DZone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
Refcards Trend Reports
Events Video Library
Over 2 million developers have joined DZone. Join Today! Thanks for visiting DZone today,
Edit Profile Manage Email Subscriptions Moderation Admin Console How to Post to DZone Article Submission Guidelines
View Profile
Sign Out
Refcards
Trend Reports
Events
View Events Video Library
Zones
Culture and Methodologies Agile Career Development Methodologies Team Management
Data Engineering AI/ML Big Data Data Databases IoT
Software Design and Architecture Cloud Architecture Containers Integration Microservices Performance Security
Coding Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks
Culture and Methodologies
Agile Career Development Methodologies Team Management
Data Engineering
AI/ML Big Data Data Databases IoT
Software Design and Architecture
Cloud Architecture Containers Integration Microservices Performance Security
Coding
Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks

Migrate, Modernize and Build Java Web Apps on Azure: This live workshop will cover methods to enhance Java application development workflow.

Modern Digital Website Security: Prepare to face any form of malicious web activity and enable your sites to optimally serve your customers.

Kubernetes in the Enterprise: The latest expert insights on scaling, serverless, Kubernetes-powered AI, cluster security, FinOps, and more.

A Guide to Continuous Integration and Deployment: Learn the fundamentals and understand the use of CI/CD in your apps.

Related

  • Web Page Accessibility Checker: Everything You Need to Know
  • Building A Simple AI Application in 2023 for Fun and Profit
  • What’s Coming to CSS in 2023-2024?
  • Exploring the Role of Consensus Algorithms in Distributed System Design

Trending

  • Introducing the Apache JMeter Docker Extension
  • A Roadmap to True Observability
  • An In-Depth Exploration of REST, gRPC, and GraphQL in Web Projects
  • Amazon EC2 Deep Dive: Optimizing Workloads With Hardware Insights
  1. DZone
  2. Data Engineering
  3. Databases
  4. MongoDB Design Patterns

MongoDB Design Patterns

MongoDB is a versatile tool, but it's not perfect for everything. For situations where it doesn't work, you can sometimes use design patterns to get around them.

Darel Lasrado user avatar by
Darel Lasrado
·
Jun. 15, 16 · Tutorial
Like (11)
Save
Tweet
Share
18.3K Views

Join the DZone community and get the full member experience.

Join For Free

MongoDB is a NoSQL document database. It's ideal for most use cases, and where it doesn't work, you can still overcome some of its limitations by using the following design patterns.

This article provides a solution for some of the limitations mentioned in my other article MongoDB : The Good, The Bad, and the Ugly.

1. Query Command Segregation Pattern

Segregate responsibility to different nodes in the replica set. The primary node may have priority 1 and may keep only indexes required for insert and update. The queries can be executed on secondaries. This pattern will increase write throughput on the “priority 1” servers because fewer indexes need to be updated and inserted on writing to a collection and secondaries benefit from having to update fewer indexes and having a working set of memory that is optimized for their workload

2. Application-Level Transactions Pattern

MongoDB does not support transactions and locking documents internally. However, with application logic, a queue may be maintained.

db.queue.insert( { _id : 123,
    message : { },
    locked : false,
    tlocked : ISODate(),
    try : 0 });
var timerange = date.Now() - TIMECONSTANT;
var doc = db.queue.findAndModify( { $or : [ { locked : false }, { locked : true, tlocked : {
$lt : timerange } } ], { $set : { locked : true, tlocked : date.Now(), $inc : { try : 1 } } }
);
//do some processing
db.queue.update( { _id : 123, try : doc.try }, { } );

3. Bucketing Pattern

When the document has an array that grows over the period of time, use the bucketing pattern. Example: Orders. The order lines can grow or may be larger than the desired size of the document. The pattern is handled programmatically and is triggered using a tolerance count.

var TOLERANCE = 100;
    for( recipient in msg.to) {
        db.inbox.update( {
            owner: msg.to[recipient], count: { $lt : TOLERANCE }, time : { $lt : Date.now() } },
{ $setOnInsert : { owner: msg.to[recipient], time : Date.now() },
{ $push: { "messages": msg }, $inc : { count : 1 } },
{ upsert: true } );


4. Relationship Pattern

Sometimes it's not feasible to embed entire document — for example, when we are modeling people. Use this pattern to build relationships.

  1. Determine if data "belongs to" a document — is there a relation?

  2. Embed when possible, especially if the data is useful and exclusive ("belongs in").

  3. Always reference _id values at minimum.

  4. Denormalize the useful parts of the relationship. Good candidates do not change value often, or ever, and are useful.

  5. Be mindful of updates to denormalized data and repair relationships

{
    _id : 1,
    name : ‘Sam Smith’,
    bio : ‘Sam Smith is a nice guy’,
    best_friend : { id : 2, name : ‘Mary Reynolds’ },
    hobbies : [ { id : 100, n :’Computers’ }, { id : 101, n : ‘Music’ } ]
}
{
    _id : 2,
    name : ‘Mary Reynolds’
    bio : ‘Mary has composed documents in MongoDB’,
    best_friend : { id : 1, name : ‘Sam Smith’ },
    hobbies : [ { id : 101, n : ‘Music’ } ]
}

5. Materialized Path Pattern


If you have a tree pattern of data model where the same object type is a child of an object, you can use the materialized path pattern for more efficient search/queries. A sample is given below.



{ _id: "Books", path: null }
{ _id: "Programming", path: ",Books," }
{ _id: "Databases", path: ",Books,Programming," }
{ _id: "Languages", path: ",Books,Programming," }
{ _id: "MongoDB", path: ",Books,Programming,Databases," }
{ _id: "dbm", path: ",Books,Programming,Databases," } 

Query to retrieve the whole tree, sorting by the field path:
    db.collection.find().sort( { path: 1 } )
Use regular expressions on the path field to find the descendants of Programming:
    db.collection.find( { path: /,Programming,/ } )
Retrieve the descendants of Books where the Books is the top parent:
    db.collection.find( { path: /^,Books,/ } )

Related Refcard:

MongoDB

MongoDB Design

Published at DZone with permission of Darel Lasrado. See the original article here.

Opinions expressed by DZone contributors are their own.

Related

  • Web Page Accessibility Checker: Everything You Need to Know
  • Building A Simple AI Application in 2023 for Fun and Profit
  • What’s Coming to CSS in 2023-2024?
  • Exploring the Role of Consensus Algorithms in Distributed System Design

Comments

Partner Resources

X

ABOUT US

  • About DZone
  • Send feedback
  • Careers
  • Sitemap

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • Become a Contributor
  • Core Program
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 3343 Perimeter Hill Drive
  • Suite 100
  • Nashville, TN 37211
  • support@dzone.com

Let's be friends: