brylie
commented
1 year ago We aim to create a flattened Activities table (ResidentActivity) for more efficient data aggregation and visualization in our Django-based caregiving project. This table should synchronize with the main Activity table and related entities. Our current challenge involves deciding on the most effective method to achieve this synchronization.
Proposed Solutions and Their Trade-offs:
1. Django Signals
- Pros:
- Automatic Sync: Ensures the ResidentActivity table is automatically updated with changes in the Activity table.
- Decoupling: The logic for updating the flat table is separate from the main application logic, providing a cleaner architecture.
- Cons:
- Complexity in Debugging: Signals can be challenging to trace, making debugging more complex.
- Performance Overhead: May introduce additional database operations, potentially impacting performance.
2. Custom Transactions in Model Save Method
- Pros:
- Immediate Consistency: Guarantees data consistency as both tables are updated in the same transaction.
- Control: Offers more direct control over data updates.
- Cons:
- Tight Coupling: Intertwines main data operations with analytics logic, which can be less maintainable.
- Risk of Long Transactions: Could lead to performance issues due to extended transaction times.
3. Asynchronous Tasks with Celery
- Pros:
- Asynchronous Processing: Enhances web application performance by handling updates in the background.
- Scalability: Facilitates horizontal scaling of the data processing workload.
- Cons:
- Infrastructure Overhead: Requires additional setup for task queues and worker management.
- Potential Delay: As the process is asynchronous, there might be a delay in reflecting data changes.
adrienneli104
Overview
Our current Activity data model, while robust, presents challenges in generating charts and reports due to its complex relationships, particularly the ManyToMany relationship between Residents and Activities. To streamline data aggregation and improve performance, we propose creating a new Django application,
metrics, featuring a more efficient data model.Proposed Model: ResidentActivity
resident: ForeignKey(Resident)activity: ForeignKey(Activity)residency: ForeignKey(Residency) - Linking Resident and Home at the activity timehome: ForeignKey(Home) - Derived from residencyactivity_type: stringactivity_minutes: intcaregiver_role: strSynchronization with Activity Model
Ensuring data consistency between the Activity and ResidentActivity models is critical. We are considering two approaches:
Custom Django Model Manager:
Django Signals:
Task Breakdown
metricsApp: Develop the new Django application within our project.Next Steps
Once the metrics application and ResidentActivity model are established, we will focus on defining specific metrics and developing visualizations to support caregiving in elder care communities.
Conclusion
This initiative aims to enhance our data handling capabilities, making it easier to generate meaningful insights and reports. The success of this implementation will lay the groundwork for advanced analytics in our caregiving project.