Semantic Fragment Merging for Data Processing Flow Efficiency
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Solution Overview
Problem
The complexity and heterogeneity of data processing flows increase the load on data processing engines, leading to decreased efficiency and prolonged response times, making it difficult to maintain and merge these flows effectively.
Innovation Solution
The method involves partitioning data processing flows into semantic fragments based on semantic features and merging these fragments based on semantic equivalence, reducing the number of elements and eliminating mutual interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data processing flows are processed in a traditional manner without merging, then each flow can be maintained independently, but the complexity and load on data processing engines increase, leading to decreased efficiency and prolonged response times
Solution Approach 1:
The patent merges multiple data processing flows by identifying and combining semantically equivalent semantic fragments from different flows. This reduces the total number of processing elements and eliminates redundancy, thereby decreasing system complexity while maintaining or improving processing efficiency through consolidated operation
Solution Approach 2:
The patent segments data processing flows into smaller semantic fragments that can be independently analyzed and compared. This segmentation allows for granular merging of equivalent fragments from different flows, making the complexity management more manageable compared to attempting to merge entire flows at once
2Ease of operation
If multiple heterogeneous data processing flows are maintained separately, then each flow's specific requirements can be preserved, but the maintenance difficulty and system load increase significantly
Solution Approach 1:
The patent reduces the quantity of data processing flows by merging semantically equivalent semantic fragments from multiple heterogeneous flows. This consolidation decreases the number of separate flows that need to be maintained while preserving the specific functional requirements through semantic equivalence matching
Solution Approach 2:
The patent creates a universal merging mechanism that can handle heterogeneous data processing flows with different structures and requirements. By using semantic fragment analysis, the system achieves multi-functionality in processing various flow types through a single unified approach, simplifying maintenance operations
3Reliability
If data processing flows are merged directly without semantic fragment analysis, then the number of elements can be reduced, but mutual interference between different semantic fragments may occur leading to loss of semantic meaning
Solution Approach 1:
The patent segments data processing flows into semantic fragments before merging, allowing for precise comparison and matching of equivalent elements. This segmentation prevents mutual interference by isolating individual semantic units that can be safely merged based on equivalence criteria, maintaining reliability while managing complexity through structured analysis
Data Source
AI summary
The present invention discloses a method and system for processing semantic fragments. Some embodiments of the present invention provides a method for processing semantic fragments. The method comprises: obtaining a plurality of groups of semantic fragments, the plurality of groups of semantic fragments at least including a first group of semantic fragments generated from a first data processing flow and a second group of semantic fragments generated from a second data processing flow, the first data processing flow being different from the second data processing flow; and merging the first group of semantic fragment and the second group of semantic fragment based on semantic equivalence. A corresponding system is also disclosed.