Configurable Exception Resolution Pipeline for Item Processing
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Solution Overview
Problem
Item-processing systems face challenges in efficiently resolving exceptions that arise during item processing, as existing methods lack a systematic approach to identify and execute exception resolution processes effectively.
Innovation Solution
A computerized system that receives item-processing exceptions, determines their source and type, creates a pipeline context with a defined exception resolution process, stores it in a database, adds it to a queue, and executes it using a worker thread, allowing for re-queuing and external resource management to ensure complete resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a systematic exception resolution pipeline is implemented, then exception resolution efficiency is improved, but system complexity increases
Solution Approach 1:
The exception resolution system is divided into distinct modular components: exception detection module, pipeline context creation module, queue management module, and worker thread execution module. Each component handles a specific aspect of exception resolution, allowing the system to manage complexity through functional segmentation while maintaining high resolution efficiency.
Solution Approach 2:
A pipeline context object serves as an intermediary data structure that bridges the exception detection phase and the resolution execution phase. The pipeline context encapsulates all necessary information about the exception and its resolution steps, allowing seamless transfer of control between different system modules without requiring complex direct interactions between them.
2Productivity
If multiple worker threads are used to execute pipeline contexts, then processing throughput is improved, but resource consumption increases
Solution Approach 1:
The system dynamically manages the worker thread pool based on the current exception load and system resources. Worker threads are created and destroyed as needed, allowing the system to scale its processing capacity dynamically. This ensures high throughput when exceptions need rapid resolution while conserving resources during low-volume periods.
Solution Approach 2:
The pipeline queue maintains a continuous flow of exception resolution tasks to worker threads, ensuring that computational resources remain consistently utilized. This continuous processing approach maximizes throughput by eliminating idle time between exception handling tasks while maintaining efficient resource usage through proper thread pool management.
Data Source
AI summary
A system for resolving item-processing exceptions typically includes a processor, a memory, and an exception resolution module stored in the memory. The exception resolution module is typically configured for: receiving an item-processing exception; determining a source of the item-processing exception; based on the source of the item-processing exception, identifying a defined exception resolution process; based on the defined exception resolution process, creating and configuring a pipeline context for resolving the item-processing exception, the pipeline context including the defined exception resolution process; storing the pipeline context in a pipeline database; adding the pipeline context to a pipeline queue; selecting, via a pipeline manager service, the pipeline context from the pipeline queue; and executing, via a worker thread, the pipeline context by executing the defined exception resolution process.