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$unsetField (aggregation)

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  • Definition
  • Syntax
  • Behavior
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$unsetField

New in version 5.0.

Removes a specified field in a document.

You can use $unsetField to remove fields with names that contain periods (.) or that start with dollar signs ($).

$unsetField is an alias for $setField using $$REMOVE to remove fields.

$unsetField has the following syntax:

{
$unsetField: {
field: <String>,
input: <Object>,
}
}

You must provide the following fields:

Field
Type
Description
field
String
Field in the input object that you want to add, update, or remove. field can be any valid expression that resolves to a string constant.
input
Object
Document that contains the field that you want to add or update. input must resolve to an object, missing, null, or undefined.
  • If input evaluates to missing, undefined, or null, $unsetField returns null and does not update input.

  • If input evaluates to anything other than an object, missing, undefined, or null, $unsetField returns an error.

  • If field resolves to anything other than a string constant, $unsetField returns an error.

  • If field doesn't exist in input, $unsetField adds it.

  • $unsetField doesn't implicitly traverse objects or arrays. For example, $unsetField evaluates a field value of "a.b.c" as a top-level field "a.b.c" instead of as a nested field, { "a": { "b": { "c": } } }.

Consider the inventory collection:

db.inventory.insertMany( [
{ _id: 1, item: "sweatshirt", qty: 300, "price.usd": 45.99 },
{ _id: 2, item: "winter coat", qty: 200, "price.usd": 499.99 },
{ _id: 3, item: "sun dress", qty: 250, "price.usd": 199.99 },
{ _id: 4, item: "leather boots", qty: 300, "price.usd": 249.99 },
{ _id: 5, item: "bow tie", qty: 180, "price.usd": 9.99 }
] )

Use the $replaceWith pipeline stage and the $unsetField operator to remove the "price.usd" field from each document:

db.inventory.aggregate( [
{ $replaceWith: {
$unsetField: {
field: "price.usd",
input: "$$ROOT"
} } }
] )

The operation returns the following results:

[
{ _id: 1, item: 'sweatshirt', qty: 300 },
{ _id: 2, item: 'winter coat', qty: 200 },
{ _id: 3, item: 'sun dress', qty: 250 },
{ _id: 4, item: 'leather boots', qty: 300 },
{ _id: 5, item: 'bow tie', qty: 180 }
]

Consider the inventory collection:

db.inventory.insertMany( [
{ _id: 1, item: "sweatshirt", qty: 300, "$price": 45.99 },
{ _id: 2, item: "winter coat", qty: 200, "$price": 499.99 },
{ _id: 3, item: "sun dress", qty: 250, "$price": 199.99 },
{ _id: 4, item: "leather boots", qty: 300, "$price": 249.99 },
{ _id: 5, item: "bow tie", qty: 180, "$price": 9.99 }
] )

Use the $replaceWith pipeline stage with the $unsetField and $literal operators to remove the "$price" field from each document:

db.inventory.aggregate( [
{ $replaceWith: {
$unsetField: {
field: { $literal: "$price" },
input: "$$ROOT"
} } }
] )

The operation returns the following results:

[
{ _id: 1, item: 'sweatshirt', qty: 300 },
{ _id: 2, item: 'winter coat', qty: 200 },
{ _id: 3, item: 'sun dress', qty: 250 },
{ _id: 4, item: 'leather boots', qty: 300 },
{ _id: 5, item: 'bow tie', qty: 180 }
]

Consider the inventory collection:

db.inventory.insertMany( [
{ _id: 1, item: "sweatshirt", qty: 300, "price": {"usd":45.99, "euro": 38.77 } },
{ _id: 2, item: "winter coat", qty: 200, "price": { "usd": 499.99, "euro": 420.51 } },
{ _id: 3, item: "sun dress", qty: 250, "price": { "usd": 199.99, "euro": 167.70 } },
{ _id: 4, item: "leather boots", qty: 300, "price": { "usd": 249.99, "euro": 210.68 } },
{ _id: 5, item: "bow tie", qty: 180, "price": { "usd": 9.99, "euro": 8.42 } }
] )

The "price" field contains a document with two subfields, "usd" and "euro". You cannot use "price.euro" to identify and remove "euro" because MongoDB parses "price.euro" as a top level field name that happens to contain a period (.).

Use the $replaceWith pipeline stage with $setField and a nested $unsetField operation to remove the "euro" field:

db.inventory.aggregate( [
{ $replaceWith: {
$setField: {
field: "price",
input: "$$ROOT",
value: {
$unsetField: {
field: "euro",
input: { $getField: "price" }
} } } } }
] )

The operation returns the following results:

[
{ _id: 1, item: "sweatshirt", qty: 300, price: { usd: 45.99 } },
{ _id: 2, item: "winter coat", qty: 200, price: { usd: 499.99 } },
{ _id: 3, item: "sun dress", qty: 250, price: { usd: 199.99 } },
{ _id: 4, item: "leather boots", qty: 300, price: { usd: 249.99 } },
{ _id: 5, item: "bow tie", qty: 180, price: { usd: 9.99 } }
]

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