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$replaceRoot (aggregation)

$replaceRoot

New in version 3.4.

Replaces the input document with the specified document. The operation replaces all existing fields in the input document, including the _id field. You can promote an existing embedded document to the top level, or create a new document for promotion (see example).

Note

Starting in version 4.2, MongoDB adds a new aggregation pipeline stage $replaceWith that is an alias for $replaceRoot.

The $replaceRoot stage has the following form:

{ $replaceRoot: { newRoot: <replacementDocument> } }

The replacement document can be any valid expression that resolves to a document. The stage errors and fails if <replacementDocument> is not a document. For more information on expressions, see Expressions.

If the <replacementDocument> is not a document, $replaceRoot errors and fails.

If the <replacementDocument> resolves to a missing document (i.e. the document does not exist), $replaceRoot errors and fails. For example, create a collection with the following documents:

db.collection.insertMany([
{ "_id": 1, "name" : { "first" : "John", "last" : "Backus" } },
{ "_id": 2, "name" : { "first" : "John", "last" : "McCarthy" } },
{ "_id": 3, "name": { "first" : "Grace", "last" : "Hopper" } },
{ "_id": 4, "firstname": "Ole-Johan", "lastname" : "Dahl" },
])

Then the following $replaceRoot operation fails because one of the documents does not have the name field:

db.collection.aggregate([
{ $replaceRoot: { newRoot: "$name" } }
])

To avoid the error, you can use $mergeObjects to merge the name document into some default document; for example:

db.collection.aggregate([
{ $replaceRoot: { newRoot: { $mergeObjects: [ { _id: "$_id", first: "", last: "" }, "$name" ] } } }
])

Alternatively, you can skip the documents that are missing the name field by including a $match stage to check for existence of the document field before passing documents to the $replaceRoot stage:

db.collection.aggregate([
{ $match: { name : { $exists: true, $not: { $type: "array" }, $type: "object" } } },
{ $replaceRoot: { newRoot: "$name" } }
])

Or, you can use $ifNull expression to specify some other document to be root; for example:

db.collection.aggregate([
{ $replaceRoot: { newRoot: { $ifNull: [ "$name", { _id: "$_id", missingName: true} ] } } }
])

A collection named people contains the following documents:

{ "_id" : 1, "name" : "Arlene", "age" : 34, "pets" : { "dogs" : 2, "cats" : 1 } }
{ "_id" : 2, "name" : "Sam", "age" : 41, "pets" : { "cats" : 1, "fish" : 3 } }
{ "_id" : 3, "name" : "Maria", "age" : 25 }

The following operation uses the $replaceRoot stage to replace each input document with the result of a $mergeObjects operation. The $mergeObjects expression merges the specified default document with the pets document.

db.people.aggregate( [
{ $replaceRoot: { newRoot: { $mergeObjects: [ { dogs: 0, cats: 0, birds: 0, fish: 0 }, "$pets" ] }} }
] )

The operation returns the following results:

{ "dogs" : 2, "cats" : 1, "birds" : 0, "fish" : 0 }
{ "dogs" : 0, "cats" : 1, "birds" : 0, "fish" : 3 }
{ "dogs" : 0, "cats" : 0, "birds" : 0, "fish" : 0 }

A collection named students contains the following documents:

db.students.insertMany([
{
"_id" : 1,
"grades" : [
{ "test": 1, "grade" : 80, "mean" : 75, "std" : 6 },
{ "test": 2, "grade" : 85, "mean" : 90, "std" : 4 },
{ "test": 3, "grade" : 95, "mean" : 85, "std" : 6 }
]
},
{
"_id" : 2,
"grades" : [
{ "test": 1, "grade" : 90, "mean" : 75, "std" : 6 },
{ "test": 2, "grade" : 87, "mean" : 90, "std" : 3 },
{ "test": 3, "grade" : 91, "mean" : 85, "std" : 4 }
]
}
])

The following operation promotes the embedded document(s) with the grade field greater than or equal to 90 to the top level:

db.students.aggregate( [
{ $unwind: "$grades" },
{ $match: { "grades.grade" : { $gte: 90 } } },
{ $replaceRoot: { newRoot: "$grades" } }
] )

The operation returns the following results:

{ "test" : 3, "grade" : 95, "mean" : 85, "std" : 6 }
{ "test" : 1, "grade" : 90, "mean" : 75, "std" : 6 }
{ "test" : 3, "grade" : 91, "mean" : 85, "std" : 4 }

You can also create new documents as part of the $replaceRoot stage and use them to replace all the other fields.

A collection named contacts contains the following documents:

{ "_id" : 1, "first_name" : "Gary", "last_name" : "Sheffield", "city" : "New York" }
{ "_id" : 2, "first_name" : "Nancy", "last_name" : "Walker", "city" : "Anaheim" }
{ "_id" : 3, "first_name" : "Peter", "last_name" : "Sumner", "city" : "Toledo" }

The following operation creates a new document out of the first_name and last_name fields.

db.contacts.aggregate( [
{
$replaceRoot: {
newRoot: {
full_name: {
$concat : [ "$first_name", " ", "$last_name" ]
}
}
}
}
] )

The operation returns the following results:

{ "full_name" : "Gary Sheffield" }
{ "full_name" : "Nancy Walker" }
{ "full_name" : "Peter Sumner" }

Create a collection named contacts with the following documents:

db.contacts.insert([
{ "_id" : 1, name: "Fred", email: "fred@example.net" },
{ "_id" : 2, name: "Frank N. Stine", cell: "012-345-9999" },
{ "_id" : 3, name: "Gren Dell", home: "987-654-3210", email: "beo@example.net" }
]);

The following operation uses $replaceRoot with $mergeObjects to output current documents with default values for missing fields:

db.contacts.aggregate([
{ $replaceRoot: { newRoot: { $mergeObjects: [ { _id: "", name: "", email: "", cell: "", home: "" }, "$$ROOT" ] } } }
])

The aggregation returns the following documents:

{ "_id" : 1, "name" : "Fred", "email" : "fred@example.net", "cell" : "", "home" : "" }
{ "_id" : 2, "name" : "Frank N. Stine", "email" : "", "cell" : "012-345-9999", "home" : "" }
{ "_id" : 3, "name" : "Gren Dell", "email" : "beo@example.net", "cell" : "", "home" : "987-654-3210" }
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