$unsetField (aggregation)
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Definition
$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$$REMOVE
to remove fields.
Syntax
$unsetField
has the following syntax:
{ $unsetField: { field: <String>, input: <Object>, } }
You must provide the following fields:
Field | Type | Description |
---|---|---|
field | String | Field in the input object that you want to remove. field
can be any valid expression that
resolves to a string constant. |
input | Object | Document that contains the field that you want to remove.
input must resolve to an object, missing , null , or
undefined . |
Behavior
If
input
evaluates tomissing
,undefined
, ornull
,$unsetField
returnsnull
and does not updateinput
.If
input
evaluates to anything other than an object,missing
,undefined
, ornull
,$unsetField
returns an error.If
field
resolves to anything other than a string constant,$unsetField
returns an error.$unsetField
doesn't implicitly traverse objects or arrays. For example,$unsetField
evaluates afield
value of"a.b.c"
as a top-level field"a.b.c"
instead of as a nested field,{ "a": { "b": { "c": } } }
.
Examples
Remove Fields that Contain Periods (.
)
Consider the inventory collection:
db.inventory.insertMany( [ { _id: 1, item: "sweatshirt", qty: 300, "price.usd": 45.99 }, { _id: 2, item: "winter coat", qty: 200, "price.usd": 499.99 }, { _id: 3, item: "sun dress", qty: 250, "price.usd": 199.99 }, { _id: 4, item: "leather boots", qty: 300, "price.usd": 249.99 }, { _id: 5, item: "bow tie", qty: 180, "price.usd": 9.99 } ] )
Use the $replaceWith
pipeline stage and the
$unsetField
operator to remove the "price.usd"
field
from each document:
db.inventory.aggregate( [ { $replaceWith: { $unsetField: { field: "price.usd", input: "$$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 } ]
Remove Fields that Start with a Dollar Sign ($
)
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: "$$ROOT" } } } ] )
The operation returns the following results:
[ { _id: 1, item: 'sweatshirt', qty: 300 }, { _id: 2, item: 'winter coat', qty: 200 }, { _id: 3, item: 'sun dress', qty: 250 }, { _id: 4, item: 'leather boots', qty: 300 }, { _id: 5, item: 'bow tie', qty: 180 } ]
Remove A Subfield
Consider the inventory collection:
db.inventory.insertMany( [ { _id: 1, item: "sweatshirt", qty: 300, "price": {"usd":45.99, "euro": 38.77 } }, { _id: 2, item: "winter coat", qty: 200, "price": { "usd": 499.99, "euro": 420.51 } }, { _id: 3, item: "sun dress", qty: 250, "price": { "usd": 199.99, "euro": 167.70 } }, { _id: 4, item: "leather boots", qty: 300, "price": { "usd": 249.99, "euro": 210.68 } }, { _id: 5, item: "bow tie", qty: 180, "price": { "usd": 9.99, "euro": 8.42 } } ] )
The "price"
field contains a document with two subfields, "usd"
and "euro"
. You cannot use "price.euro"
to identify and remove
"euro"
because MongoDB parses "price.euro"
as a top level field
name that happens to contain a period (.
).
Use the $replaceWith
pipeline stage with
$setField
and a nested $unsetField
operation to remove the "euro"
field:
db.inventory.aggregate( [ { $replaceWith: { $setField: { field: "price", input: "$$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 } } ]