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Aggregation Stages

$replaceRoot (aggregation)

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  • Definition
  • Behavior
  • Examples

Definition

$replaceRoot

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. The $replaceWith stage peforms the same action as the $replaceRoot stage, but the stages have different forms.

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 Expression Operators.

Behavior

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} ] } } }
])

Examples

$replaceRoot with an Embedded Document Field

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 }

$replaceRoot with a Document Nested in an Array

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 }

$replaceRoot with a newly created document

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" }

$replaceRoot with a New Document Created from $$ROOT and a Default Document

Create a collection named contacts with the following documents:

db.contacts.insertMany( [
   { "_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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$redact (aggregation)