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Schema.md

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MongoDB Schema Definitions

This document details how schema definitions are managed in this system. These definitions are expressed in YAML format and provide the basis for the data structure of each collection in the MongoDB database.

Schema Definition Files

Each collection has its own schema definition file. This file contains the field definitions and validation rules for the data in the collection.

The schema definition file is structured as follows:

collectionName:
  fieldName:
    type: dataType
    required: true/false
    unique: true/false
  anotherFieldName:
    type: dataType
    required: true/false
    ...

For example:

users:
  username:
    type: String
    required: true
    unique: true
  email:
    type: String
    required: true
    unique: true

The type field specifies the data type of the field, e.g., String, Number, Date, Array, etc.

The required field specifies whether this field must be present in every document in the collection.

The unique field specifies whether the value of this field must be unique across the collection.

Handling Schema Changes

Schema changes are handled through the CLI tool. When a schema definition file is modified, the CLI tool is used to apply the changes to the MongoDB database.

Here's a PlantUML sequence diagram that shows the flow of handling schema changes:

@startuml
actor Developer
participant "CLI Tool" as C
database "MongoDB" as M

Developer -> C: Run CLI tool with new schema files
C -> C: Read and parse new schema definitions from YAML files
C -> M: Connect to MongoDB
C -> M: Fetch current schemas
C -> C: Check compatibility between old and new schemas
alt if schemas are compatible
    C -> M: Apply new schema changes
else
    C -> C: Throw error
end
Developer <- C: Receive operation status
@enduml

In this diagram, the developer initiates the schema update process by running the CLI tool. The tool reads the new schema definitions, connects to MongoDB, fetches the current schemas, and checks the compatibility. If the new schemas are compatible, they are applied to the database. The operation status is then communicated back to the developer.

This approach allows us to safely manage schema changes and avoid potential issues with data compatibility or loss.