💡 Tip and Trick: MongoDB Polymorphic & Outlier Pattern 💡

🔍 Scale:

• Cheaper
• Flexibility to scale horizontally through sharding
• Distributing data across multiple servers
• When database exceeds capacity, sharding and split it over two servers

🔍 BSON:

• Binary representation of JSON (JavaScript Object Notation) documents
• Data types: Double, String, Object, Array, Binary Data, ObjectId, Boolean, Date, Null, Regular Expression, JavaScript, 32-bit Integer, Timestamp, 64-bit Integer, Decimal128, Min Key, Max Key

🗄️ Documents:

• Grouped together in collections
• 16 megabyte size limit
• Related collections are grouped together and stored in a database

🔑 _id:

• Unique for each document in a collection
• Immutable
• Any type (cannot be array)

🤯 Challenge:

• Access data together should be stored together
• Storage is a small cost, developers are expensive
• Instead of optimizing for storage, optimize for developers’ time
• Implementing business logic
• Optimize data model for developer productivity and query optimization

🔍 Validation Option:

• Choice of throwing an error or a warning if a validation rule is violated

🤟 Embrace Document Diversity:

• Not all documents in a collection need to have the same fields

🤖 Polymorphic Pattern:

• Collections are of similar, but not identical
• Grouping documents together based on the queries
• Example:

{ "type": "singles", "titles": 167
}
{ "type": "doubles", "titles": 177, "tournaments": 233
}

🤯 Outlier Pattern:

• Solve outlier use case (a document has millions of embedding data)
• Add has_extras fields
• Create a new document where store other embedding data
• Example:

{ "author": "Ken W. Alger", "customers_purchased": ["user00", "user01"]
}
{ "author": "J.K. Rowling", "customers_purchased": ["user00", ..., "user999"], "has_extras": "true"
}

🤯 Reference:

https://www.mongodb.com/developer/products/mongodb/polymorphic-pattern/
Building with Patterns: The Polymorphic Pattern

https://www.mongodb.com/blog/post/building-with-patterns-the-outlier-pattern
Building With Patterns: The Outlier Pattern

Editor

Danny Chan, specialty of FSI and Serverless

Kenny Chan, specialty of FSI and Machine Learning