$addFields (aggregation)
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Definition
$addFields
Adds new fields to documents.
$addFields
outputs documents that contain all existing fields from the input documents and newly added fields.The
$addFields
stage is equivalent to a$project
stage that explicitly specifies all existing fields in the input documents and adds the new fields.Note
You can also use the
$set
stage, which is an alias for$addFields
.
Compatibility
You can use $addFields
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
The stage has the following syntax:
{ $addFields: { <newField>: <expression>, ... } }
Specify the name of each field to add and set its value to an aggregation expression or an empty object. For more information on expressions, see Expression Operators.
Important
If the name of the new field is the same as an existing field name
(including _id
), $addFields
overwrites the existing value
of that field with the value of the specified expression.
Behavior
$addFields
appends new fields to existing documents. You can include one or more$addFields
stages in an aggregation operation.$addFields
accepts the embedding of objects where you can set a value to an aggregation expression or to an empty object. For example, the following nested objects are accepted:{$addFields: { a: { b: { } } } } To add a field or fields to embedded documents (including documents in arrays) use the dot notation. See example.
To add an element to an existing array field with
$addFields
, use with$concatArrays
. See example.
Examples
Using Two $addFields
Stages
A collection called scores
contains the following documents:
db.scores.insertMany( [ { _id: 1, student: "Maya", homework: [ 10, 5, 10 ], quiz: [ 10, 8 ], extraCredit: 0 }, { _id: 2, student: "Ryan", homework: [ 5, 6, 5 ], quiz: [ 8, 8 ], extraCredit: 8 } ] )
The following operation uses two $addFields
stages to
include three new fields in the output documents:
db.scores.aggregate( [ { $addFields: { totalHomework: { $sum: "$homework" } , totalQuiz: { $sum: "$quiz" } } }, { $addFields: { totalScore: { $add: [ "$totalHomework", "$totalQuiz", "$extraCredit" ] } } } ] )
The operation returns the following documents:
[ { _id: 1, student: "Maya", homework: [ 10, 5, 10 ], quiz: [ 10, 8 ], extraCredit: 0, totalHomework: 25, totalQuiz: 18, totalScore: 43 }, { _id: 2, student: "Ryan", homework: [ 5, 6, 5 ], quiz: [ 8, 8 ], extraCredit: 8, totalHomework: 16, totalQuiz: 16, totalScore: 40 } ]
Adding Fields to an Embedded Document
Use dot notation to add new fields to embedded documents.
For example, create a collection called vehicles
with
the following documents:
db.vehicles.insertMany( [ { _id: 1, type: "car", specs: { doors: 4, wheels: 4 } }, { _id: 2, type: "motorcycle", specs: { doors: 0, wheels: 2 } }, { _id: 3, type: "jet ski" } ] )
The following aggregation operation adds a new field fuel_type
to
the embedded document specs
.
db.vehicles.aggregate( [ { $addFields: { "specs.fuel_type": "unleaded" } } ] )
The operation returns the following results:
[ { _id: 1, type: "car", specs: { doors: 4, wheels: 4, fuel_type: "unleaded" } }, { _id: 2, type: "motorcycle", specs: { doors: 0, wheels: 2, fuel_type: "unleaded" } }, { _id: 3, type: "jet ski", specs: { fuel_type: "unleaded" } } ]
Overwriting an existing field
Specifying an existing field name in an $addFields
operation
causes the original field to be replaced.
A collection called animals
contains the following document:
db.animals.insertOne( { _id: 1, dogs: 10, cats: 15 } )
The following $addFields
operation specifies the cats
field.
db.animals.aggregate( [ { $addFields: { cats: 20 } } ] )
The operation returns the following document:
[ { _id: 1, dogs: 10, cats: 20 } ]
It is possible to replace one field with another. In the following
example the item
field substitutes for the _id
field.
A collection called fruit
contains the following documents:
db.fruit.insertMany( [ { _id: 1, item: "tangerine", type: "citrus" }, { _id: 2, item: "lemon", type: "citrus" }, { _id: 3, item: "grapefruit", type: "citrus" } ] )
The following aggregation operation uses $addFields
to replace
the _id
field of each document with the value of the item
field, and replaces the item
field with a static value.
db.fruit.aggregate( [ { $addFields: { _id : "$item", item: "fruit" } } ] )
The operation returns the following:
[ { _id: "tangerine", item: "fruit", type: "citrus" }, { _id: "lemon", item: "fruit", type: "citrus" }, { _id: "grapefruit", item: "fruit", type: "citrus" } ]
Add Element to an Array
Create a sample scores
collection with the following:
db.scores.insertMany( [ { _id: 1, student: "Maya", homework: [ 10, 5, 10 ], quiz: [ 10, 8 ], extraCredit: 0 }, { _id: 2, student: "Ryan", homework: [ 5, 6, 5 ], quiz: [ 8, 8 ], extraCredit: 8 } ] )
You can use $addFields
with a $concatArrays
expression to add an element to an existing array field. For example,
the following operation uses $addFields
to replace the
homework
field with a new array whose elements are the current
homework
array concatenated with another array containing a new
score [ 7 ]
.
db.scores.aggregate( [ { $match: { _id: 1 } }, { $addFields: { homework: { $concatArrays: [ "$homework", [ 7 ] ] } } } ] )
The operation returns the following:
[ { _id: 1, student: "Maya", homework: [ 10, 5, 10, 7 ], quiz: [ 10, 8 ], extraCredit: 0 } ]
Remove Fields
You can use $addFields
with the $$REMOVE
variable to remove document fields.
For example, create a labReadings
collection:
db.labReadings.insertMany( [ { date: ISODate("2024-10-09"), temperature: 80 }, { date: null, temperature: 83 }, { date: ISODate("2024-12-09"), temperature: 85 } ] )
To remove the date
field from the labReadings
documents, use
$addFields
with the $$REMOVE
variable:
db.labReadings.aggregate( [ { $addFields: { date: "$$REMOVE" } } ] )
Output:
[ { _id: ObjectId('671285306fd2c3b24f2e7eaa'), temperature: 80 }, { _id: ObjectId('671285306fd2c3b24f2e7eab'), temperature: 83 }, { _id: ObjectId('671285306fd2c3b24f2e7eac'), temperature: 85 } ]
You can also use $$REMOVE
to conditionally remove fields. For
example, the following aggregation removes the date
field from
documents where date
is null
:
db.labReadings.aggregate( [ { $addFields: { date: { $ifNull: [ "$date", "$$REMOVE" ] } } } ] )
Output:
[ { _id: ObjectId('671285306fd2c3b24f2e7eaa'), date: ISODate('2024-10-09T00:00:00.000Z'), temperature: 80 }, { _id: ObjectId('671285306fd2c3b24f2e7eab'), temperature: 83 }, { _id: ObjectId('671285306fd2c3b24f2e7eac'), date: ISODate('2024-12-09T00:00:00.000Z'), temperature: 85 } ]
Tip
Comparison with $project
You can use either the $addFields
or $project
stage to remove
document fields. The best approach depends on your pipeline and how much
of the original document you want to retain.
For an example using $$REMOVE
in a $project
stage, see
Conditionally Exclude Fields.