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db.collection.findAndModify()

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db.collection.findAndModify(document)

Important

mongosh Method

This page documents a mongosh method. This is not the documentation for database commands or language-specific drivers, such as Node.js.

For the database command, see the findAndModify command.

For MongoDB API drivers, refer to the language-specific MongoDB driver documentation.

For the legacy mongo shell documentation, refer to the documentation for the corresponding MongoDB Server release:

mongo shell v4.4

Updates and returns a single document. By default, the returned document does not include the modifications made on the update. To return the document with the modifications made on the update, use the new option.

You can use db.collection.findAndModify() for deployments hosted in the following environments:

  • MongoDB Atlas: The fully managed service for MongoDB deployments in the cloud

Changed in version 5.0.

The findAndModify() method has the following form:

db.collection.findAndModify({
query: <document>,
sort: <document>,
remove: <boolean>,
update: <document or aggregation pipeline>, // Changed in MongoDB 4.2
new: <boolean>,
fields: <document>,
upsert: <boolean>,
bypassDocumentValidation: <boolean>,
writeConcern: <document>,
maxTimeMS: <integer>,
collation: <document>,
arrayFilters: [ <filterdocument1>, ... ],
let: <document> // Added in MongoDB 5.0
});

The db.collection.findAndModify() method takes a document parameter with the following embedded document fields:

Parameter
Type
Description
query
document

Optional. The selection criteria for the modification. The query field employs the same query selectors as used in the db.collection.find() method. Although the query may match multiple documents, db.collection.findAndModify() will only select one document to modify.

If unspecified, defaults to an empty document.

Starting in MongoDB 4.2 (and 4.0.12+, 3.6.14+, and 3.4.23+), the operation errors if the query argument is not a document.

sort

document

Optional. Determines which document the operation updates if the query selects multiple documents. db.collection.findAndModify() updates the first document in the sort order specified by this argument.

Starting in MongoDB 4.2 (and 4.0.12+, 3.6.14+, and 3.4.23+), the operation errors if the sort argument is not a document.

MongoDB does not store documents in a collection in a particular order. When sorting on a field which contains duplicate values, documents containing those values may be returned in any order.

If consistent sort order is desired, include at least one field in your sort that contains unique values. The easiest way to guarantee this is to include the _id field in your sort query.

See Sort Consistency for more information.

remove
boolean
Must specify either the remove or the update field. Removes the document specified in the query field. Set this to true to remove the selected document . The default is false.
update
document or array

Must specify either the remove or the update field. Performs an update of the selected document.

new
boolean
Optional. When true, returns the updated document rather than the original. The default is false.
fields
document

Optional. A subset of fields to return. The fields document specifies an inclusion of a field with 1, as in: fields: { <field1>: 1, <field2>: 1, ... }.

Starting in MongoDB 4.2 (and 4.0.12+, 3.6.14+, and 3.4.23+), the operation errors if the fields argument is not a document.

For more information on projection, see fields Projection.

upsert
boolean

Optional. Used in conjunction with the update field.

When true, findAndModify() either:

  • Creates a new document if no documents match the query. For more details see upsert behavior.

  • Updates a single document that matches the query.

To avoid multiple upserts, ensure that the query field(s) are uniquely indexed. See Upsert with Unique Index for an example.

Defaults to false, which does not insert a new document when no match is found.

bypassDocumentValidation
boolean
Optional. Enables db.collection.findAndModify() to bypass document validation during the operation. This lets you update documents that do not meet the validation requirements.
writeConcern
document

Optional. A document expressing the write concern. Omit to use the default write concern.

Do not explicitly set the write concern for the operation if run in a transaction. To use write concern with transactions, see Transactions and Write Concern.

maxTimeMS
non-negative integer

Optional.

Specifies a time limit in milliseconds. If you do not specify a value for maxTimeMS, operations will not time out. A value of 0 explicitly specifies the default unbounded behavior.

MongoDB terminates operations that exceed their allotted time limit using the same mechanism as db.killOp(). MongoDB only terminates an operation at one of its designated interrupt points.

collation
document

Optional.

Specifies the collation to use for the operation.

Collation allows users to specify language-specific rules for string comparison, such as rules for lettercase and accent marks.

The collation option has the following syntax:

collation: {
locale: <string>,
caseLevel: <boolean>,
caseFirst: <string>,
strength: <int>,
numericOrdering: <boolean>,
alternate: <string>,
maxVariable: <string>,
backwards: <boolean>
}

When specifying collation, the locale field is mandatory; all other collation fields are optional. For descriptions of the fields, see Collation Document.

If the collation is unspecified but the collection has a default collation (see db.createCollection()), the operation uses the collation specified for the collection.

If no collation is specified for the collection or for the operations, MongoDB uses the simple binary comparison used in prior versions for string comparisons.

You cannot specify multiple collations for an operation. For example, you cannot specify different collations per field, or if performing a find with a sort, you cannot use one collation for the find and another for the sort.

arrayFilters
array

Optional. An array of filter documents that determine which array elements to modify for an update operation on an array field.

In the update document, use the $[<identifier>] filtered positional operator to define an identifier, which you then reference in the array filter documents. You cannot have an array filter document for an identifier if the identifier is not included in the update document.

Note

The <identifier> must begin with a lowercase letter and contain only alphanumeric characters.

You can include the same identifier multiple times in the update document; however, for each distinct identifier ($[identifier]) in the update document, you must specify exactly one corresponding array filter document. That is, you cannot specify multiple array filter documents for the same identifier. For example, if the update statement includes the identifier x (possibly multiple times), you cannot specify the following for arrayFilters that includes 2 separate filter documents for x:

// INVALID
[
{ "x.a": { $gt: 85 } },
{ "x.b": { $gt: 80 } }
]

However, you can specify compound conditions on the same identifier in a single filter document, such as in the following examples:

// Example 1
[
{ $or: [{"x.a": {$gt: 85}}, {"x.b": {$gt: 80}}] }
]
// Example 2
[
{ $and: [{"x.a": {$gt: 85}}, {"x.b": {$gt: 80}}] }
]
// Example 3
[
{ "x.a": { $gt: 85 }, "x.b": { $gt: 80 } }
]

For examples, see Specify arrayFilters for an Array Update Operations.

Note

arrayFilters is not available for updates that use an aggregation pipeline.

document

Optional.

Specifies a document with a list of variables. This allows you to improve command readability by separating the variables from the query text.

The document syntax is:

{ <variable_name_1>: <expression_1>,
...,
<variable_name_n>: <expression_n> }

The variable is set to the value returned by the expression, and cannot be changed afterwards.

To access the value of a variable in the command, use the double dollar sign prefix ($$) together with your variable name in the form $$<variable_name>. For example: $$targetTotal.

Note

To use a variable to filter results, you must access the variable within the $expr operator.

For a complete example using let and variables, see Use Variables in let.

New in version 5.0.

For remove operations, if the query matches a document, findAndModify() returns the removed document. If the query does not match a document to remove, findAndModify() returns null.

For update operations, findAndModify() returns one of the following:

  • If the new parameter is not set or is false:

    • the pre-modification document if the query matches a document;

    • otherwise, null.

  • If new is true:

    • the updated document if the query returns a match;

    • the inserted document if upsert: true and no document matches the query;

    • otherwise, null.

Important

Language Consistency

Starting in MongoDB 4.4, as part of making find() and findAndModify() projection consistent with aggregation's $project stage,

The fields option takes a document in the following form:

{ field1: <value>, field2: <value> ... }
Projection
Description
<field>: <1 or true>
Specifies the inclusion of a field. If you specify a non-zero integer for the projection value, the operation treats the value as true.
<field>: <0 or false>
Specifies the exclusion of a field.
"<field>.$": <1 or true>

Uses the $ array projection operator to return the first element that matches the query condition on the array field. If you specify a non-zero integer for the projection value, the operation treats the value as true.

Not available for views.

<field>: <array projection>

Uses the array projection operators ($elemMatch, $slice) to specify the array elements to include.

Not available for views.

<field>: <aggregation expression>

Specifies the value of the projected field.

Starting in MongoDB 4.4, with the use of aggregation expressions and syntax, including the use of literals and aggregation variables, you can project new fields or project existing fields with new values.

  • If you specify a non-numeric, non-boolean literal (such as a literal string or an array or an operator expression) for the projection value, the field is projected with the new value, for example:

    • { field: [ 1, 2, 3, "$someExistingField" ] }

    • { field: "New String Value" }

    • { field: { status: "Active", total: { $sum: "$existingArray" } } }

  • To project a literal value for a field, use the $literal aggregation expression, for example:

    • { field: { $literal: 5 } }

    • { field: { $literal: true } }

    • { field: { $literal: { fieldWithValue0: 0, fieldWithValue1: 1 } } }

In versions 4.2 and earlier, any specification value (with the exception of the previously unsupported document value) is treated as either true or false to indicate the inclusion or exclusion of the field.

New in version 4.4.

For fields in an embedded documents, you can specify the field using either:

  • dot notation, for example "field.nestedfield": <value>

  • nested form, for example { field: { nestedfield: <value> } } (Starting in MongoDB 4.4)

The _id field is included in the returned documents by default unless you explicitly specify _id: 0 in the projection to suppress the field.

A projection cannot contain both include and exclude specifications, with the exception of the _id field:

  • In projections that explicitly include fields, the _id field is the only field that you can explicitly exclude.

  • In projections that explicitly excludes fields, the _id field is the only field that you can explicitly include; however, the _id field is included by default.

For more information on projection, see also:

Upserts can create duplicate documents, unless there is a unique index to prevent duplicates.

Consider an example where no document with the name Andy exists and multiple clients issue the following command at roughly the same time:

db.people.findAndModify(
{
query: { name: "Andy" },
update: { $inc: { score: 1 } },
upsert: true
}
)

If all findOneAndUpdate() operations finish the query phase before any client successfully inserts data, and there is no unique index on the name field, each findOneAndUpdate() operation may result in an insert, creating multiple documents with name: Andy.

A unique index on the name field ensures that only one document is created. With a unique index in place, the multiple findOneAndUpdate() operations now exhibit the following behavior:

  • Exactly one findOneAndUpdate() operation will successfully insert a new document.

  • Other findOneAndUpdate() operations either update the newly-inserted document or fail due to a unique key collision.

    In order for other findOneAndUpdate() operations to update the newly-inserted document, all of the following conditions must be met:

    • The target collection has a unique index that would cause a duplicate key error.

    • The update operation is not updateMany or multi is false.

    • The update match condition is either:

      • A single equality predicate. For example { "fieldA" : "valueA" }

      • A logical AND of equality predicates. For example { "fieldA" : "valueA", "fieldB" : "valueB" }

    • The fields in the equality predicate match the fields in the unique index key pattern.

    • The update operation does not modify any fields in the unique index key pattern.

The following table shows examples of upsert operations that, when a key collision occurs, either result in an update or fail.

Unique Index Key Pattern
Update Operation
Result
{ name : 1 }
db.people.updateOne(
{ name: "Andy" },
{ $inc: { score: 1 } },
{ upsert: true }
)
The score field of the matched document is incremented by 1.
{ name : 1 }
db.people.updateOne(
{ name: { $ne: "Joe" } },
{ $set: { name: "Andy" } },
{ upsert: true }
)
The operation fails because it modifies the field in the unique index key pattern (name).
{ name : 1 }
db.people.updateOne(
{ name: "Andy", email: "andy@xyz.com" },
{ $set: { active: false } },
{ upsert: true }
)
The operation fails because the equality predicate fields (name, email) do not match the index key field (name).

To use findAndModify on a sharded collection:

  • If you only target one shard, you can use a partial shard key in the query field or,

  • You can provide an equality condition on a full shard key in the query field.

Starting in version 4.4, documents in a sharded collection can be missing the shard key fields. To target a document that is missing the shard key, you can use the null equality match in conjunction with another filter condition (such as on the _id field). For example:

{ _id: <value>, <shardkeyfield>: null } // _id of the document missing shard key

Starting in MongoDB 4.2, you can update a document's shard key value unless the shard key field is the immutable _id field. In MongoDB 4.2 and earlier, a document's shard key field value is immutable.

Warning

Starting in version 4.4, documents in sharded collections can be missing the shard key fields. Take precaution to avoid accidentally removing the shard key when changing a document's shard key value.

To update the existing shard key value with db.collection.findAndModify():

  • You must run on a mongos. Do not issue the operation directly on the shard.

  • You must run either in a transaction or as a retryable write.

  • You must include an equality filter on the full shard key.

Starting in version 4.4, documents in a sharded collection can be missing the shard key fields. To use db.collection.findAndModify() to set the document's missing shard key:

  • You must run on a mongos. Do not issue the operation directly on the shard.

  • You must run either in a transaction or as a retryable write if the new shard key value is not null.

  • You must include an equality filter on the full shard key.

Tip

Since a missing key value is returned as part of a null equality match, to avoid updating a null-valued key, include additional query conditions (such as on the _id field) as appropriate.

See also:

The db.collection.findAndModify() method adds support for the bypassDocumentValidation option, which lets you bypass document validation when inserting or updating documents in a collection with validation rules.

When updating a document, db.collection.findAndModify() and the updateOne() method operate differently:

  • If multiple documents match the update criteria, for db.collection.findAndModify(), you can specify a sort to provide some measure of control on which document to update.

    updateOne() updates the first document that matches.

  • By default, db.collection.findAndModify() returns the pre-modified version of the document. To obtain the updated document, use the new option.

    The updateOne() method returns a WriteResult() object that contains the status of the operation.

    To return the updated document, use the find() method. However, other updates may have modified the document between your update and the document retrieval. Also, if the update modified only a single document but multiple documents matched, you will need to use additional logic to identify the updated document.

When modifying a single document, both db.collection.findAndModify() and the updateOne() method atomically update the document. See Atomicity and Transactions for more details about interactions and order of operations of these methods.

db.collection.findAndModify() can be used inside distributed transactions.

Important

In most cases, a distributed transaction incurs a greater performance cost over single document writes, and the availability of distributed transactions should not be a replacement for effective schema design. For many scenarios, the denormalized data model (embedded documents and arrays) will continue to be optimal for your data and use cases. That is, for many scenarios, modeling your data appropriately will minimize the need for distributed transactions.

For additional transactions usage considerations (such as runtime limit and oplog size limit), see also Production Considerations.

You can create collections and indexes inside a distributed transaction if the transaction is not a cross-shard write transaction.

db.collection.findAndModify() with upsert: true can be run on an existing collection or a non-existing collection. If run on a non-existing collection, the operation creates the collection.

Do not explicitly set the write concern for the operation if run in a transaction. To use write concern with transactions, see Transactions and Write Concern.

If a db.collection.findAndModify() operation successfully finds and modifies a document, the operation adds an entry on the oplog (operations log). If the operation fails or does not find a document to modify, the operation does not add an entry on the oplog.

The following method updates and returns an existing document in the people collection where the document matches the query criteria:

db.people.findAndModify({
query: { name: "Tom", state: "active", rating: { $gt: 10 } },
sort: { rating: 1 },
update: { $inc: { score: 1 } }
})

This method performs the following actions:

  1. The query finds a document in the people collection where the name field has the value Tom, the state field has the value active and the rating field has a value greater than 10.

  2. The sort orders the results of the query in ascending order. If multiple documents meet the query condition, the method will select for modification the first document as ordered by this sort.

  3. The update increments the value of the score field by 1.

  4. The method returns the original (i.e. pre-modification) document selected for this update:

    {
    "_id" : ObjectId("50f1e2c99beb36a0f45c6453"),
    "name" : "Tom",
    "state" : "active",
    "rating" : 100,
    "score" : 5
    }

    To return the updated document, add the new:true option to the method.

    If no document matched the query condition, the method returns null.

The following method includes the upsert: true option for the update operation to either update a matching document or, if no matching document exists, create a new document:

db.people.findAndModify({
query: { name: "Gus", state: "active", rating: 100 },
sort: { rating: 1 },
update: { $inc: { score: 1 } },
upsert: true
})

If the method finds a matching document, the method performs an update.

If the method does not find a matching document, the method creates a new document. Because the method included the sort option, it returns an empty document { } as the original (pre-modification) document:

{ }

If the method did not include a sort option, the method returns null.

null

The following method includes both the upsert: true option and the new:true option. The method either updates a matching document and returns the updated document or, if no matching document exists, inserts a document and returns the newly inserted document in the value field.

In the following example, no document in the people collection matches the query condition:

db.people.findAndModify({
query: { name: "Pascal", state: "active", rating: 25 },
sort: { rating: 1 },
update: { $inc: { score: 1 } },
upsert: true,
new: true
})

The method returns the newly inserted document:

{
"_id" : ObjectId("50f49ad6444c11ac2448a5d6"),
"name" : "Pascal",
"rating" : 25,
"score" : 1,
"state" : "active"
}

By including a sort specification on the rating field, the following example removes from the people collection a single document with the state value of active and the lowest rating among the matching documents:

db.people.findAndModify(
{
query: { state: "active" },
sort: { rating: 1 },
remove: true
}
)

The method returns the deleted document:

{
"_id" : ObjectId("52fba867ab5fdca1299674ad"),
"name" : "XYZ123",
"score" : 1,
"state" : "active",
"rating" : 3
}

Collation allows users to specify language-specific rules for string comparison, such as rules for lettercase and accent marks.

A collection myColl has the following documents:

{ _id: 1, category: "café", status: "A" }
{ _id: 2, category: "cafe", status: "a" }
{ _id: 3, category: "cafE", status: "a" }

The following operation includes the collation option:

db.myColl.findAndModify({
query: { category: "cafe", status: "a" },
sort: { category: 1 },
update: { $set: { status: "Updated" } },
collation: { locale: "fr", strength: 1 }
});

The operation returns the following document:

{ "_id" : 1, "category" : "café", "status" : "A" }

Note

arrayFilters is not available for updates that use an aggregation pipeline.

Starting in MongoDB 3.6, when updating an array field, you can specify arrayFilters that determine which array elements to update.

Note

arrayFilters is not available for updates that use an aggregation pipeline.

Create a collection students with the following documents:

db.students.insertMany( [
{ "_id" : 1, "grades" : [ 95, 92, 90 ] },
{ "_id" : 2, "grades" : [ 98, 100, 102 ] },
{ "_id" : 3, "grades" : [ 95, 110, 100 ] }
] )

To update all elements that are greater than or equal to 100 in the grades array, use the filtered positional operator $[<identifier>] with the arrayFilters option in the db.collection.findAndModify() method:

db.students.findAndModify({
query: { grades: { $gte: 100 } },
update: { $set: { "grades.$[element]" : 100 } },
arrayFilters: [ { "element": { $gte: 100 } } ]
})

The operation updates the grades field for a single document, and after the operation, the collection has the following documents:

{ "_id" : 1, "grades" : [ 95, 92, 90 ] }
{ "_id" : 2, "grades" : [ 98, 100, 100 ] }
{ "_id" : 3, "grades" : [ 95, 110, 100 ] }

Note

arrayFilters is not available for updates that use an aggregation pipeline.

Create a collection students2 with the following documents:

db.students2.insertMany( [
{
"_id" : 1,
"grades" : [
{ "grade" : 80, "mean" : 75, "std" : 6 },
{ "grade" : 85, "mean" : 90, "std" : 4 },
{ "grade" : 85, "mean" : 85, "std" : 6 }
]
},
{
"_id" : 2,
"grades" : [
{ "grade" : 90, "mean" : 75, "std" : 6 },
{ "grade" : 87, "mean" : 90, "std" : 3 },
{ "grade" : 85, "mean" : 85, "std" : 4 }
]
}
] )

The following operation finds a document where the _id field equals 1 and uses the filtered positional operator $[<identifier>] with the arrayFilters to update the mean for all elements in the grades array where the grade is greater than or equal to 85.

db.students2.findAndModify({
query: { _id : 1 },
update: { $set: { "grades.$[elem].mean" : 100 } },
arrayFilters: [ { "elem.grade": { $gte: 85 } } ]
})

The operation updates the grades field for a single document, and after the operation, the collection has the following documents:

{
"_id" : 1,
"grades" : [
{ "grade" : 80, "mean" : 75, "std" : 6 },
{ "grade" : 85, "mean" : 100, "std" : 4 },
{ "grade" : 85, "mean" : 100, "std" : 6 }
]
}
{
"_id" : 2,
"grades" : [
{ "grade" : 90, "mean" : 75, "std" : 6 },
{ "grade" : 87, "mean" : 90, "std" : 3 },
{ "grade" : 85, "mean" : 85, "std" : 4 }
]
}

Starting in MongoDB 4.2, db.collection.findAndModify() can accept an aggregation pipeline for the update. The pipeline can consist of the following stages:

Using the aggregation pipeline allows for a more expressive update statement, such as expressing conditional updates based on current field values or updating one field using the value of another field(s).

For example, create a collection students2 with the following documents:

db.students2.insertMany( [
{
"_id" : 1,
"grades" : [
{ "grade" : 80, "mean" : 75, "std" : 6 },
{ "grade" : 85, "mean" : 90, "std" : 4 },
{ "grade" : 85, "mean" : 85, "std" : 6 }
]
},
{
"_id" : 2,
"grades" : [
{ "grade" : 90, "mean" : 75, "std" : 6 },
{ "grade" : 87, "mean" : 90, "std" : 3 },
{ "grade" : 85, "mean" : 85, "std" : 4 }
]
}
] )

The following operation finds a document where the _id field equals 1 and uses an aggregation pipeline to calculate a new field total from the grades field:

db.students2.findAndModify( {
query: { "_id" : 1 },
update: [ { $set: { "total" : { $sum: "$grades.grade" } } } ], // The $set stage is an alias for ``$addFields`` stage
new: true
} )

Note

The $set used in the pipeline refers to the aggregation stage $set and not the update operator $set.

The operation returns the updated document:

{
"_id" : 1,
"grades" : [ { "grade" : 80, "mean" : 75, "std" : 6 }, { "grade" : 85, "mean" : 90, "std" : 4 }, { "grade" : 85, "mean" : 85, "std" : 6 } ],
"total" : 250
}

New in version 5.0.

To define variables that you can access elsewhere in the command, use the let option.

Note

To filter results using a variable, you must access the variable within the $expr operator.

Create a collection cakeFlavors:

db.cakeFlavors.insertMany( [
{ _id: 1, flavor: "chocolate" },
{ _id: 2, flavor: "strawberry" },
{ _id: 3, flavor: "cherry" }
] )

The following example defines a targetFlavor variable in let and uses the variable to change the cake flavor from cherry to orange:

db.cakeFlavors.findAndModify( {
query: {
$expr: { $eq: [ "$flavor", "$$targetFlavor" ] }
},
update: { flavor: "orange" },
let: { targetFlavor: "cherry" }
} )

Starting in MongoDB 7.0, you can use the new USER_ROLES system variable to return user roles.

The example in this section shows updates to fields in a collection containing medical information. The example reads the current user roles from the USER_ROLES system variable and only performs the updates if the user has a specific role.

To use a system variable, add $$ to the start of the variable name. Specify the USER_ROLES system variable as $$USER_ROLES.

The example creates these users:

  • James with a Billing role.

  • Michelle with a Provider role.

Perform the following steps to create the roles, users, and collection:

1

Create roles named Billing and Provider with the required privileges and resources.

Run:

db.createRole( { role: "Billing", privileges: [ { resource: { db: "test",
collection: "medicalView" }, actions: [ "find" ] } ], roles: [ ] } )
db.createRole( { role: "Provider", privileges: [ { resource: { db: "test",
collection: "medicalView" }, actions: [ "find" ] } ], roles: [ ] } )
2

Create users named James and Michelle with the required roles.

db.createUser( {
user: "James",
pwd: "js008",
roles: [
{ role: "Billing", db: "test" }
]
} )
db.createUser( {
user: "Michelle",
pwd: "me009",
roles: [
{ role: "Provider", db: "test" }
]
} )
3

Run:

db.medical.insertMany( [
{
_id: 0,
patientName: "Jack Jones",
diagnosisCode: "CAS 17",
creditCard: "1234-5678-9012-3456"
},
{
_id: 1,
patientName: "Mary Smith",
diagnosisCode: "ACH 01",
creditCard: "6541-7534-9637-3456"
}
] )

Log in as as Michelle, who has the Provider role, and perform an update:

1

Run:

db.auth( "Michelle", "me009" )
2

Run:

// Attempt to find and modify document
db.medical.findAndModify( {
query:
{ $and: [
{
// Only update the document for Mary Smith
patientName: { $eq: "Mary Smith" }
},
{
// User must have the Provider role to perform the update
$expr: { $ne: [ {
$setIntersection: [ [ "Provider" ], "$$USER_ROLES.role" ]
}, [] ] }
}
]
},
// Update document
update: {
patientName: "Mary Smith",
diagnosisCode: "ACH 03",
creditCard: "6541-7534-9637-3456"
}
} )

The previous example uses $setIntersection to return documents where the intersection between the "Provider" string and the user roles from $$USER_ROLES.role is not empty. Michelle has the Provider role, so the update is performed.

Next, log in as as James, who does not have the Provider role, and attempt to perform the same update:

1

Run:

db.auth( "James", "js008" )
2

Run:

// Attempt to find and modify document
db.medical.findAndModify( {
query:
{ $and: [
{
// Only update the document for Mary Smith
patientName: { $eq: "Mary Smith" }
},
{
// User must have the Provider role to perform the update
$expr: { $ne: [ {
$setIntersection: [ [ "Provider" ], "$$USER_ROLES.role" ]
}, [] ] }
}
]
},
// Update document
update: {
patientName: "Mary Smith",
diagnosisCode: "ACH 03",
creditCard: "6541-7534-9637-3456"
}
} )

The previous example does not update any documents.

←  db.collection.find()db.collection.findOne() →