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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.

Do not explicitly set the write concern for the operation if run in a transaction. To use write concern with transactions, see Transaction Options (Read Concern/Write Concern/Read Preference).

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().

The number of operations in each group cannot exceed the value of the maxWriteBatchSize of the database. As of MongoDB 3.6, this value is 100,000. This value is shown in the isMaster.maxWriteBatchSize field.

This limit prevents issues with oversized error messages. If a group exceeds this limit, the client driver divides the group into smaller groups with counts less than or equal to the value of the limit. For example, with the maxWriteBatchSize value of 100,000, if the queue consists of 200,000 operations, the driver creates 2 groups, each with 100,000 operations.

Note

The driver only divides the group into smaller groups when using the high-level API. If using db.runCommand() directly (for example, when writing a driver), MongoDB throws an error when attempting to execute a write batch which exceeds the limit.

Starting in MongoDB 3.6, once the error report for a single batch grows too large, MongoDB truncates all remaining error messages to the empty string. Currently, begins once there are at least 2 error messages with total size greater than 1MB.

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.

Transactions

db.collection.insertMany() supports multi-document transactions.

The collection must already exist. An insert operation that would result in the creation of a new collection are not allowed in a transaction.

Do not explicitly set the write concern for the operation if run in a transaction. To use write concern with transactions, see Transaction Options (Read Concern/Write Concern/Read Preference).

Important

In most cases, multi-document transaction incurs a greater performance cost over single document writes, and the availability of multi-document transaction 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 multi-document transactions.

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: inventory.products index: _id_ dup key: { : 13.0 }",
         "op" : {
            "_id" : 13,
            "item" : "stamps",
            "qty" : 110
         }
      }
   ],
   "writeConcernErrors" : [ ],
   "nInserted" : 1,
   "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"
})