$match (aggregation)



Filters the documents to pass only the documents that match the specified condition(s) to the next pipeline stage.

The $match stage has the following prototype form:

{ $match: { <query> } }

$match takes a document that specifies the query conditions. The query syntax is identical to the read operation query syntax.


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().


  • You cannot use $where in $match queries as part of the aggregation pipeline.
  • To use $text in the $match stage, the $match stage has to be the first stage of the pipeline.


Equality Match

The following operation uses $match to perform a simple equality match:

    [ { $match : { author : "dave" } } ]

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

  "result" : [
                 "_id" : ObjectId("512bc95fe835e68f199c8686"),
                 "author": "dave",
                 "score" : 80
               { "_id" : ObjectId("512bc962e835e68f199c8687"),
                 "author" : "dave",
                 "score" : 85
  "ok" : 1

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 : { score : { $gt : 70, $lte : 90 } } },
                        { $group: { _id: null, count: { $sum: 1 } } }
                       ] );

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

  "result" : [
                 "_id" : null,
                 "count" : 3
  "ok" : 1

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