and how to incorporate them into your application, see MongoDB Search Overview in the Atlas manual.

$vectorSearch

The $vectorSearch aggregation stage performs an approximate nearest neighbor search on a vector in the specified field. Your collection must have a defined MongoDB Vector Search index before you can perform a vector search on your data.

Tip:

To obtain the sample dataset used in the following example, see [Get Started with the .NET/C# Driver](https://www.mongodb.com/docs/drivers/csharp/current/get-started.md#std-label-csharp-get-started. To create the sample MongoDB Vector Search index used in the following example, see Create a MongoDB Vector Search Index in the Atlas manual.

To create a $vectorSearch pipeline stage, call the VectorSearch() method on a PipelineStageDefinitionBuilder object. The VectorSearch() method accepts the following parameters:

You can use the options parameter to configure your vector search operation. The VectorSearchOptions class contains the following properties:

Consider the embedded_movies collection in the sample_mflix database. The following EmbeddedMovie class represents a document in this database:

[BsonIgnoreExtraElements]
public class EmbeddedMovie
{
    public ObjectId Id { get; set; }
    public string Plot { get; set; }
    public string Title { get; set; }
    [BsonElement("plot_embedding")]
    public float[] PlotEmbedding { get; set; }
}

You can use a $vectorSearch stage to perform a semantic search on the plot_embedding field of the documents in the collection. The following example shows how to use LINQ to generate an aggregation pipeline to perform the following operations:

• Perform a vector search on the MongoDB Vector Search index of the plot_embedding field by using vector embeddings for the string “time travel”

• Fetch the Title and Plot fields from documents found in the vector search

```csharp // Defines vector embeddings for the string "time travel" var vector = new[] 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