$match (aggregation)

Definition

$match: Filters documents based on a specified query predicate. Matched documents are passed to the next pipeline stage.

Compatibility

You can use $match for deployments hosted in the following environments:

MongoDB Atlas: The fully managed service for MongoDB deployments in the cloud

MongoDB Enterprise: The subscription-based, self-managed version of MongoDB
MongoDB Community: The source-available, free-to-use, and self-managed version of MongoDB

Syntax

{ $match: { <query predicate> } }

The syntax for the $match query predicate is identical to the syntax used in the query argument of a find() command.

Behavior

Pipeline Optimization

Place the $match as early in the aggregation pipeline as possible. Because $match limits the total number of documents in the aggregation pipeline, earlier $match operations minimize the amount of processing down the pipe.
If you place a $match at the very beginning of a pipeline, the query can take advantage of indexes like any other db.collection.find() or db.collection.findOne().

Expressions in Query Predicates

To include expressions in a query predicate, use the $expr operator.

0, Null, False or Missing Values

A $match stage filters out a document from pipeline results if one of the following conditions applies:

The $match query predicate returns a 0, null, or false value on that document.
The $match query predicate uses a field that is missing from that document.

Restrictions

You cannot use $where in a $match stage.
You cannot use $near or $nearSphere in a $match stage. As an alternative, you can either:
- Use the $geoNear stage instead of the $match stage.
- Use the $geoWithin query predicate operator with $center or $centerSphere in the $match stage.
To use $text in a $match stage, the $match stage has to be the first stage of the pipeline.
Views do not support $text.
Note
$text provides text query capabilities for self-managed (non-Atlas) deployments. For data hosted on MongoDB Atlas, MongoDB offers an improved full-text query solution, Atlas Search.

Filter Data on Atlas by Using Atlas Search

For data stored in MongoDB Atlas, you can use the Atlas Search compound operator filter option to match or filter documents when running $search queries. Running $match after $search is less performant than running $search with the compound operator filter option.

To learn more about the filter option, see compound in the Atlas documentation.

Examples

The examples use a collection named articles with the following documents:

{ "_id" : ObjectId("512bc95fe835e68f199c8686"), "author" : "dave", "score" : 80, "views" : 100 }
{ "_id" : ObjectId("512bc962e835e68f199c8687"), "author" : "dave", "score" : 85, "views" : 521 }
{ "_id" : ObjectId("55f5a192d4bede9ac365b257"), "author" : "ahn", "score" : 60, "views" : 1000 }
{ "_id" : ObjectId("55f5a192d4bede9ac365b258"), "author" : "li", "score" : 55, "views" : 5000 }
{ "_id" : ObjectId("55f5a1d3d4bede9ac365b259"), "author" : "annT", "score" : 60, "views" : 50 }
{ "_id" : ObjectId("55f5a1d3d4bede9ac365b25a"), "author" : "li", "score" : 94, "views" : 999 }
{ "_id" : ObjectId("55f5a1d3d4bede9ac365b25b"), "author" : "ty", "score" : 95, "views" : 1000 }

Equality Match

The following operation uses $match to perform an equality match:

db.articles.aggregate(
    [ { $match : { author : "dave" } } ]
);

The $match selects the documents where the author field equals dave, and the aggregation returns the following:

{ "_id" : ObjectId("512bc95fe835e68f199c8686"), "author" : "dave", "score" : 80, "views" : 100 }
{ "_id" : ObjectId("512bc962e835e68f199c8687"), "author" : "dave", "score" : 85, "views" : 521 }

Perform a Count

The following example selects documents to process using the $match pipeline operator and then pipes the results to the $group pipeline operator to compute a count of the documents:

db.articles.aggregate( [
  { $match: { $or: [ { score: { $gt: 70, $lt: 90 } }, { views: { $gte: 1000 } } ] } },
  { $group: { _id: null, count: { $sum: 1 } } }
] );

In the aggregation pipeline, $match selects the documents where either the score is greater than 70 and less than 90 or the views is greater than or equal to 1000. These documents are then piped to the $group to perform a count. The aggregation returns the following:

{ "_id" : null, "count" : 5 }

The C# examples on this page use the sample_mflix database from the Atlas sample datasets. To learn how to create a free MongoDB Atlas cluster and load the sample datasets, see Get Started in the MongoDB .NET/C# Driver documentation.

The following Movie class models the documents in the sample_mflix.movies collection:

public class Movie
{
    public string Id { get; set; }
    public int Runtime { get; set; }
    
    public string Title { get; set; }
    public string Rated { get; set; }
    public List<string> Genres { get; set; }
    public string Plot { get; set; }
    
    public ImdbData Imdb { get; set; }
    public int Year { get; set; }
    public int Index { get; set; }
    
    public string[] Comments { get; set; }
   
    [BsonElement("lastupdated")]
    public DateTime LastUpdated { get; set; }
}

To use the MongoDB .NET/C# driver to add a $match stage to an aggregation pipeline, call the Match() method on a PipelineDefinition object.

The following example creates a pipeline stage that matches all Movie documents where the Title field is equal to "The Shawshank Redemption":

var pipeline = new EmptyPipelineDefinition<Movie>()
    .Match(m => m.Title == "The Shawshank Redemption");

Additional Information

Refer to the following pages for more information and use cases on aggregation.

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$merge