Template Reconciliation via Batch Processing and Segmentation
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Solution Overview
Problem
Existing methods for modifying email templates in digital marketing systems consume excessive computing power and resources due to frequent, bit-by-bit changes and unnecessary deletion/recreation of template data, leading to slowed network and system performance.
Innovation Solution
A template management system that continuously receives modification requests and applies minimal necessary operations to the relational database upon a triggering event, comparing the original template with the updated version to synchronize changes efficiently, eliminating redundant operations and improving system agility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the server immediately sends a request to change the template data in the database for every modification, then the template is updated in real-time, but the computing power consumption increases substantially and system performance slows down
Solution Approach 1:
The system transitions from continuous real-time updates to periodic batch processing. Modification requests are accumulated and processed together in batches, reducing the frequency of database operations from every individual change to periodic consolidated updates, thereby significantly lowering computing power consumption while maintaining update functionality.
Solution Approach 2:
Multiple individual modification requests are merged into a single batch processing operation. Instead of handling each modification separately with immediate database updates, the system combines multiple requests and applies them collectively in one operation, reducing the total number of server processing cycles and improving system performance.
2Reliability
If the server deletes the previous version of the template data and rewrites it with new data, then the template is completely updated, but unnecessary computing resources are consumed by complete deletion and recreation
Solution Approach 1:
The template data is segmented into individual components or fields that can be updated independently. Instead of deleting and recreating the entire template data structure, the system identifies and updates only the specific segments that have changed, reducing computing resource consumption while maintaining data accuracy through targeted modifications.
Solution Approach 2:
The system discards only the unnecessary portions of the template data that need changes, while recovering and retaining the unchanged portions. This selective update approach replaces the complete deletion and recreation process, conserving computing resources by preserving valid data structures and only modifying what is necessary.
3Loss of time
If the system processes every modification request immediately, then all changes are applied without delay, but the system becomes less efficient and more redundant operations are executed
Solution Approach 1:
The system performs preliminary actions by buffering and accumulating modification requests before processing them. Modification requests are stored in a queue or buffer and processed together in batches when ready, allowing the system to prepare changes in advance without immediately executing them, thereby improving efficiency while maintaining timely updates.
Solution Approach 2:
The system maintains continuous accumulation of modification requests while processing them in efficient batches. Instead of stopping to process each request immediately (which causes redundancy), the system continuously collects changes and processes them continuously in optimized batches, maintaining useful action continuity while eliminating redundant processing operations.
Data Source
AI summary
Methods and systems for improved and efficient template reconciliation are disclosed. By comparing the original template with the proposed modified template, the template management system can determine the minimally necessary modifications in a relational database to implement all changes and automatically generate scripts to update the template in a short amount of time. The present subject can improve computer and network efficiency by eliminating constant and in-between modifications of the template. It also saves computing resources by avoiding the complete deletion and replacement of a template in the relational database.