Avoid Unbounded Arrays¶

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Overview
Example
Learn More

Overview¶

One of the benefits of MongoDB’s rich schema model is the ability to store arrays as document field values. Storing arrays as field values allows you to model one-to-many or many-to-many relationships in a single document, instead of across separate collections as you might in a relational database.

However, you should exercise caution if you are consistently adding elements to arrays in your documents. If you do not limit the number of elements in an array, your documents may grow to an unpredictable size. As an array continues to grow, reading and building indexes on that array gradually decrease in performance. A large, growing array can strain application resources and put your documents at risk of exceeding the BSON Document Size limit.

Instead, consider bounding your arrays to improve performance and keep your documents a manageable size.

Example¶

Consider the following schema for a publishers collection:

copy

// publishers collection
{
  "_id": "orielly"
  "name": "O'Reilly Media",
  "founded": 1980,
  "location": "CA",
  "books": [
    {
      "_id": 123456789,
      "title": "MongoDB: The Definitive Guide",
      "author": [ "Kristina Chodorow", "Mike Dirolf" ],
      "published_date": ISODate("2010-09-24"),
      "pages": 216,
      "language": "English"
    },
    {
      "_id": 234567890,
      "title": "50 Tips and Tricks for MongoDB Developer",
      "author": "Kristina Chodorow",
      "published_date": ISODate("2011-05-06"),
      "pages": 68,
      "language": "English"
    }
  ]
}

In this scenario, the books array is unbounded. Each new book released by this publishing company adds a new sub-document to the books array. As publishing companies continue to release books, the documents will eventually grow very large and cause a disproportionate amount of memory strain on the application.

To avoid mutable, unbounded arrays, separate the publishers collection into two collections, one for publishers and one for books. Instead of embedding the entire book document in the publishers document, include a reference to the publisher inside of the book document:

copy

// publishers collection
{
  "_id": "oreilly"
  "name": "O'Reilly Media",
  "founded": 1980,
  "location": "CA"
}

copy

// books collection
{
  "_id": 123456789,
  "title": "MongoDB: The Definitive Guide",
  "author": [ "Kristina Chodorow", "Mike Dirolf" ],
  "published_date": ISODate("2010-09-24"),
  "pages": 216,
  "language": "English",
  "publisher_id": "oreilly"
}

{
  "_id": 234567890,
  "title": "50 Tips and Tricks for MongoDB Developer",
  "author": "Kristina Chodorow",
  "published_date": ISODate("2011-05-06"),
  "pages": 68,
  "language": "English",
  "publisher_id": "oreilly"
}

This updated schema removes the unbounded array in the publishers collection and places a reference to the publisher in each book document using the publisher_id field. This ensures that each document has a manageable size, and there is no risk of a document field growing abnormally large.

Document References May Require `$lookups`¶

This approach works especially well if your application loads the book and publisher information separately. If your application requires the book and information together, it needs to perform a $lookup operation to join the data from the publishers and books collections. $lookup operations are not very performant, but in this scenario may be worth the trade off to avoid unbounded arrays.

Learn More¶

To learn more about Data Modeling in MongoDB and the flexible schema model, see Data Modeling Introduction.
To learn how to model relationships with document references, see Model One-to-Many Relationships with Document References
To learn how to query arrays in MongoDB, see Query an Array.
MongoDB also offers a free MongoDB University Course on Data Modeling: M320: Data Modeling.

MongoDB.live 2020 Presentations¶

To learn how to incorporate the flexible data model into your schema, see the following presentations from MongoDB.live 2020:

Learn about entity relationships in MongoDB and examples of their implementations with Data Modeling with MongoDB.
Learn advanced data modeling design patterns you can incorporate into your schema with Advanced Schema Design Patterns.

← Reduce $lookup Operations Remove Unnecessary Indexes →

Avoid Unbounded Arrays¶

Overview¶

Example¶

Document References May Require $lookups¶

Learn More¶

MongoDB.live 2020 Presentations¶

Document References May Require `$lookups`¶