$regexFind (aggregation)
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Definition
Syntax
The $regexFind
operator has the following syntax:
{ $regexFind: { input: <expression> , regex: <expression>, options: <expression> } }
Operator Fields
Field | Description | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
The string on which you wish to apply the regex pattern. Can be a string or any valid expression that resolves to a string. | |||||||||||
The regex pattern to apply. Can be any valid expression that resolves to either a string or regex
pattern
Alternatively, you can also specify the regex options with the
options field. To specify the You cannot specify options in both the | |||||||||||
Optional. The following You cannot specify options in both the
|
Returns
If the operator does not find a match, the result of the operator is a
null
.
If the operator finds a match, the result of the operator is a document that contains:
the first matching string in the input,
the code point index (not byte index) of the matching string in the input, and
An array of the strings that corresponds to the groups captured by the matching string. Capturing groups are specified with unescaped parenthesis
()
in the regex pattern.
{ "match" : <string>, "idx" : <num>, "captures" : <array of strings> }
Behavior
PCRE Library
Starting in version 6.1, MongoDB uses the PCRE2 (Perl Compatible Regular Expressions) library to implement regular expression pattern matching. To learn more about PCRE2, see the PCRE Documentation.
$regexFind
and Collation
$regexFind
ignores the collation specified for the
collection, db.collection.aggregate()
, and the index, if used.
For example, the create a sample collection with collation strength
1
(i.e. compare base character only and ignore other differences
such as case and diacritics):
db.createCollection( "myColl", { collation: { locale: "fr", strength: 1 } } )
Insert the following documents:
db.myColl.insertMany([ { _id: 1, category: "café" }, { _id: 2, category: "cafe" }, { _id: 3, category: "cafE" } ])
Using the collection's collation, the following operation performs a case-insensitive and diacritic-insensitive match:
db.myColl.aggregate( [ { $match: { category: "cafe" } } ] )
The operation returns the following 3 documents:
{ "_id" : 1, "category" : "café" } { "_id" : 2, "category" : "cafe" } { "_id" : 3, "category" : "cafE" }
However, the aggregation expression $regexFind
ignores
collation; that is, the following regular expression pattern matching examples
are case-sensitive and diacritic sensitive:
db.myColl.aggregate( [ { $addFields: { resultObject: { $regexFind: { input: "$category", regex: /cafe/ } } } } ] ) db.myColl.aggregate( [ { $addFields: { resultObject: { $regexFind: { input: "$category", regex: /cafe/ } } } } ], { collation: { locale: "fr", strength: 1 } } // Ignored in the $regexFind )
Both operations return the following:
{ "_id" : 1, "category" : "café", "resultObject" : null } { "_id" : 2, "category" : "cafe", "resultObject" : { "match" : "cafe", "idx" : 0, "captures" : [ ] } } { "_id" : 3, "category" : "cafE", "resultObject" : null }
To perform a case-insensitive regex pattern matching, use the
i
Option instead. See
i
Option for an example.
captures
Output Behavior
If your regex pattern contains capture groups
and the pattern finds a match in the input, the
captures
array in the results corresponds to the groups captured by
the matching string. Capture groups are specified with unescaped
parentheses ()
in the regex pattern. The
length of the captures
array equals the number of capture groups in
the pattern and the order of the array matches the order in which the
capture groups appear.
Create a sample collection named contacts
with the following
documents:
db.contacts.insertMany([ { "_id": 1, "fname": "Carol", "lname": "Smith", "phone": "718-555-0113" }, { "_id": 2, "fname": "Daryl", "lname": "Doe", "phone": "212-555-8832" }, { "_id": 3, "fname": "Polly", "lname": "Andrews", "phone": "208-555-1932" }, { "_id": 4, "fname": "Colleen", "lname": "Duncan", "phone": "775-555-0187" }, { "_id": 5, "fname": "Luna", "lname": "Clarke", "phone": "917-555-4414" } ])
The following pipeline applies the regex
pattern /(C(ar)*)ol/
to the fname
field:
db.contacts.aggregate([ { $project: { returnObject: { $regexFind: { input: "$fname", regex: /(C(ar)*)ol/ } } } } ])
The regex pattern finds a match with fname
values Carol
and Colleen
:
{ "_id" : 1, "returnObject" : { "match" : "Carol", "idx" : 0, "captures" : [ "Car", "ar" ] } } { "_id" : 2, "returnObject" : null } { "_id" : 3, "returnObject" : null } { "_id" : 4, "returnObject" : { "match" : "Col", "idx" : 0, "captures" : [ "C", null ] } } { "_id" : 5, "returnObject" : null }
The pattern contains the capture group (C(ar)*)
which contains the
nested group (ar)
. The elements in the captures
array correspond
to the two capture groups. If a matching document is not captured by a
group (e.g. Colleen
and the group (ar)
),
$regexFind
replaces the group with a null placeholder.
As shown in the previous example, the captures
array contains an
element for each capture group (using null
for non-captures).
Consider the following example which searches for phone numbers with
New York City area codes by applying a logical or
of capture
groups to the phone
field. Each group represents a New York City
area code:
db.contacts.aggregate([ { $project: { nycContacts: { $regexFind: { input: "$phone", regex: /^(718).*|^(212).*|^(917).*/ } } } } ])
For documents which are matched by the regex
pattern, the captures
array includes the matching capture group
and replaces any non-capturing groups with null
:
{ "_id" : 1, "nycContacts" : { "match" : "718-555-0113", "idx" : 0, "captures" : [ "718", null, null ] } } { "_id" : 2, "nycContacts" : { "match" : "212-555-8832", "idx" : 0, "captures" : [ null, "212", null ] } } { "_id" : 3, "nycContacts" : null } { "_id" : 4, "nycContacts" : null } { "_id" : 5, "nycContacts" : { "match" : "917-555-4414", "idx" : 0, "captures" : [ null, null, "917" ] } }
Examples
$regexFind
and Its Options
To illustrate the behavior of the $regexFind
operator as
discussed in this example, create a sample collection products
with
the following documents:
db.products.insertMany([ { _id: 1, description: "Single LINE description." }, { _id: 2, description: "First lines\nsecond line" }, { _id: 3, description: "Many spaces before line" }, { _id: 4, description: "Multiple\nline descriptions" }, { _id: 5, description: "anchors, links and hyperlinks" }, { _id: 6, description: "métier work vocation" } ])
By default, $regexFind
performs a case-sensitive match.
For example, the following aggregation performs a case-sensitive
$regexFind
on the description
field. The regex
pattern /line/
does not specify any grouping:
db.products.aggregate([ { $addFields: { returnObject: { $regexFind: { input: "$description", regex: /line/ } } } } ])
The operation returns the following:
{ "_id" : 1, "description" : "Single LINE description.", "returnObject" : null } { "_id" : 2, "description" : "First lines\nsecond line", "returnObject" : { "match" : "line", "idx" : 6, "captures" : [ ] } } { "_id" : 3, "description" : "Many spaces before line", "returnObject" : { "match" : "line", "idx" : 23, "captures" : [ ] } } { "_id" : 4, "description" : "Multiple\nline descriptions", "returnObject" : { "match" : "line", "idx" : 9, "captures" : [ ] } } { "_id" : 5, "description" : "anchors, links and hyperlinks", "returnObject" : null } { "_id" : 6, "description" : "métier work vocation", "returnObject" : null }
The following regex pattern /lin(e|k)/
specifies a grouping
(e|k)
in the pattern:
db.products.aggregate([ { $addFields: { returnObject: { $regexFind: { input: "$description", regex: /lin(e|k)/ } } } } ])
The operation returns the following:
{ "_id" : 1, "description" : "Single LINE description.", "returnObject" : null } { "_id" : 2, "description" : "First lines\nsecond line", "returnObject" : { "match" : "line", "idx" : 6, "captures" : [ "e" ] } } { "_id" : 3, "description" : "Many spaces before line", "returnObject" : { "match" : "line", "idx" : 23, "captures" : [ "e" ] } } { "_id" : 4, "description" : "Multiple\nline descriptions", "returnObject" : { "match" : "line", "idx" : 9, "captures" : [ "e" ] } } { "_id" : 5, "description" : "anchors, links and hyperlinks", "returnObject" : { "match" : "link", "idx" : 9, "captures" : [ "k" ] } } { "_id" : 6, "description" : "métier work vocation", "returnObject" : null }
In the return option, the idx
field is the code point index and not the byte
index. To illustrate, consider the following example that uses the
regex pattern /tier/
:
db.products.aggregate([ { $addFields: { returnObject: { $regexFind: { input: "$description", regex: /tier/ } } } } ])
The operation returns the following where only the last record
matches the pattern and the returned idx
is 2
(instead of 3
if using a byte index)
{ "_id" : 1, "description" : "Single LINE description.", "returnObject" : null } { "_id" : 2, "description" : "First lines\nsecond line", "returnObject" : null } { "_id" : 3, "description" : "Many spaces before line", "returnObject" : null } { "_id" : 4, "description" : "Multiple\nline descriptions", "returnObject" : null } { "_id" : 5, "description" : "anchors, links and hyperlinks", "returnObject" : null } { "_id" : 6, "description" : "métier work vocation", "returnObject" : { "match" : "tier", "idx" : 2, "captures" : [ ] } }
i
Option
Note
You cannot specify options in both the regex
and the
options
field.
To perform case-insensitive pattern matching, include the i option as part of the regex field or in the options field:
// Specify i as part of the regex field { $regexFind: { input: "$description", regex: /line/i } } // Specify i in the options field { $regexFind: { input: "$description", regex: /line/, options: "i" } } { $regexFind: { input: "$description", regex: "line", options: "i" } }
For example, the following aggregation performs a case-insensitive
$regexFind
on the description
field. The regex
pattern /line/
does not specify any grouping:
db.products.aggregate([ { $addFields: { returnObject: { $regexFind: { input: "$description", regex: /line/i } } } } ])
The operation returns the following documents:
{ "_id" : 1, "description" : "Single LINE description.", "returnObject" : { "match" : "LINE", "idx" : 7, "captures" : [ ] } } { "_id" : 2, "description" : "First lines\nsecond line", "returnObject" : { "match" : "line", "idx" : 6, "captures" : [ ] } } { "_id" : 3, "description" : "Many spaces before line", "returnObject" : { "match" : "line", "idx" : 23, "captures" : [ ] } } { "_id" : 4, "description" : "Multiple\nline descriptions", "returnObject" : { "match" : "line", "idx" : 9, "captures" : [ ] } } { "_id" : 5, "description" : "anchors, links and hyperlinks", "returnObject" : null } { "_id" : 6, "description" : "métier work vocation", "returnObject" : null }
m
Option
Note
You cannot specify options in both the regex
and the
options
field.
To match the specified anchors (e.g. ^
, $
) for each line of a
multiline string, include the m option as
part of the regex field or in the
options field:
// Specify m as part of the regex field { $regexFind: { input: "$description", regex: /line/m } } // Specify m in the options field { $regexFind: { input: "$description", regex: /line/, options: "m" } } { $regexFind: { input: "$description", regex: "line", options: "m" } }
The following example includes both the i
and the m
options to
match lines starting with either the letter s
or S
for
multiline strings:
db.products.aggregate([ { $addFields: { returnObject: { $regexFind: { input: "$description", regex: /^s/im } } } } ])
The operation returns the following:
{ "_id" : 1, "description" : "Single LINE description.", "returnObject" : { "match" : "S", "idx" : 0, "captures" : [ ] } } { "_id" : 2, "description" : "First lines\nsecond line", "returnObject" : { "match" : "s", "idx" : 12, "captures" : [ ] } } { "_id" : 3, "description" : "Many spaces before line", "returnObject" : null } { "_id" : 4, "description" : "Multiple\nline descriptions", "returnObject" : null } { "_id" : 5, "description" : "anchors, links and hyperlinks", "returnObject" : null } { "_id" : 6, "description" : "métier work vocation", "returnObject" : null }
x
Option
Note
You cannot specify options in both the regex
and the
options
field.
To ignore all unescaped white space characters and comments (denoted by
the un-escaped hash #
character and the next new-line character) in
the pattern, include the s option in the
options field:
// Specify x in the options field { $regexFind: { input: "$description", regex: /line/, options: "x" } } { $regexFind: { input: "$description", regex: "line", options: "x" } }
The following example includes the x
option to skip unescaped white
spaces and comments:
db.products.aggregate([ { $addFields: { returnObject: { $regexFind: { input: "$description", regex: /lin(e|k) # matches line or link/, options:"x" } } } } ])
The operation returns the following:
{ "_id" : 1, "description" : "Single LINE description.", "returnObject" : null } { "_id" : 2, "description" : "First lines\nsecond line", "returnObject" : { "match" : "line", "idx" : 6, "captures" : [ "e" ] } } { "_id" : 3, "description" : "Many spaces before line", "returnObject" : { "match" : "line", "idx" : 23, "captures" : [ "e" ] } } { "_id" : 4, "description" : "Multiple\nline descriptions", "returnObject" : { "match" : "line", "idx" : 9, "captures" : [ "e" ] } } { "_id" : 5, "description" : "anchors, links and hyperlinks", "returnObject" : { "match" : "link", "idx" : 9, "captures" : [ "k" ] } } { "_id" : 6, "description" : "métier work vocation", "returnObject" : null }
s
Option
Note
You cannot specify options in both the regex
and the
options
field.
To allow the dot character (i.e. .
) in the pattern to match all
characters including the new line character, include the s option in the options
field:
// Specify s in the options field { $regexFind: { input: "$description", regex: /m.*line/, options: "s" } } { $regexFind: { input: "$description", regex: "m.*line", options: "s" } }
The following example includes the s
option to allow the dot
character (i.e. .) to match all characters including new line as well
as the i
option to perform a case-insensitive match:
db.products.aggregate([ { $addFields: { returnObject: { $regexFind: { input: "$description", regex:/m.*line/, options: "si" } } } } ])
The operation returns the following:
{ "_id" : 1, "description" : "Single LINE description.", "returnObject" : null } { "_id" : 2, "description" : "First lines\nsecond line", "returnObject" : null } { "_id" : 3, "description" : "Many spaces before line", "returnObject" : { "match" : "Many spaces before line", "idx" : 0, "captures" : [ ] } } { "_id" : 4, "description" : "Multiple\nline descriptions", "returnObject" : { "match" : "Multiple\nline", "idx" : 0, "captures" : [ ] } } { "_id" : 5, "description" : "anchors, links and hyperlinks", "returnObject" : null } { "_id" : 6, "description" : "métier work vocation", "returnObject" : null }
Use $regexFind
to Parse Email from String
Create a sample collection feedback
with the following documents:
db.feedback.insertMany([ { "_id" : 1, comment: "Hi, I'm just reading about MongoDB -- aunt.arc.tica@example.com" }, { "_id" : 2, comment: "I wanted to concatenate a string" }, { "_id" : 3, comment: "How do I convert a date to string? cam@mongodb.com" }, { "_id" : 4, comment: "It's just me. I'm testing. fred@MongoDB.com" } ])
The following aggregation uses the $regexFind
to extract
the email from the comment
field (case insensitive).
db.feedback.aggregate( [ { $addFields: { "email": { $regexFind: { input: "$comment", regex: /[a-z0-9_.+-]+@[a-z0-9_.+-]+\.[a-z0-9_.+-]+/i } } } }, { $set: { email: "$email.match"} } ] )
- First Stage
The stage uses the
$addFields
stage to add a new fieldemail
to the document. The new field contains the result of performing the$regexFind
on thecomment
field:{ "_id" : 1, "comment" : "Hi, I'm just reading about MongoDB -- aunt.arc.tica@example.com", "email" : { "match" : "aunt.arc.tica@example.com", "idx" : 38, "captures" : [ ] } } { "_id" : 2, "comment" : "I wanted to concatenate a string", "email" : null } { "_id" : 3, "comment" : "I can't find how to convert a date to string. cam@mongodb.com", "email" : { "match" : "cam@mongodb.com", "idx" : 46, "captures" : [ ] } } { "_id" : 4, "comment" : "It's just me. I'm testing. fred@MongoDB.com", "email" : { "match" : "fred@MongoDB.com", "idx" : 28, "captures" : [ ] } } - Second Stage
The stage use the
$set
stage to reset theemail
to the current"$email.match"
value. If the current value ofemail
is null, the new value ofemail
is set to null.{ "_id" : 1, "comment" : "Hi, I'm just reading about MongoDB -- aunt.arc.tica@example.com", "email" : "aunt.arc.tica@example.com" } { "_id" : 2, "comment" : "I wanted to concatenate a string" } { "_id" : 3, "comment" : "I can't find how to convert a date to string. cam@mongodb.com", "email" : "cam@mongodb.com" } { "_id" : 4, "comment" : "It's just me. I'm testing. fred@MongoDB.com", "email" : "fred@MongoDB.com" }
Apply $regexFind
to String Elements of an Array
Create a sample collection contacts
with the following documents:
db.contacts.insertMany([ { "_id" : 1, name: "Aunt Arc Tikka", details: [ "+672-19-9999", "aunt.arc.tica@example.com" ] }, { "_id" : 2, name: "Belle Gium", details: [ "+32-2-111-11-11", "belle.gium@example.com" ] }, { "_id" : 3, name: "Cam Bo Dia", details: [ "+855-012-000-0000", "cam.bo.dia@example.com" ] }, { "_id" : 4, name: "Fred", details: [ "+1-111-222-3333" ] } ])
The following aggregation uses the $regexFind
to convert
the details
array into an embedded document with an email
and
phone
fields:
db.contacts.aggregate( [ { $unwind: "$details" }, { $addFields: { "regexemail": { $regexFind: { input: "$details", regex: /^[a-z0-9_.+-]+@[a-z0-9_.+-]+\.[a-z0-9_.+-]+$/, options: "i" } }, "regexphone": { $regexFind: { input: "$details", regex: /^[+]{0,1}[0-9]*\-?[0-9_\-]+$/ } } } }, { $project: { _id: 1, name: 1, details: { email: "$regexemail.match", phone: "$regexphone.match" } } }, { $group: { _id: "$_id", name: { $first: "$name" }, details: { $mergeObjects: "$details"} } }, { $sort: { _id: 1 } } ])
- First Stage
The stage
$unwinds
the array into separate documents:{ "_id" : 1, "name" : "Aunt Arc Tikka", "details" : "+672-19-9999" } { "_id" : 1, "name" : "Aunt Arc Tikka", "details" : "aunt.arc.tica@example.com" } { "_id" : 2, "name" : "Belle Gium", "details" : "+32-2-111-11-11" } { "_id" : 2, "name" : "Belle Gium", "details" : "belle.gium@example.com" } { "_id" : 3, "name" : "Cam Bo Dia", "details" : "+855-012-000-0000" } { "_id" : 3, "name" : "Cam Bo Dia", "details" : "cam.bo.dia@example.com" } { "_id" : 4, "name" : "Fred", "details" : "+1-111-222-3333" } - Second Stage
The stage uses the
$addFields
stage to add new fields to the document that contains the result of the$regexFind
for phone number and email:{ "_id" : 1, "name" : "Aunt Arc Tikka", "details" : "+672-19-9999", "regexemail" : null, "regexphone" : { "match" : "+672-19-9999", "idx" : 0, "captures" : [ ] } } { "_id" : 1, "name" : "Aunt Arc Tikka", "details" : "aunt.arc.tica@example.com", "regexemail" : { "match" : "aunt.arc.tica@example.com", "idx" : 0, "captures" : [ ] }, "regexphone" : null } { "_id" : 2, "name" : "Belle Gium", "details" : "+32-2-111-11-11", "regexemail" : null, "regexphone" : { "match" : "+32-2-111-11-11", "idx" : 0, "captures" : [ ] } } { "_id" : 2, "name" : "Belle Gium", "details" : "belle.gium@example.com", "regexemail" : { "match" : "belle.gium@example.com", "idx" : 0, "captures" : [ ] }, "regexphone" : null } { "_id" : 3, "name" : "Cam Bo Dia", "details" : "+855-012-000-0000", "regexemail" : null, "regexphone" : { "match" : "+855-012-000-0000", "idx" : 0, "captures" : [ ] } } { "_id" : 3, "name" : "Cam Bo Dia", "details" : "cam.bo.dia@example.com", "regexemail" : { "match" : "cam.bo.dia@example.com", "idx" : 0, "captures" : [ ] }, "regexphone" : null } { "_id" : 4, "name" : "Fred", "details" : "+1-111-222-3333", "regexemail" : null, "regexphone" : { "match" : "+1-111-222-3333", "idx" : 0, "captures" : [ ] } } - Third Stage
The stage use the
$project
stage to output documents with the_id
field, thename
field and thedetails
field. Thedetails
field is set to a document withemail
andphone
fields, whose values are determined from theregexemail
andregexphone
fields, respectively.{ "_id" : 1, "name" : "Aunt Arc Tikka", "details" : { "phone" : "+672-19-9999" } } { "_id" : 1, "name" : "Aunt Arc Tikka", "details" : { "email" : "aunt.arc.tica@example.com" } } { "_id" : 2, "name" : "Belle Gium", "details" : { "phone" : "+32-2-111-11-11" } } { "_id" : 2, "name" : "Belle Gium", "details" : { "email" : "belle.gium@example.com" } } { "_id" : 3, "name" : "Cam Bo Dia", "details" : { "phone" : "+855-012-000-0000" } } { "_id" : 3, "name" : "Cam Bo Dia", "details" : { "email" : "cam.bo.dia@example.com" } } { "_id" : 4, "name" : "Fred", "details" : { "phone" : "+1-111-222-3333" } } - Fourth Stage
The stage uses the
$group
stage to groups the input documents by their_id
value. The stage uses the$mergeObjects
expression to merge thedetails
documents.{ "_id" : 3, "name" : "Cam Bo Dia", "details" : { "phone" : "+855-012-000-0000", "email" : "cam.bo.dia@example.com" } } { "_id" : 4, "name" : "Fred", "details" : { "phone" : "+1-111-222-3333" } } { "_id" : 1, "name" : "Aunt Arc Tikka", "details" : { "phone" : "+672-19-9999", "email" : "aunt.arc.tica@example.com" } } { "_id" : 2, "name" : "Belle Gium", "details" : { "phone" : "+32-2-111-11-11", "email" : "belle.gium@example.com" } } - Fifth Stage
The stage uses the
$sort
stage to sort the documents by the_id
field.{ "_id" : 1, "name" : "Aunt Arc Tikka", "details" : { "phone" : "+672-19-9999", "email" : "aunt.arc.tica@example.com" } } { "_id" : 2, "name" : "Belle Gium", "details" : { "phone" : "+32-2-111-11-11", "email" : "belle.gium@example.com" } } { "_id" : 3, "name" : "Cam Bo Dia", "details" : { "phone" : "+855-012-000-0000", "email" : "cam.bo.dia@example.com" } } { "_id" : 4, "name" : "Fred", "details" : { "phone" : "+1-111-222-3333" } }
Use Captured Groupings to Parse User Name
Create a sample collection employees
with the following documents:
db.employees.insertMany([ { "_id" : 1, name: "Aunt Arc Tikka", "email" : "aunt.tica@example.com" }, { "_id" : 2, name: "Belle Gium", "email" : "belle.gium@example.com" }, { "_id" : 3, name: "Cam Bo Dia", "email" : "cam.dia@example.com" }, { "_id" : 4, name: "Fred" } ])
The employee email has the format
<firstname>.<lastname>@example.com
. Using the captured
field
returned in the $regexFind
results, you can parse out
user names for employees.
db.employees.aggregate( [ { $addFields: { "username": { $regexFind: { input: "$email", regex: /^([a-z0-9_.+-]+)@[a-z0-9_.+-]+\.[a-z0-9_.+-]+$/, options: "i" } }, } }, { $set: { username: { $arrayElemAt: [ "$username.captures", 0 ] } } } ] )
- First Stage
The stage uses the
$addFields
stage to add a new fieldusername
to the document. The new field contains the result of performing the$regexFind
on theemail
field:{ "_id" : 1, "name" : "Aunt Arc Tikka", "email" : "aunt.tica@example.com", "username" : { "match" : "aunt.tica@example.com", "idx" : 0, "captures" : [ "aunt.tica" ] } } { "_id" : 2, "name" : "Belle Gium", "email" : "belle.gium@example.com", "username" : { "match" : "belle.gium@example.com", "idx" : 0, "captures" : [ "belle.gium" ] } } { "_id" : 3, "name" : "Cam Bo Dia", "email" : "cam.dia@example.com", "username" : { "match" : "cam.dia@example.com", "idx" : 0, "captures" : [ "cam.dia" ] } } { "_id" : 4, "name" : "Fred", "username" : null } - Second Stage
The stage use the
$set
stage to reset theusername
to the zero-th element of the"$username.captures"
array. If the current value ofusername
is null, the new value ofusername
is set to null.{ "_id" : 1, "name" : "Aunt Arc Tikka", "email" : "aunt.tica@example.com", "username" : "aunt.tica" } { "_id" : 2, "name" : "Belle Gium", "email" : "belle.gium@example.com", "username" : "belle.gium" } { "_id" : 3, "name" : "Cam Bo Dia", "email" : "cam.dia@example.com", "username" : "cam.dia" } { "_id" : 4, "name" : "Fred", "username" : null }
Tip
See also:
For more information on the behavior of the captures
array and
additional examples, see
captures
Output Behavior.