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$project (aggregation)

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  • Definition
  • Compatibility
  • Syntax
  • Behavior
  • Considerations
  • Examples
$project

Passes along the documents with the requested fields to the next stage in the pipeline. The specified fields can be existing fields from the input documents or newly computed fields.

You can use $project 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 $project stage has the following prototype form:

{ $project: { <specification(s)> } }

The $project takes a document that can specify the inclusion of fields, the suppression of the _id field, the addition of new fields, and the resetting of the values of existing fields. Alternatively, you may specify the exclusion of fields.

The $project specifications have the following forms:

Form
Description

<field>: <1 or true>

Specifies the inclusion of a field. Non-zero integers are also treated as true.

_id: <0 or false>

Specifies the suppression of the _id field.

To exclude a field conditionally, use the REMOVE variable instead. For details, see Exclude Fields Conditionally.

<field>: <expression>

Adds a new field or resets the value of an existing field.

If the expression evaluates to $$REMOVE, the field is excluded in the output. For details, see Exclude Fields Conditionally.

<field>: <0 or false>

Specifies the exclusion of a field.

To exclude a field conditionally, use the REMOVE variable instead. For details, see Exclude Fields Conditionally.

If you specify the exclusion of a field other than _id, you cannot employ any other $project specification forms. This restriction does not apply to conditionally exclusion of a field using the REMOVE variable.

See also the $unset stage to exclude fields.

  • The _id field is, by default, included in the output documents. To include any other fields from the input documents in the output documents, you must explicitly specify the inclusion in $project.

  • If you specify an inclusion of a field that does not exist in the document, $project ignores that field inclusion and does not add the field to the document.

By default, the _id field is included in the output documents. To exclude the _id field from the output documents, you must explicitly specify the suppression of the _id field in $project.

If you specify the exclusion of a field or fields, all other fields are returned in the output documents.

{ $project: { "<field1>": 0, "<field2>": 0, ... } } // Return all but the specified fields

If you specify the exclusion of a field other than _id, you cannot employ any other $project specification forms: i.e. if you exclude fields, you cannot also specify the inclusion of fields, reset the value of existing fields, or add new fields. This restriction does not apply to conditional exclusion of a field using the REMOVE variable.

See also the $unset stage to exclude fields.

You can use the variable REMOVE in aggregation expressions to conditionally suppress a field. For an example, see Conditionally Exclude Fields.

Note

MongoDB also provides $addFields to add new fields to the documents.

To add a new field or to reset the value of an existing field, specify the field name and set its value to some expression. For more information on expressions, see Expressions.

To set a field value directly to a numeric or boolean literal, as opposed to setting the field to an expression that resolves to a literal, use the $literal operator. Otherwise, $project treats the numeric or boolean literal as a flag for including or excluding the field.

By specifying a new field and setting its value to the field path of an existing field, you can effectively rename a field.

The $project stage supports using the square brackets [] to directly create new array fields. If you specify array fields that do not exist in a document, the operation substitutes null as the value for that field. For an example, see Project New Array Fields.

You cannot use an array index with the $project stage. For more information, see Array Indexes are Unsupported.

When projecting or adding/resetting a field within an embedded document, you can either use dot notation, as in

"contact.address.country": <1 or 0 or expression>

Or you can nest the fields:

contact: { address: { country: <1 or 0 or expression> } }

When nesting the fields, you cannot use dot notation inside the embedded document to specify the field, e.g. contact: { "address.country": <1 or 0 or expression> } is invalid.

You cannot specify both an embedded document and a field within that embedded document in the same projection.

The following $project stage fails with a Path collision error because it attempts to project both the embedded contact document and the contact.address.country field:

{ $project: { contact: 1, "contact.address.country": 1 } }

The error occurs regardless of the order in which the parent document and embedded field are specified. The following $project fails with the same error:

{ $project: { "contact.address.country": 1, contact: 1 } }

When you use a $project stage it should typically be the last stage in your pipeline, used to specify which fields to return to the client.

Using a $project stage at the beginning or middle of a pipeline to reduce the number of fields passed to subsequent pipeline stages is unlikely to improve performance, as the database performs this optimization automatically.

MongoDB returns an error if the $project stage is passed an empty document.

For example, running the following pipeline produces an error:

db.myCollection.aggregate( [ {
$project: { }
} ] )

You cannot use an array index with the $project stage. For more information, see Array Indexes are Unsupported.

Consider a books collection with the following document:

{
"_id" : 1,
title: "abc123",
isbn: "0001122223334",
author: { last: "zzz", first: "aaa" },
copies: 5
}

The following $project stage includes only the _id, title, and the author fields in its output documents:

db.books.aggregate( [ { $project : { title : 1 , author : 1 } } ] )

The operation results in the following document:

{ "_id" : 1, "title" : "abc123", "author" : { "last" : "zzz", "first" : "aaa" } }

The _id field is always included by default. To exclude the _id field from the output documents of the $project stage, specify the exclusion of the _id field by setting it to 0 in the projection document.

Consider a books collection with the following document:

{
"_id" : 1,
title: "abc123",
isbn: "0001122223334",
author: { last: "zzz", first: "aaa" },
copies: 5
}

The following $project stage excludes the _id field but includes the title, and the author fields in its output documents:

db.books.aggregate( [ { $project : { _id: 0, title : 1 , author : 1 } } ] )

The operation results in the following document:

{ "title" : "abc123", "author" : { "last" : "zzz", "first" : "aaa" } }

Consider a books collection with the following document:

{
"_id" : 1,
title: "abc123",
isbn: "0001122223334",
author: { last: "zzz", first: "aaa" },
copies: 5,
lastModified: "2016-07-28"
}

The following $project stage excludes the lastModified field from the output:

db.books.aggregate( [ { $project : { "lastModified": 0 } } ] )

See also the $unset stage to exclude fields.

Consider a books collection with the following document:

{
"_id" : 1,
title: "abc123",
isbn: "0001122223334",
author: { last: "zzz", first: "aaa" },
copies: 5,
lastModified: "2016-07-28"
}

The following $project stage excludes the author.first and lastModified fields from the output:

db.books.aggregate( [ { $project : { "author.first" : 0, "lastModified" : 0 } } ] )

Alternatively, you can nest the exclusion specification in a document:

db.bookmarks.aggregate( [ { $project: { "author": { "first": 0}, "lastModified" : 0 } } ] )

Both specifications result in the same output:

{
"_id" : 1,
"title" : "abc123",
"isbn" : "0001122223334",
"author" : {
"last" : "zzz"
},
"copies" : 5,
}

See also the $unset stage to exclude fields.

You can use the variable REMOVE in aggregation expressions to conditionally suppress a field.

Consider a books collection with the following document:

{
"_id" : 1,
title: "abc123",
isbn: "0001122223334",
author: { last: "zzz", first: "aaa" },
copies: 5,
lastModified: "2016-07-28"
}
{
"_id" : 2,
title: "Baked Goods",
isbn: "9999999999999",
author: { last: "xyz", first: "abc", middle: "" },
copies: 2,
lastModified: "2017-07-21"
}
{
"_id" : 3,
title: "Ice Cream Cakes",
isbn: "8888888888888",
author: { last: "xyz", first: "abc", middle: "mmm" },
copies: 5,
lastModified: "2017-07-22"
}

The following $project stage uses the REMOVE variable to excludes the author.middle field only if it equals "":

db.books.aggregate( [
{
$project: {
title: 1,
"author.first": 1,
"author.last" : 1,
"author.middle": {
$cond: {
if: { $eq: [ "", "$author.middle" ] },
then: "$$REMOVE",
else: "$author.middle"
}
}
}
}
] )

The aggregation operation results in the following output:

{ "_id" : 1, "title" : "abc123", "author" : { "last" : "zzz", "first" : "aaa" } }
{ "_id" : 2, "title" : "Baked Goods", "author" : { "last" : "xyz", "first" : "abc" } }
{ "_id" : 3, "title" : "Ice Cream Cakes", "author" : { "last" : "xyz", "first" : "abc", "middle" : "mmm" } }

Tip

Comparison with $addFields

You can use either the $addFields or $project stage to remove document fields. The best approach depends on your pipeline and how much of the original document you want to retain.

To see an example using $$REMOVE in an $addFields stage, see Remove Fields.

Consider a bookmarks collection with the following documents:

{ _id: 1, user: "1234", stop: { title: "book1", author: "xyz", page: 32 } }
{ _id: 2, user: "7890", stop: [ { title: "book2", author: "abc", page: 5 }, { title: "book3", author: "ijk", page: 100 } ] }

To include only the title field in the embedded document in the stop field, you can use the dot notation:

db.bookmarks.aggregate( [ { $project: { "stop.title": 1 } } ] )

Or, you can nest the inclusion specification in a document:

db.bookmarks.aggregate( [ { $project: { stop: { title: 1 } } } ] )

Both specifications result in the following documents:

{ "_id" : 1, "stop" : { "title" : "book1" } }
{ "_id" : 2, "stop" : [ { "title" : "book2" }, { "title" : "book3" } ] }

Consider a books collection with the following document:

{
"_id" : 1,
title: "abc123",
isbn: "0001122223334",
author: { last: "zzz", first: "aaa" },
copies: 5
}

The following $project stage adds the new fields isbn, lastName, and copiesSold:

db.books.aggregate(
[
{
$project: {
title: 1,
isbn: {
prefix: { $substr: [ "$isbn", 0, 3 ] },
group: { $substr: [ "$isbn", 3, 2 ] },
publisher: { $substr: [ "$isbn", 5, 4 ] },
title: { $substr: [ "$isbn", 9, 3 ] },
checkDigit: { $substr: [ "$isbn", 12, 1] }
},
lastName: "$author.last",
copiesSold: "$copies"
}
}
]
)

The operation results in the following document:

{
"_id" : 1,
"title" : "abc123",
"isbn" : {
"prefix" : "000",
"group" : "11",
"publisher" : "2222",
"title" : "333",
"checkDigit" : "4"
},
"lastName" : "zzz",
"copiesSold" : 5
}

For example, if a collection includes the following document:

{ "_id" : ObjectId("55ad167f320c6be244eb3b95"), "x" : 1, "y" : 1 }

The following operation projects the fields x and y as elements in a new field myArray:

db.collection.aggregate( [ { $project: { myArray: [ "$x", "$y" ] } } ] )

The operation returns the following document:

{ "_id" : ObjectId("55ad167f320c6be244eb3b95"), "myArray" : [ 1, 1 ] }

If array specification includes fields that are non-existent in a document, the operation substitutes null as the value for that field.

For example, given the same document as above, the following operation projects the fields x, y, and a non-existing field $someField as elements in a new field myArray:

db.collection.aggregate( [ { $project: { myArray: [ "$x", "$y", "$someField" ] } } ] )

The operation returns the following document:

{ "_id" : ObjectId("55ad167f320c6be244eb3b95"), "myArray" : [ 1, 1, null ] }

You cannot use an array index with the $project stage. This section shows an example.

Create the following pizzas collection:

db.pizzas.insert( [
{ _id: 0, name: [ 'Pepperoni' ] },
] )

The following example returns the pizza:

db.pizzas.aggregate( [
{ $project: { x: '$name', _id: 0 } },
] )

The pizza is returned in the example output:

[ { x: [ 'Pepperoni' ] } ]

The following example uses an array index ($name.0) to attempt to return the pizza:

db.pizzas.aggregate( [
{ $project: { x: '$name.0', _id: 0 } },
] )

The pizza is not returned in the example output:

[ { x: [] } ]

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