OPTIONS

db.collection.insertMany()

Definition

db.collection.insertMany()

New in version 3.2.

Inserts multiple documents into a collection.

The insertMany() method has the following syntax:

db.collection.insertMany(
   { [ <document 1> , <document 2>, ... ] },
   {
      writeConcern: <document>,
      ordered: <boolean>
   }
)
Parameter Type Description
document document An array of documents to insert into the collection.
writeConcern document Optional. A document expressing the write concern. Omit to use the default write concern.
ordered boolean Optional. A boolean specifying whether the mongod instance should perform an ordered or unordered insert. Defaults to true.
Returns:A document containing:
  • A boolean acknowledged as true if the operation ran with write concern or false if write concern was disabled
  • An array of _id for each successfully inserted documents

Behaviors

Given an array of documents, insertMany() inserts each document in the array into the collection.

Execution of Operations

By default documents are inserted in order.

If ordered is set to false, documents are inserted in an unordered format and may be reordered by mongod to increase performance. Applications should not depend on ordering of inserts if using an unordered insertMany().

Each group of operations can have at most 1000 operations. If a group exceeds this limit, MongoDB will divide the group into smaller groups of 1000 or less. For example, if the queue consists of 2000 operations, MongoDB creates 2 groups, each with 1000 operations.

The sizes and grouping mechanics are internal performance details and are subject to change in future versions.

Executing an ordered list of operations on a sharded collection will generally be slower than executing an unordered list since with an ordered list, each operation must wait for the previous operation to finish.

Collection Creation

If the collection does not exist, then insertMany() creates the collection on successful write.

_id Field

If the document does not specify an _id field, then mongod adds the _id field and assign a unique ObjectId for the document. Most drivers create an ObjectId and insert the _id field, but the mongod will create and populate the _id if the driver or application does not.

If the document contains an _id field, the _id value must be unique within the collection to avoid duplicate key error.

Explainability

insertMany() is not compatible with db.collection.explain().

Use insert() instead.

Error Handling

Inserts throw a BulkWriteError exception.

Excluding Write Concern errors, ordered operations stop after an error, while unordered operations continue to process any remaining write operations in the queue.

Write concern errors are displayed in the writeConcernErrors field, while all other errors are displayed in the writeErrors field. If an error is encountered, the number of successful write operations are displayed instead of a list of inserted _ids. Ordered operations display the single error encountered while unordered operations display each error in an array.

Examples

The following examples insert documents into the products collection.

Insert Several Document without Specifying an _id Field

The following example uses db.collection.insertMany() to insert documents that do not contain the _id field:

try {
   db.products.insertMany( [
      { item: "card", qty: 15 },
      { item: "envelope", qty: 20 },
      { item: "stamps" , qty: 30 }
   ] );
} catch (e) {
   print (e);
}

The operation returns the following document:

{
   "acknowledged" : true,
   "insertedIds" : [
      ObjectId("562a94d381cb9f1cd6eb0e1a"),
      ObjectId("562a94d381cb9f1cd6eb0e1b"),
      ObjectId("562a94d381cb9f1cd6eb0e1c")
   ]
}

Because the documents did not include _id, mongod creates and adds the _id field for each document and assigns it a unique ObjectId value.

The ObjectId values are specific to the machine and time when the operation is run. As such, your values may differ from those in the example.

Insert Several Document Specifying an _id Field

The following example/operation uses insertMany() to insert documents that include the _id field. The value of _id must be unique within the collection to avoid a duplicate key error.

try {
   db.products.insertMany( [
      { _id: 10, item: "large box", qty: 20 },
      { _id: 11, item: "small box", qty: 55 },
      { _id: 12, item: "medium box", qty: 30 }
   ] );
} catch (e) {
   print (e);
}

The operation returns the following document:

{ "acknowledged" : true, "insertedIds" : [ 10, 11, 12 ] }

Inserting a duplicate value for any key that is part of a unique index, such as _id, throws an exception. The following attempts to insert a document with a _id value that already exists:

try {
   db.products.insertMany( [
      { _id: 13, item: "envelopes", qty: 60 },
      { _id: 13, item: "stamps", qty: 110 },
      { _id: 14, item: "packing tape", qty: 38 }
   ] );
} catch (e) {
   print (e);
}

Since _id: 13 already exists, the following exception is thrown:

BulkWriteError({
   "writeErrors" : [
      {
         "index" : 0,
         "code" : 11000,
         "errmsg" : "E11000 duplicate key error collection: restaurant.test index: _id_ dup key: { : 13.0 }",
         "op" : {
            "_id" : 13,
            "item" : "envelopes",
            "qty" : 60
         }
      }
   ],
   "writeConcernErrors" : [ ],
   "nInserted" : 0,
   "nUpserted" : 0,
   "nMatched" : 0,
   "nModified" : 0,
   "nRemoved" : 0,
   "upserted" : [ ]
})

Note that one document was inserted: The first document of _id: 13 will insert successfully, but the second insert will fail. This will also stop additional documents left in the queue from being inserted.

With ordered to false, the insert operation would continue with any remaining documents.

Unordered Inserts

The following attempts to insert multiple documents with _id field and ordered: false. The array of documents contains two documents with duplicate _id fields.

try {
   db.products.insertMany( [
      { _id: 10, item: "large box", qty: 20 },
      { _id: 11, item: "small box", qty: 55 },
      { _id: 11, item: "medium box", qty: 30 },
      { _id: 12, item: "envelope", qty: 100},
      { _id: 13, item: "stamps", qty: 125 },
      { _id: 13, item: "tape", qty: 20},
      { _id: 14, item: "bubble wrap", qty: 30}
   ], { ordered: false } );
} catch (e) {
   print (e);
}

The operation throws the following exception:

BulkWriteError({
   "writeErrors" : [
      {
         "index" : 2,
         "code" : 11000,
         "errmsg" : "E11000 duplicate key error collection: inventory.products index: _id_ dup key: { : 11.0 }",
         "op" : {
            "_id" : 11,
            "item" : "medium box",
            "qty" : 30
         }
      },
      {
         "index" : 5,
         "code" : 11000,
         "errmsg" : "E11000 duplicate key error collection: inventory.products index: _id_ dup key: { : 13.0 }",
         "op" : {
            "_id" : 13,
            "item" : "tape",
            "qty" : 20
         }
      }
   ],
   "writeConcernErrors" : [ ],
   "nInserted" : 5,
   "nUpserted" : 0,
   "nMatched" : 0,
   "nModified" : 0,
   "nRemoved" : 0,
   "upserted" : [ ]
})

While the document with item: "medium box" and item: "tape" failed to insert due to duplicate _id values, nInserted shows that the remaining 5 documents were inserted.

Using Write Concern

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

try {
   db.products.insertMany(
      [
         { _id: 10, item: "large box", qty: 20 },
         { _id: 11, item: "small box", qty: 55 },
         { _id: 12, item: "medium box", qty: 30 }
      ],
      { w: "majority", wtimeout: 100 }
   );
} catch (e) {
   print (e);
}

If the primary and at least one secondary acknowledge each write operation within 100 milliseconds, it returns:

{
  "acknowledged" : true,
  "insertedIds" : [
     ObjectId("562a94d381cb9f1cd6eb0e1a"),
     ObjectId("562a94d381cb9f1cd6eb0e1b"),
     ObjectId("562a94d381cb9f1cd6eb0e1c")
  ]
}

If the total time required for all required nodes in the replica set to acknowledge the write operation is greater than wtimeout, the following writeConcernError is displayed when the wtimeout period has passed.

This operation returns:

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