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mongoimport Examples

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Simple Import

Replace Matching Documents during Import
Merge Matching Documents during Import
Delete Matching Documents
Import JSON to Remote Host Running with Authentication
CSV Import
Learn More

This page shows examples for mongoimport.

Run mongoimport from the system command line, not the mongo shell.

Simple Import

mongoimport restores a database from a backup taken with mongoexport. Most of the arguments to mongoexport also exist for mongoimport.

In the following example, mongoimport imports the JSON data from the contacts.json file into the collection contacts in the users database.

mongoimport --db=users --collection=contacts --file=contacts.json

Replace Matching Documents during Import

With --mode upsert, mongoimport replaces existing documents in the database that match a document in the import file with the document from the import file. Documents that do not match an existing document in the database are inserted as usual. By default mongoimport matches documents based on the _id field. Use --upsertFields to specify the fields to match against.

Consider the following document in the people collection in the example database:

{
   "_id" : ObjectId("580100f4da893943d393e909"),
   "name" : "Crystal Duncan",
   "region" : "United States",
   "email" : "crystal@example.com"
}

The following document exists in a people-20160927.json JSON file. The _id field of the JSON object matches the _id field of the document in the people collection.

{
   "_id" : ObjectId("580100f4da893943d393e909"),
   "username" : "crystal",
   "likes" : [ "running", "pandas", "software development" ]
}

To import the people-20160927.json file and replace documents in the database that match the documents in the import file, specify --mode upsert, as in the following:

mongoimport -c=people -d=example --mode=upsert --file=people-20160927.json

The document in the people collection would then contain only the fields from the imported document, as in the following:

{
   "_id" : ObjectId("580100f4da893943d393e909"),
   "username" : "crystal",
   "likes" : [ "running", "pandas", "software development" ]
}

Merge Matching Documents during Import

With --mode merge, mongoimport enables you to merge fields from a new record with an existing document in the database. Documents that do not match an existing document in the database are inserted as usual. By default mongoimport matches documents based on the _id field. Use --upsertFields to specify the fields to match against.

The people collection in the example database contains the following document:

{
   "_id" : ObjectId("580100f4da893943d393e909"),
   "name" : "Crystal Duncan",
   "region" : "United States",
   "email" : "crystal@example.com"
}

The following document exists in a people-20160927.json JSON file. The _id field of the JSON object matches the _id field of the document in the people collection.

{
   "_id" : ObjectId("580100f4da893943d393e909"),
   "username" : "crystal",
   "email": "crystal.duncan@example.com",
   "likes" : [ "running", "pandas", "software development" ]
}

To import the people-20160927.json file and merge documents from the import file with matching documents in the database, specify --mode merge, as in the following:

mongoimport -c=people -d=example --mode=merge --file=people-20160927.json

The import operation combines the fields from the JSON file with the original document in the database, matching the documents based on the _id field. During the import process, mongoimport adds the new username and likes fields to the document and updates the email field with the value from the imported document, as in the following:

{
   "_id" : ObjectId("580100f4da893943d393e909"),
   "name" : "Crystal Duncan",
   "region" : "United States",
   "email" : "crystal.duncan@example.com",
   "username" : "crystal",
   "likes" : [
      "running",
      "pandas",
      "software development"
   ]
}

Delete Matching Documents

New in version 100.0.0.

With --mode delete, mongoimport deletes existing documents in the database that match a document in the import file. Documents that do not match an existing document in the database are ignored. By default mongoimport matches documents based on the _id field. Use --upsertFields to specify the fields to match against.

Note

With --mode delete, mongoimport only deletes one existing document per match. Ensure that documents from the import file match a single existing document from the database.

The people collection in the example database contains the following document:

{
   "_id" : ObjectId("580100f4da893943d393e909"),
   "name" : "Crystal Duncan",
   "region" : "United States",
   "email" : "crystal@example.com",
   "employee_id" : "5463789356"
}

The following document exists in a people-20160927.json JSON file. The _id field of the JSON object matches the _id field of the document in the people collection.

{
   "_id" : ObjectId("580100f4da893943d393e909"),
   "username" : "crystal",
   "email": "crystal.duncan@example.com",
   "likes" : [ "running", "pandas", "software development" ],
   "employee_id" : "5463789356"
}

To delete the documents in the database that match a document in the people-20160927.json file, specify --mode delete, as in the following:

mongoimport -c=people -d=example --mode=delete --file=people-20160927.json

Because the _id fields match between the database and the input file, mongoimport deletes the matching document from the people collection. The same results could also have been achieved by using --upsertFields to specify the employee_id field, which also matches between the database and the input file.

Import `JSON` to Remote Host Running with Authentication

In the following example, mongoimport imports data from the file /opt/backups/mdb1-examplenet.json into the contacts collection within the database marketing on a remote MongoDB database with authentication enabled.

mongoimport connects to the mongod instance running on the host mongodb1.example.net over port 37017. It authenticates with the username user; the example omits the --password option to have mongoimport prompt for the password:

mongoimport --host=mongodb1.example.net --port=37017 --username=user --collection=contacts --db=marketing --file=/opt/backups/mdb1-examplenet.json

`CSV` Import

General CSV Import

In the following example, mongoimport imports the CSV formatted data in the /opt/backups/contacts.csv file into the collection contacts in the users database on the MongoDB instance running on the localhost port numbered 27017.

Specifying --headerline instructs mongoimport to determine the name of the fields using the first line in the CSV file.

mongoimport --db=users --collection=contacts --type=csv --headerline --file=/opt/backups/contacts.csv

mongoimport uses the input file name, without the extension, as the collection name if -c or --collection is unspecified. The following example is therefore equivalent:

mongoimport --db=users --type=csv --headerline --file=/opt/backups/contacts.csv

Import CSV with Specified Field Types

When specifying the field name, you can also specify the data type. To specify field names and type, include --columnsHaveTypes with either: --fields, --fieldFile, or --headerline.

Specify field names and data types in the form <colName>.<type>(<arg>).

For example, /example/file.csv contains the following data:

Katherine Gray, 1996-02-03, false, 1235, 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
Albert Gilbert, 1992-04-24, true, 13, 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

The following operation uses mongoimport with the --fields and --columnsHaveTypes option to specify both the field names and the BSON types of the imported CSV data.

mongoimport --db=users --collection=contacts --type=csv \
   --columnsHaveTypes \
   --fields="name.string(),birthdate.date(2006-01-02),contacted.boolean(),followerCount.int32(),thumbnail.binary(base64)" \
   --file=/example/file.csv

Ignore Blank Fields

Use the --ignoreBlanks option to ignore blank fields. For CSV and TSV imports, this option provides the desired functionality in most cases because it avoids inserting fields with null values into your collection.

The following example imports the data from data.csv, skipping any blank fields:

mongoimport --db=users --collection=contacts --type=csv --file=/example/data.csv --ignoreBlanks

Connect to a MongoDB Atlas Cluster using AWS IAM Credentials

New in version 100.1.0.

To connect to a MongoDB Atlas cluster which has been configured to support authentication via AWS IAM credentials, provide a connection string to mongoimport similar to the following:

mongoimport 'mongodb+srv://<aws access key id>:<aws secret access key>@cluster0.example.com/testdb?authSource=$external&authMechanism=MONGODB-AWS' <other options>

Connecting to Atlas using AWS IAM credentials in this manner uses the MONGODB-AWS authentication mechanism and the $external authSource, as shown in this example.

If using an AWS session token, as well, provide it with the AWS_SESSION_TOKEN authMechanismProperties value, as follows:

mongoimport 'mongodb+srv://<aws access key id>:<aws secret access key>@cluster0.example.com/testdb?authSource=$external&authMechanism=MONGODB-AWS&authMechanismProperties=AWS_SESSION_TOKEN:<aws session token>' <other options>

Note

If the AWS access key ID, secret access key, or session token include the following characters:

: / ? # [ ] @

those characters must be converted using percent encoding.

Alternatively, the AWS access key ID, secret access key, and optionally session token can each be provided outside of the connection string using the --username, --password, and --awsSessionToken options instead, like so:

mongoimport 'mongodb+srv://cluster0.example.com/testdb?authSource=$external&authMechanism=MONGODB-AWS' --username <aws access key id> --password <aws secret access key> --awsSessionToken <aws session token> <other options>

When provided as command line parameters, these three options do not require percent encoding.

You may also set these credentials on your platform using standard AWS IAM environment variables. mongoimport checks for the following environment variables when you use the MONGODB-AWS authentication mechanism:

AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY
AWS_SESSION_TOKEN

If set, these credentials do not need to be specified in the connection string or via their explicit options.

Note

If you chose to use the AWS environment variables to specify these values, you cannot mix and match with the corresponding explicit or connection string options for these credentials. Either use the environment variables for access key ID and secret access key (and session token if used), or specify each of these using the explicit or connection string options instead.

The following example sets these environment variables in the bash shell:

export AWS_ACCESS_KEY_ID='<aws access key id>'
export AWS_SECRET_ACCESS_KEY='<aws secret access key>'
export AWS_SESSION_TOKEN='<aws session token>'

Other shells use different syntax to set environment variables. Consult the documentation for your platform for more information.

You can verify that these environment variables have been set with the following command:

env | grep AWS

Once set, the following example connects to a MongoDB Atlas cluster using these environment variables:

mongoimport 'mongodb+srv://cluster0.example.com/testdb?authSource=$external&authMechanism=MONGODB-AWS'  <other options>

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Simple Import

Replace Matching Documents during Import

Merge Matching Documents during Import

Delete Matching Documents

Note

Import JSON to Remote Host Running with Authentication

CSV Import

General CSV Import

Import CSV with Specified Field Types

Ignore Blank Fields

Connect to a MongoDB Atlas Cluster using AWS IAM Credentials

Note

Note

Learn More

mongoimport Examples

Import `JSON` to Remote Host Running with Authentication

`CSV` Import