db.collection.updateMany()

Definition

• db.collection.updateMany(filter, update, options)

mongo Shell Method

This page documents the mongo shell method, and doesnot refer to the MongoDB Node.js driver (or any other driver)method. For corresponding MongoDB driver API, refer to your specificMongoDB driver documentation instead.

New in version 3.2.

Updates all documents that match the specified filter for acollection.

Syntax

The updateMany() method has the following form:

db.collection.updateMany(
   <filter>,
   <update>,
   {
     upsert: <boolean>,
     writeConcern: <document>,
     collation: <document>,
     arrayFilters: [ <filterdocument1>, ... ],
     hint:  <document|string>        // Available starting in MongoDB 4.2.1
   }
)

Parameters

The updateMany() method takes the followingparameters:

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

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

// 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 } }]

Returns

The method returns a document that contains:

• A boolean acknowledged as true if the operation ran withwrite concern or false if write concern was disabled
• matchedCount containing the number of matched documents
• modifiedCount containing the number of modified documents
• upsertedId containing the _id for the upserted document

Access Control

On deployments running with authorization, theuser must have access that includes the following privileges:

• update action on the specified collection(s).
• find action on the specified collection(s).
• insert action on the specified collection(s) if theoperation results in an upsert.

The built-in role readWrite provides the requiredprivileges.

Behavior

updateMany() updates all matching documents inthe collection that match the filter, using the update criteriato apply modifications.

Upsert

If upsert: true and no documents match the filter,db.collection.updateMany() creates a newdocument based on the filter and update parameters.

If you specify upsert: true on a sharded collection, you mustinclude the full shard key in the filter. For additionaldb.collection.updateMany() behavior, seeSharded Collections.

SeeUpdate Multiple Documents with Upsert.

Update with an Update Operator Expressions Document

For the modification specification, thedb.collection.updateMany() method can accept a document thatonly contains update operator expressions toperform.

For example:

db.collection.updateMany(
   <query>,
   { $set: { status: "D" }, $inc: { quantity: 2 } },
   ...
)

Update with an Aggregation Pipeline

Starting in MongoDB 4.2, the db.collection.updateMany() methodcan accept an aggregation pipeline [ <stage1>, <stage2>, … ] thatspecifies the modifications to perform. The pipeline can consist ofthe following stages:

• $addFields and its alias $set
• $project and its alias $unset
• $replaceRoot and its alias $replaceWith.

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

For example:

db.collection.updateMany(
   <query>,
   [
      { $set: { status: "Modified", comments: [ "$misc1", "$misc2" ] } },
      { $unset: [ "misc1", "misc2" ] }
   ]
   ...
)

Note

The $set and $unset used in the pipeline refers to theaggregation stages $set and $unsetrespectively, and not the update operators $set and $unset.

For examples, see Update with Aggregation Pipeline.

Capped Collections

If an update operation changes the document size, the operation will fail.

Sharded Collections

For a db.collection.updateMany() operation that includesupsert: true and is on a sharded collection, you must include thefull shard key in the filter.

Explainability

updateMany() is not compatible withdb.collection.explain().

Use update() instead.

Transactions

db.collection.updateMany() can be used inside multi-document transactions.

If the operation results in an upsert, the collection must already exist.

Do not explicitly set the write concern for the operation if run ina transaction. To use write concern with transactions, seeTransactions and Write Concern.

Important

In most cases, multi-document transaction incurs a greaterperformance cost over single document writes, and theavailability of multi-document transactions should not be areplacement for effective schema design. For many scenarios, thedenormalized data model (embedded documents and arrays) will continue to be optimal for yourdata and use cases. That is, for many scenarios, modeling your dataappropriately will minimize the need for multi-documenttransactions.

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

Examples

Update Multiple Documents

The restaurant collection contains the following documents:

{ "_id" : 1, "name" : "Central Perk Cafe", "violations" : 3 }
{ "_id" : 2, "name" : "Rock A Feller Bar and Grill", "violations" : 2 }
{ "_id" : 3, "name" : "Empire State Sub", "violations" : 5 }
{ "_id" : 4, "name" : "Pizza Rat's Pizzaria", "violations" : 8 }

The following operation updates all documents where violations aregreater than 4 and $set a flag for review:

try {
   db.restaurant.updateMany(
      { violations: { $gt: 4 } },
      { $set: { "Review" : true } }
   );
} catch (e) {
   print(e);
}

The operation returns:

{ "acknowledged" : true, "matchedCount" : 2, "modifiedCount" : 2 }

The collection now contains the following documents:

{ "_id" : 1, "name" : "Central Perk Cafe", "violations" : 3 }
{ "_id" : 2, "name" : "Rock A Feller Bar and Grill", "violations" : 2 }
{ "_id" : 3, "name" : "Empire State Sub", "violations" : 5, "Review" : true }
{ "_id" : 4, "name" : "Pizza Rat's Pizzaria", "violations" : 8, "Review" : true }

If no matches were found, the operation instead returns:

{ "acknowledged" : true, "matchedCount" : 0, "modifiedCount" : 0 }

Setting upsert: true would insert a document if no match was found.

Update with Aggregation Pipeline

Starting in MongoDB 4.2, the db.collection.updateMany() can usean aggregation pipeline for the update. The pipeline can consist of thefollowing stages:

• $addFields and its alias $set
• $project and its alias $unset
• $replaceRoot and its alias $replaceWith.

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

Example 1

The following examples uses the aggregation pipeline to modify a fieldusing the values of the other fields in the document.

Create a members collection with the following documents:

db.members.insertMany([
   { "_id" : 1, "member" : "abc123", "status" : "A", "points" : 2, "misc1" : "note to self: confirm status", "misc2" : "Need to activate" },
   { "_id" : 2, "member" : "xyz123", "status" : "A", "points" : 60, "misc1" : "reminder: ping me at 100pts", "misc2" : "Some random comment" }
])

Assume that instead of separate misc1 and misc2 fields, youwant to gather these into a new comments field. The followingupdate operation uses an aggregation pipeline to add the newcomments field and remove the misc1 and misc2 fields forall documents in the collection.

db.members.updateMany(
   { },
   [
      { $set: { status: "Modified", comments: [ "$misc1", "$misc2" ] } },
      { $unset: [ "misc1", "misc2" ] }
   ]
)

Note

The $set and $unset used in the pipeline refers to theaggregation stages $set and $unsetrespectively, and not the update operators $set and $unset.

• First Stage
• The $set stage creates a new array field commentswhose elements are the current content of the misc1 andmisc2 fields.
• Second Stage
• The $unset stage removes the misc1 and misc2 fields.

After the command, the collection contains the following documents:

{ "_id" : 1, "member" : "abc123", "status" : "Modified", "points" : 2, "comments" : [ "note to self: confirm status", "Need to activate" ] }
{ "_id" : 2, "member" : "xyz123", "status" : "Modified", "points" : 60, "comments" : [ "reminder: ping me at 100pts", "Some random comment" ] }

Example 2

The aggregation pipeline allows the update to perform conditionalupdates based on the current field values as well as use current fieldvalues to calculate a separate field value.

For example, create a students3 collection with the following documents:

db.students3.insert([
   { "_id" : 1, "tests" : [ 95, 92, 90 ] },
   { "_id" : 2, "tests" : [ 94, 88, 90 ] },
   { "_id" : 3, "tests" : [ 70, 75, 82 ] }
]);

Using an aggregation pipeline, you can update the documents with thecalculated grade average and letter grade.

db.students3.updateMany(
   { },
   [
     { $set: { average : { $avg: "$tests" } } },
     { $set: { grade: { $switch: {
                           branches: [
                               { case: { $gte: [ "$average", 90 ] }, then: "A" },
                               { case: { $gte: [ "$average", 80 ] }, then: "B" },
                               { case: { $gte: [ "$average", 70 ] }, then: "C" },
                               { case: { $gte: [ "$average", 60 ] }, then: "D" }
                           ],
                           default: "F"
     } } } }
   ]
)

Note

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

• First Stage
• The $set stage calculates a new field average basedon the average of the tests field. See $avg formore information on the $avg aggregation operator.
• Second Stage
• The $set stage calculates a new field grade based onthe average field calculated in the previous stage. See$switch for more information on the $switchaggregation operator.

After the command, the collection contains the following documents:

{ "_id" : 1, "tests" : [ 95, 92, 90 ], "average" : 92.33333333333333, "grade" : "A" }
{ "_id" : 2, "tests" : [ 94, 88, 90 ], "average" : 90.66666666666667, "grade" : "A" }
{ "_id" : 3, "tests" : [ 70, 75, 82 ], "average" : 75.66666666666667, "grade" : "C" }

Update Multiple Documents with Upsert

The inspectors collection contains the following documents:

{ "_id" : 92412, "inspector" : "F. Drebin", "Sector" : 1, "Patrolling" : true },
{ "_id" : 92413, "inspector" : "J. Clouseau", "Sector" : 2, "Patrolling" : false },
{ "_id" : 92414, "inspector" : "J. Clouseau", "Sector" : 3, "Patrolling" : true },
{ "_id" : 92415, "inspector" : "R. Coltrane", "Sector" : 3, "Patrolling" : false }

The following operation updates all documents with Sector greaterthan 4 and inspector equal to "R. Coltrane":

try {
   db.inspectors.updateMany(
      { "Sector" : { $gt : 4 }, "inspector" : "R. Coltrane" },
      { $set: { "Patrolling" : false } },
      { upsert: true }
   );
} catch (e) {
   print(e);
}

The operation returns:

{
   "acknowledged" : true,
   "matchedCount" : 0,
   "modifiedCount" : 0,
   "upsertedId" : ObjectId("56fc5dcb39ee682bdc609b02")
}

The collection now contains the following documents:

{ "_id" : 92412, "inspector" : "F. Drebin", "Sector" : 1, "Patrolling" : true },
{ "_id" : 92413, "inspector" : "J. Clouseau", "Sector" : 2, "Patrolling" : false },
{ "_id" : 92414, "inspector" : "J. Clouseau", "Sector" : 3, "Patrolling" : true },
{ "_id" : 92415, "inspector" : "R. Coltrane", "Sector" : 3, "Patrolling" : false },
{ "_id" : ObjectId("56fc5dcb39ee682bdc609b02"), "inspector" : "R. Coltrane", "Patrolling" : false }

Since no documents matched the filter, and upsert was true,updateMany inserted the document with agenerated _id, the equality conditions from the filter, and theupdate modifiers.

Update with Write Concern

Given a three member replica set, the following operation specifies aw of majority and wtimeout of 100:

try {
   db.restaurant.updateMany(
       { "name" : "Pizza Rat's Pizzaria" },
       { $inc: { "violations" : 3}, $set: { "Closed" : true } },
       { w: "majority", wtimeout: 100 }
   );
} catch (e) {
   print(e);
}

If the acknowledgement takes longer than the wtimeout limit, the followingexception is thrown:

WriteConcernError({
   "code" : 64,
   "errInfo" : {
      "wtimeout" : true
   },
   "errmsg" : "waiting for replication timed out"
}) :
undefined

The wtimeout error only indicates that the operation did not complete ontime. The write operation itself can still succeed outside of the set timelimit.

Specify Collation

New in version 3.4.

Collation allows users to specifylanguage-specific rules for string comparison, such as rules forlettercase 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 collationoption:

db.myColl.updateMany(
   { category: "cafe" },
   { $set: { status: "Updated" } },
   { collation: { locale: "fr", strength: 1 } }
);

Specify arrayFilters for an Array Update Operations

New in version 3.6.

Starting in MongoDB 3.6, when updating an array field, you canspecify arrayFilters that determine which array elements toupdate.

Update Elements Match arrayFilters Criteria

Create a collection students with the following documents:

db.students.insert([
   { "_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 thegrades array, use the filtered positional operator$[<identifier>] with the arrayFilters option:

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

After the operation, the collection contains the following documents:

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

Update Specific Elements of an Array of Documents

Create a collection students2 with the following documents:

db.students2.insert([
   {
      "_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 }
      ]
   }
])

To modify the value of the mean field for all elements in thegrades array where the grade is greater than or equal to 85,use the filtered positional operator $[<identifier>] withthe arrayFilters:

db.students2.updateMany(
   { },
   { $set: { "grades.$[elem].mean" : 100 } },
   { arrayFilters: [ { "elem.grade": { $gte: 85 } } ] }
)

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" : 100, "std" : 6 },
      { "grade" : 87, "mean" : 100, "std" : 3 },
      { "grade" : 85, "mean" : 100, "std" : 4 }
   ]
}

Specify hint for Update Operations

New in version 4.2.1.

Create a sample members collection with the following documents:

db.members.insertMany([
   { "_id" : 1, "member" : "abc123", "status" : "P", "points" :  0,  "misc1" : null, "misc2" : null },
   { "_id" : 2, "member" : "xyz123", "status" : "A", "points" : 60,  "misc1" : "reminder: ping me at 100pts", "misc2" : "Some random comment" },
   { "_id" : 3, "member" : "lmn123", "status" : "P", "points" :  0,  "misc1" : null, "misc2" : null },
   { "_id" : 4, "member" : "pqr123", "status" : "D", "points" : 20,  "misc1" : "Deactivated", "misc2" : null },
   { "_id" : 5, "member" : "ijk123", "status" : "P", "points" :  0,  "misc1" : null, "misc2" : null },
   { "_id" : 6, "member" : "cde123", "status" : "A", "points" : 86,  "misc1" : "reminder: ping me at 100pts", "misc2" : "Some random comment" }
])

Create the following indexes on the collection:

db.members.createIndex( { status: 1 } )
db.members.createIndex( { points: 1 } )

The following update operation explicitly hints to use the index {status: 1 }:

Note

If you specify an index that does not exist, the operation errors.

db.members.updateMany(
   { "points": { $lte: 20 }, "status": "P" },
   { $set: { "misc1": "Need to activate" } },
   { hint: { status: 1 } }
)

The update command returns the following:

{ "acknowledged" : true, "matchedCount" : 3, "modifiedCount" : 3 }

To view the indexes used, you can use the $indexStats pipeline:

db.members.aggregate( [ { $indexStats: { } }, { $sort: { name: 1 } } ] )