Object Update Event Merging for Faster Asynchronous Data Handling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing information handling systems face inefficiencies in processing update events, particularly in asynchronous environments, leading to high computational costs and slower data processing due to reliance on traditional caching methods.
Innovation Solution
Implementing a method to identify and manage partial and full update events by determining the required intents of objects, updating storage devices with timestamps, and merging these events to optimize data processing without caching, thereby enhancing processing speed and reducing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional caching methods are used to process update events, then data availability is improved, but computational costs increase and processing speed decreases
Solution Approach 1:
The patent extracts and processes only the necessary parts of update events (partial updates) rather than handling complete event objects. By identifying and processing only the changed fields and their intents, the system reduces computational overhead while maintaining data availability, directly resolving the contradiction between reliability and productivity.
Solution Approach 2:
The patent segments update events into partial updates containing only dynamic data, separating them from complete event objects. This segmentation allows the system to process only essential information, reducing computational costs while maintaining data availability through intent-based processing.
2Reliability
If traditional caching methods are used to process update events, then data availability is improved, but computational costs increase
Solution Approach 1:
The patent extracts only the necessary dynamic data and intents from update events, avoiding processing of complete event objects. This extraction approach reduces computational costs significantly while maintaining data availability through targeted processing of essential event components.
Solution Approach 2:
The patent applies partial action by processing only the necessary portions of update events (partial updates with dynamic data) rather than complete events. This selective processing reduces computational overhead while maintaining sufficient data availability for system operations.
3Productivity
If update events are processed without intent determination, then processing speed is improved, but data integrity deteriorates
Solution Approach 1:
The patent performs preliminary intent determination before processing update events. By pre-identifying which intents are required and which fields need updating, the system maintains data integrity through structured processing while optimizing speed through targeted operations rather than comprehensive event processing.
Solution Approach 2:
The patent applies local quality by determining and processing only the specific intents and fields relevant to each update event. This localized approach ensures data integrity for critical fields while maintaining processing speed through selective operations rather than uniform processing of all event data.
Data Source
AI summary
Receiving an update event for an object; determining that the update event is a partial update event that includes only dynamic data, and in response: determining that the object, stored at a storage device and corresponding to the update event, includes all required intents, and in response: updating the storage device to include the partial update event for the object, including a timestamp associated with the partial update event; and merging the partial update event with the object such that the object includes the partial update event, including the dynamic data of the partial update event.