Event-Driven Batch Processing with Granular Job Control
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Solution Overview
Problem
Current batch processing systems lack granular operational access, making it difficult for users to pause, terminate, or modify specific data jobs once a batch cycle is initiated, leading to inefficiencies and increased computing resource usage.
Innovation Solution
An event-driven batch processing system with granular operational access that retrieves attributes and resources from databases, generates a dashboard interface for users to manage data jobs, and allows manual intervention and real-time status updates, enabling pausing, canceling, and restarting of data jobs within a batch cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If batch processing is initiated to process high-volume data, then processing efficiency is improved, but operational flexibility deteriorates as users cannot pause or modify jobs once started
Solution Approach 1:
The batch processing system transitions from a static, all-or-nothing execution model to a dynamic model where individual data jobs can be independently controlled. Users can pause, resume, cancel, or modify specific jobs within a batch cycle through a dashboard interface, allowing the system to adapt operational parameters in real-time while maintaining high-volume processing capabilities
Solution Approach 2:
The batch processing workload is segmented into individual data jobs that can be independently managed. Each data job represents a discrete unit of work that can be controlled separately, allowing granular operational access where users can intervene in specific jobs without affecting the entire batch cycle or other jobs
2Speed
If batch processing runs to completion without intervention, then processing speed is improved, but resource waste increases when errors require reprocessing entire batches
Solution Approach 1:
The system extracts the ability to intervene in specific data jobs from the monolithic batch processing flow. When an error is detected or anticipated, users can cancel or pause only the affected data job(s) rather than the entire batch, preventing wasted computation on subsequent jobs that would fail for the same reason and eliminating the need to reprocess successful jobs
Solution Approach 2:
The dashboard interface provides real-time feedback on the status of each data job within the batch cycle. This feedback mechanism allows users to monitor processing progress and intervene when issues arise, enabling corrective actions that prevent resource waste from cascading failures or unnecessary reprocessing
3Adaptability or versatility
If granular control over individual data jobs is added, then operational flexibility is improved, but system complexity increases
Solution Approach 1:
A dashboard interface is introduced as an intermediary layer between the user and the batch processing system. This intermediary provides granular control over individual data jobs through a user-friendly interface without requiring changes to the underlying batch processing engine, thereby managing system complexity while enhancing operational flexibility
Data Source
AI summary
Systems, computer program products, and methods are described herein for event-driven batch processing with granular operational access. The present disclosure is configured to retrieve, from one or more feature databases, one or more attributes to process one or more records associated with a first batch cycle; retrieve, from one or more configuration databases, one or more resources associated with the one or more records; generate a dashboard interface for the one or more records, wherein the dashboard interface comprises the one or more attributes, the one or more resources, and one or more operational access parameters associated with the processing of the one or more records; and provide, to a user input device associated with a user, the dashboard interface.