Federated Search System Resolving Data Model Conflicts
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Solution Overview
Problem
Users face difficulties in searching for information across multiple data sources due to incompatibilities, such as different data models, versions, and permission levels, leading to frustration and potential information loss.
Innovation Solution
A federated search system that transforms graphical search queries into compatible formats across heterogeneous data sources, resolves data objects using resolution rules, deduplicates results, and synchronizes changes, while filtering and enriching data based on access control and provenance identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a user performs multiple searches in multiple data sources to find comprehensive information, then the completeness of information retrieval is improved, but the time consumption and user frustration increase
Solution Approach 1:
The patent combines multiple separate search operations into a single federated search operation that simultaneously queries multiple data sources. The system merges the search capabilities of heterogeneous data sources (relational databases, NoSQL databases, search engines, file systems) into one unified search interface, allowing users to retrieve information from all sources in parallel rather than sequentially, thus reducing time consumption while maintaining information completeness
Solution Approach 2:
The patent creates a universal search system that can handle multiple types of data sources with different data models through a common query interface. The federated search engine provides multi-functionality by adapting to various data source types (SQL databases, MongoDB, Elasticsearch, local files) using the same search mechanism, eliminating the need for users to learn different query languages for different sources while maintaining comprehensive information retrieval
2Loss of information
If a federated search system queries multiple heterogeneous data sources, then the coverage of information retrieval is improved, but data incompatibility and complexity increase
Solution Approach 1:
The patent introduces a federated search engine as an intermediary layer between the user and multiple heterogeneous data sources. This mediator translates unified search queries into source-specific queries, handles data model differences, and reconciles results from various sources. The intermediary absorbs the complexity of dealing with heterogeneous data models, permission levels, and query languages, while presenting a simplified interface to users and maintaining comprehensive information coverage
Solution Approach 2:
The patent segments the search system into distinct functional components: a unified query interface, a federated search engine that manages multiple data sources, and individual data source adapters. Each component handles specific tasks independently, allowing the system to manage complexity through modular architecture while maintaining broad information coverage across heterogeneous sources
3Adaptability or versatility
If different data sources with different data models are searched, then the versatility of information retrieval is improved, but data compatibility and conflict resolution become problematic
Solution Approach 1:
The patent dynamically changes query parameters and data representation formats based on the target data source. The federated search engine transforms the unified query into source-specific parameters (SQL queries for relational databases, BSON for MongoDB, JSON for Elasticsearch, path queries for file systems) while maintaining the semantic intent of the original search. This parameter adaptation allows the system to query diverse data models effectively while ensuring reliable and compatible results through standardized result formatting
Data Source
AI summary
A method of persisting results of executing search queries across multiple data sources comprises obtaining a first data object as a result of executing a first search query against one or more data sources of a plurality of heterogeneous data sources; receiving a first request to store the first data object in a repository, a specific data source of the one or more data sources and the repository having different data models; determining that a repository data object with which the first data object resolves does not exist; generating a specific repository data object as a stub data object for the first data object, comprising: creating a unique identifier based on one or more data object properties that uniquely identify the first data object; and utilizing the unique identifier in the repository as a key or index value for the specific repository data object; storing the specific repository data object.