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Fundamentals

LINQ

On this page

  • Overview
  • Make A Collection Queryable
  • Supported Aggregation Stages
  • $project
  • $match
  • $limit
  • $skip
  • $unwind
  • Nested Statements
  • $group
  • $sort
  • $lookup
  • $vectorSearch
  • Bitwise Operators
  • $bitAnd
  • $bitOr
  • $bitNot
  • $bitXor
  • Unsupported Aggregation Stages
  • Supported Methods
  • View Translated Queries

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.

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 the Quick Start.

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.

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();

The AsQueryable() method returns an IMongoQueryable instance that has the IQueryable extension methods, along with a set of MongoDB specific methods.

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:

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

You can print the results of the preceding example as follows:

foreach (var restaurant in query)
{
    Console.WriteLine(restaurant.ToJson());
}
{ "name" : "The Movable Feast", "address" : { "building" : "284", "coord" : [-73.982923900000003, 40.6580753], "street" : "Prospect Park West", "zipcode" : "11215" } }

Tip

Accessing Query Results

You can also access the results of your query by using the ToList() or ToCursor() methods:

var results = query.ToList();
var results = query.ToCursor();

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 the Aggregation Stages page in the 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:

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

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

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" }

$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" }
...

$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:

var query = queryableCollection
    .Where(r => r.Name == "The Movable Feast")
    .SelectMany(r => r.Grades);
var query = from r in queryableCollection
    where r.Name == "The Movable Feast"
    from grade in r.Grades
    select grade;

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 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 an $group stage using LINQ:

var query = queryableCollection
    .GroupBy(r => r.Cuisine)
    .Select(g => new { Cuisine = g.Key, Count = g.Count() });
var query = from r in queryableCollection
    group r by r.Cuisine into g
    select 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 an $sort stage using LINQ:

var query = queryableCollection
    .OrderBy(r => r.Name)
    .ThenByDescending(r => r.RestaurantId);
var query = from r in queryableCollection
    orderby r.Name, r.RestaurantId descending
    select r;

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.

Note

To perform a 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.

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; }
}

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

var query = queryableCollection
    .GroupJoin(reviewCollection,
        restaurant => restaurant.Name,
        review => review.RestaurantName,
        (restaurant, reviews) =>
            new { Restaurant = restaurant, Reviews = reviews }
    );
var query = from restaurant in queryableCollection
    join rv in reviewCollection on restaurant.Name equals rv.RestaurantName into reviews
    select new { restaurant, 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"
      }
   ]
}

$vectorSearch

The $vectorSearch aggregation stage performs an approximate nearest neighbor search on a vector in the specified field. Your collection must have a defined Atlas 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 Quick Start. To create the sample Atlas Vector Search index used in the following example, see Create an Atlas Vector Search Index in the Atlas manual.

Consider the embedded_movies collection in the sample_mflix database. You can use a $vectorSearch stage to perform a semantic search on the plot_embedding field of the documents in the collection.

The following EmbeddedMovie class models the documents in the embedded_movies collection:

[BsonIgnoreExtraElements]
public class EmbeddedMovie
{
   [BsonIgnoreIfDefault]
   public string Title { get; set; }
   public string Plot { get; set; }
   [BsonElement("plot_embedding")]
   public double[] Embedding { get; set; }
}

The following example shows how to generate a $vectorSearch stage to search the plot_embedding field using vector embeddings for the string "time travel":

// 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 results = queryableCollection
   .VectorSearch(m => m.Embedding, vector, 10, options)
   .Select(m => new { m.Title, m.Plot });

The results of the preceding example contain the following documents:

{ "_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" }

For more information about Atlas Vector Search, Atlas Vector Search indexes, and how to incorporate them into your application, see Atlas Vector Search Overview in the Atlas manual. For more examples about running Atlas Vector Search queries using the .NET/C# Driver, see Run Vector Search Queries in the Atlas manual and select C# from the language dropdown.

Bitwise Operators

This section describes the bitwise operators supported by the .NET/C# Driver that you can use in an aggregation pipeline. You can use multiple bitwise operators in the same stage. The following guidelines apply when using bitwise operators:

  • All operands must be of type int or long.

  • $bitAnd, $bitOr, and $bitXor take two or more operands. $bitNot takes one operand.

  • Bitwise operations are evaluated from left to right.

The examples in this section use the following documents in a collection called ingredients:

{ "_id" : 1, "name" : "watermelon", "is_available" : 1, "is_cheap" : 1 },
{ "_id" : 2, "name" : "onions", "is_available" : 1, "is_cheap" : 0 },
{ "_id" : 3, "name" : "eggs", "is_available" : 0, "is_cheap" : 0 },
{ "_id" : 4, "name" : "potatoes", "is_available" : 1, "is_cheap" : 1 },
{ "_id" : 5, "name" : "pasta", "is_available" : 0, "is_cheap" : 1 },
{ "_id" : 6, "name" : "cheese", "is_available" : 1 }

The "is_available" field represents if an ingredient is available. If this field has a value of 0, the ingredient is not available. If it has a value of 1, the ingredient is available.

The "is_cheap" field represents if an ingredient is cheap. If this field has a value of 0, the ingredient is not cheap. If it has a value of 1, the ingredient is cheap.

The following Ingredient class models the documents in the ingredients collection:

public class Ingredient 
{
    public int Id { get; set; }
    public string Name { get; set; }
    [BsonElement("is_available")]
    public int? IsAvailable { get; set; }
    [BsonElement("is_cheap")]
    public int? IsCheap { get; set; }
}

Note

Missing or Undefined Operands

If the operands you pass to any bitwise operator are of type nullable int or long and contain a missing or undefined value, the entire expression evaluates to null. If the operands are of type non-nullable int or long and contain a missing or undefined value, the .NET/C# Driver will throw an error.

$bitAnd

The $bitAnd aggregation operator performs a bitwise AND operation on the given arguments. You can use the $bitAnd operator by connecting two or more clauses with a & character.

The following example shows how to create a $bitAnd stage by using LINQ. The code retrieves the document in which the Name field has the value "watermelon". It then performs a bitwise AND operation on the values of the IsAvailable and IsCheap fields in this document.

var query = queryableCollection
    .Where(i => i.Name == "watermelon")
    .Select(i => i.IsAvailable & i.IsCheap);

The preceding code returns 1, the result of the AND operation on the values of the IsAvailable field (1) and the IsCheap field (1).

The following example performs the same bitwise AND operation on all documents in the collection:

var query = queryableCollection
    .Select(i => i.IsAvailable & i.IsCheap);
1
0
0
1
0
null

The null result comes from the document where the Name field has the value of "cheese". This document is missing an IsCheap field, so the expression evaluates to null.

$bitOr

The $bitOr aggregation operator performs a bitwise OR operation on the given arguments. You can use the $bitOr operator by connecting two or more clauses with a | character.

The following example shows how to create a $bitOr stage by using LINQ. The code retrieves the document in which the Name field has the value "onions". It then performs a bitwise OR operation on the values of the IsAvailable and IsCheap fields in this document.

var query = queryableCollection
    .Where(i => i.Name == "onions")
    .Select(i => i.IsAvailable | i.IsCheap);

The preceding code returns 1, the result of the OR operation on the values of the IsAvailable field (1) and the IsCheap field (0).

$bitNot

The $bitNot aggregation operator performs a bitwise NOT operation on the given argument. You can use the $bitNot operator by preceding an operand with a ~ character. $bitNot only takes one argument. The following example shows how to create a $bitNot stage by using LINQ:

var query = queryableCollection
    .Select(i => ~i.IsCheap);
-2
-1
-1
-2
-2
null

$bitXor

The $bitXor aggregation operator performs a bitwise XOR operation on the given arguments. You can use the $bitXor operator by connecting two or more clauses with a ^ character.

The following example shows how to create a $bitXor stage by using LINQ. The code retrieves the documents in which the Name field has the value "watermelon" or "onions". It then performs a bitwise XOR operation on the values of the IsAvailable and IsCheap fields in these documents.

var query = queryableCollection
    .Where(i => i.Name == "watermelon" || i.Name == "onions")
    .Select(i => i.IsAvailable ^ i.IsCheap);

The result contains the following values:

0
1

Unsupported Aggregation Stages

The MongoDB .NET/C# Driver implementation of LINQ does not support the following aggregation stages:

  • $redact

  • $geoNear

  • $out

To learn how to create an aggregation pipeline with the $out stage by using Builders, see the Write Pipeline Results to a Collection section.

Supported Methods

The following are some methods supported by the MongoDB .NET/C# Driver implementation of LINQ:

Method Name
Description

Any

Determines if any documents match the specified criteria

Average

Calculates the average of the specified fields

Count

Returns an Int32 that represents the number of documents that match the specified criteria

LongCount

Returns an Int64 that represents the number of documents that match the specified criteria

DateFromString

Converts a string to a DateTime object

Distinct

Returns distinct documents that match the specified criteria

Exists

Tests whether a field exists

First

Returns the first matching document, and throws an exception if none are found

FirstOrDefault

Returns the first matching document, or null if none are found

GroupBy

Groups documents based on specified criteria

GroupJoin

Performs a left outer join to another collection in the same database

IsMissing

Returns true if a field is missing and false otherwies

IsNullOrMissing

Returns true if a field is null or missing and false otherwise

Max

Returns the document with the maximum specified value

OfType

Returns documents that match the specified type

OrderBy, OrderByDescending

Returns results in a specified sort order

ThenBy, ThenByDescending

Allows a secondary sort to be specified

Select

Selects documents based on specified criteria

SelectMany

Projects each element of a sequence and combines the resulting sequences into one document

Single

Returns the only matching document, and throws an exception if there is not exactly one document

SingleOrDefault

Returns a single matching document or null if no documents match

Skip

Skips over a specified number of documents and returns the rest of the results

Sum

Returns the sum of the values in a specified field

Take

Specifies the number of results to return

Where

Returns all documents that match your specified criteria

View Translated Queries

When you run a LINQ query, the .NET/C# Driver automatically translates your query into an aggregation pipeline written with the MongoDB Query API. You can view the translated query by using the ToString() method or the LoggedStages property.

To see the translated query for non-scalar operations, use the ToString() method. Non-scalar operations are operations that return a query object, such as:

  • Where

  • Select

  • SelectMany

  • GroupJoin

The following example calls the ToString() method on a LINQ query and prints the translated query:

 var queryableCollection = _restaurantsCollection.AsQueryable();
 var query = queryableCollection
      .Where(r => r.Name == "The Movable Feast");
 var queryTranslated = query.ToString();
 Console.WriteLine(queryTranslated);
sample_restaurants.restaurants.Aggregate([{ "$match" : { "name" : "The Movable Feast" } }])

To get the translated query for scalar operations use the LoggedStages property. Scalar operations are operations that return a scalar result rather than a query object, such as:

  • First

  • Sum

  • Count

  • Min

  • Max

To get a translated query with the LoggedStages property, you must save the translated query directly after it is executed, and before executing any other queries with the same queryable object.

The following example uses the LoggedStages property on a LINQ query that uses a scalar operation, then prints the translated query:

var queryableCollection = _restaurantsCollection.AsQueryable();
var query = queryableCollection
    .Where(r => r.Name == "The Movable Feast");
var result = query.FirstOrDefault();
var queryTranslated = query.LoggedStages;
Console.WriteLine(queryTranslated.ToJson());
[{ "$match" : { "name" : "The Movable Feast" } }, { "$limit" : NumberLong(1) }]

Important

LoggedStages is not thread-safe. Executing a query and accessing the associated LoggedStages property from multiple threads might have non-deterministic results.

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Aggregation

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BSON Operations