$match
Filters the documents to pass only the documents that match the specified condition(s) to the next pipeline stage.
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
The $match stage has the following prototype form:
$match takes a document that specifies the query conditions. The query syntax is identical to the read operation query syntax; i.e. $match does not accept raw aggregation expressions. Instead, use a $expr query expression to include aggregation expression in $match.
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().
To include expressions in a query predicate, use the $expr operator.
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.
The $match query syntax is identical to the read operation query syntax; i.e. $match does not accept raw aggregation expressions. To include aggregation expression in $match, use a $expr query expression:
{ $match: { $expr: { <aggregation expression> } } }You cannot use $where in $match queries as part of the aggregation pipeline.
You cannot use $near or $nearSphere in $match queries as part of the aggregation pipeline. As an alternative, you can either:
Use $geoWithin query operator with $center or $centerSphere in the $match stage.
To use $text in the $match stage, the $match stage has to be the first stage of the pipeline.
Views do not support $text.
$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.
For data stored in MongoDB Atlas, you can use the Atlas Search compound Operator 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 operator filter option.
To learn more about the filter option, see compound Operator in the Atlas documentation.
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 }The following operation uses $match to perform a simple 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 }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 ObjectId 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; }}The C# classes on this page use Pascal case for their property names, but the field names in the MongoDB collection use camel case. To account for this difference, you can use the following code to register a ConventionPack when your application starts:
var camelCaseConvention = new ConventionPack { new CamelCaseElementNameConvention() };ConventionRegistry.Register("CamelCase", camelCaseConvention, type => true);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");The Node.js 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 Node.js driver documentation.
To use the MongoDB Node.js driver to add a $match stage to an aggregation pipeline, use the $match operator in a pipeline object.
The following example creates a pipeline stage that matches all movie documents where the title field is equal to "The Shawshank Redemption". The example then runs the aggregation pipeline:
const pipeline = [ { $match: { title: "The Shawshank Redemption" } }];const cursor = collection.aggregate(pipeline);return cursor;Refer to the Complete Aggregation Pipeline Tutorials for more information and use cases on aggregation.
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