Replication Filters for Selective Data Synchronization
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Solution Overview
Problem
Current computing systems face challenges in efficiently integrating and replicating data across different systems, particularly in managing data attributes, locations, and time values, which hinders seamless data synchronization and processing.
Innovation Solution
A system that utilizes a graphical user interface (GUI) to configure replication filters based on attribute values and data objects, allowing for selective data replication between systems, including location and time-based filtering, and employs field mapping and hierarchical data organization for accurate data transmission and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data replication is performed across multiple systems without filtering, then data completeness is improved, but data processing time and system load increase
Solution Approach 1:
The patent extracts and replicates only specific subsets of data objects that match defined criteria (filter conditions) rather than replicating all data. The filter configuration allows selective extraction of data objects based on attributes, locations, and time values, reducing the volume of replicated data while maintaining data completeness for relevant items.
Solution Approach 2:
The patent segments the data replication process into filterable categories based on attributes, locations, and time periods. By dividing data into manageable segments that can be independently filtered and replicated, the system processes only necessary portions of data, reducing overall processing time while maintaining completeness of relevant data sets.
2Measurement precision
If comprehensive data filtering is implemented, then data precision is improved, but system complexity increases
Solution Approach 1:
The filter configuration system serves multiple functions: it filters data based on attributes, locations, and time values; it organizes data into hierarchical structures; and it manages replication rules across systems. This multi-functional approach achieves comprehensive data precision without proportionally increasing system complexity, as a single filter configuration mechanism handles multiple filtering dimensions.
3Manufacturing precision
If selective data replication is performed, then data synchronization accuracy is improved, but data transmission volume decreases
Solution Approach 1:
The patent extracts only the specific data objects that require synchronization based on filter criteria (matching attributes, locations, and time values). This selective extraction ensures high synchronization accuracy for relevant data while minimizing the transmission volume of unnecessary data, directly resolving the contradiction between synchronization accuracy and transmission volume.
Data Source
AI summary
Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a set of values for a set of attributes associated with a plurality of data objects managed by a first system. The program further generates a replication filter for filtering the plurality of data objects based on the set of values for the set of attributes associated with the plurality of data objects. The program also replicates a subset of the plurality of data objects from the first system to the second system based on the replication filter. The program further receives a set of data from the second system, the set of data generated by the second system based on the subset of the plurality of data objects.