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db.collection.deleteMany()

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  • Definition
  • Compatibility
  • Syntax
  • Behavior
  • Examples
db.collection.deleteMany()

MongoDB with drivers

This page documents a mongosh method. To see the equivalent method in a MongoDB driver, see the corresponding page for your programming language:

C#Java SyncNode.jsPyMongoCC++GoJava RSKotlin CoroutineKotlin SyncPHPMongoidRustScala

Removes all documents that match the filter from a collection.

Returns:A document containing:
  • A boolean acknowledged as true if the operation ran with write concern or false if write concern was disabled

  • deletedCount containing the number of deleted documents

Note

If you are deleting all documents in a large collection, it may be faster to drop the collection and recreate it. Before dropping the collection, note all indexes on the collection. You must recreate any indexes that existed in the original collection. If the original collection was sharded, you must also shard the recreated collection.

For more information on dropping a collection, see db.collection.drop().

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

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

The deleteMany() method has the following syntax:

db.collection.deleteMany(
<filter>,
{
writeConcern: <document>,
collation: <document>
}
)
Parameter
Type
Description
document

Specifies deletion criteria using query operators.

To delete all documents in a collection, pass in an empty document ({ }).

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.

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.

document

Optional. A document or string that specifies the index to use to support the query predicate.

The option can take an index specification document or the index name string.

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

For an example, see Specify hint for Delete Operations.

db.collection.deleteMany() throws a WriteError exception if used on a time series collection. To remove all documents from a time series collection, use db.collection.drop().

To delete a single document, use db.collection.deleteOne() instead.

Alternatively, use a field that is a part of a unique index such as _id.

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

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.

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.

db.collection.deleteMany() deletes documents one at a time. If the primary node fails during a db.collection.deleteMany() operation, documents that were not yet deleted from secondary nodes are not deleted from the collection.

If a db.collection.deleteMany() operation successfully deletes one or more documents, the operation adds an entry for each deleted document on the oplog (operations log). If the operation fails or does not find any documents to delete, the operation does not add an entry on the oplog.

The orders collection has documents with the following structure:

db.orders.insertOne(
{
_id: ObjectId("563237a41a4d68582c2509da"),
stock: "Brent Crude Futures",
qty: 250,
type: "buy-limit",
limit: 48.90,
creationts: ISODate("2015-11-01T12:30:15Z"),
expiryts: ISODate("2015-11-01T12:35:15Z"),
client: "Crude Traders Inc."
}
)

The following operation deletes all documents where client : "Crude Traders Inc.":

try {
db.orders.deleteMany( { "client" : "Crude Traders Inc." } );
} catch (e) {
print (e);
}

The operation returns:

{ "acknowledged" : true, "deletedCount" : 10 }

The following operation deletes all documents where stock : "Brent Crude Futures" and limit is greater than 48.88:

try {
db.orders.deleteMany( { "stock" : "Brent Crude Futures", "limit" : { $gt : 48.88 } } );
} catch (e) {
print (e);
}

The operation returns:

{ "acknowledged" : true, "deletedCount" : 8 }

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

try {
db.orders.deleteMany(
{ "client" : "Crude Traders Inc." },
{ writeConcern: { w : "majority", wtimeout : 100 }}
);
} catch (e) {
print (e);
}

If the acknowledgment takes longer than the wtimeout limit, the following exception is thrown:

WriteConcernError({
"code" : 64,
"errmsg" : "waiting for replication timed out",
"errInfo" : {
"wtimeout" : true,
"writeConcern" : {
"w" : "majority",
"wtimeout" : 100,
"provenance" : "getLastErrorDefaults"
}
}
})

Tip

See also:

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

A collection restaurants has the following documents:

db.restaurants.insertMany( [
{ _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.restaurants.deleteMany(
{ category: "cafe", status: "A" },
{ collation: { locale: "fr", strength: 1 } }
)

In mongosh, create a 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 delete operation explicitly hints to use the index { status: 1 }:

db.members.deleteMany(
{ "points": { $lte: 20 }, "status": "P" },
{ hint: { status: 1 } }
)

Note

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

The delete command returns the following:

{ "acknowledged" : true, "deletedCount" : 3 }

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

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

The accesses.ops field in the $indexStats output indicates the number of operations that used the index.

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