db.collection.insertMany()

Execution of Operations

By default, documents are inserted in the order they are provided.

If ordered is set to true and an insert fails, the server does not continue inserting records.

If ordered is set to false and an insert fails, the server continues inserting records. Documents 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. The default value of maxWriteBatchSize is 100,000. This value is shown in the hello.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.

If the error report for a single batch grows too large, MongoDB truncates all remaining error messages to the empty string. If there are at least two error messages with total size greater than 1MB, they are trucated.

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().

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() can be used inside distributed transactions.

Performance Consideration for Random Data

If an operation inserts a large amount of random data (for example, hashed indexes) on an indexed field, insert performance may decrease. Bulk inserts of random data create random index entries, which increase the size of the index. If the index reaches the size that requires each random insert to access a different index entry, the inserts result in a high rate of WiredTiger cache eviction and replacement. When this happens, the index is no longer fully in cache and is updated on disk, which decreases performance.

To improve the performance of bulk inserts of random data on indexed fields, you can either:

• Drop the index, then recreate it after you insert the random data.

• Insert the data into an empty unindexed collection.

Creating the index after the bulk insert sorts the data in memory and performs an ordered insert on all indexes.

Oplog Entries

If a db.collection.insertMany() operation successfully inserts one or more documents, the operation adds an entry on the oplog (operations log) for each inserted document. If the operation fails, the operation does not add an entry on the oplog.

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