Unified Search Architecture for Structured and Unstructured Queries
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Solution Overview
Problem
Existing systems struggle to efficiently handle both structured and unstructured queries across diverse data environments like mainframe and big data, leading to inefficiencies and inaccuracies in search and retrieval processes.
Innovation Solution
A blended and unified search platform with application programming interfaces (APIs) that differentiate between structured and unstructured queries, enabling seamless interaction with both mainframe and big data systems, utilizing search and match applications like Apache Solr for big data and SQL for mainframe data, and a scheduler for data porting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single search system is used to handle both structured and unstructured queries across mainframe and big data environments, then system simplicity is maintained, but search accuracy and efficiency deteriorate
Solution Approach 1:
The patent divides the search system into separate specialized search applications: one for structured queries on mainframe data and another for unstructured queries on big data. Each search application is optimized for its specific data type and query structure, resulting in improved search accuracy while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The patent creates a unified search platform that can handle both structured and unstructured queries across different data environments (mainframe and big data) through a common architecture. This multi-functional system allows organizations to search diverse data types without requiring separate independent systems, balancing specialization with overall system simplicity.
2Measurement precision
If separate search systems are used for structured and unstructured queries, then search accuracy is improved, but system complexity increases
Solution Approach 1:
The patent merges separate search capabilities into a unified search platform that handles both structured and unstructured queries. By combining specialized search applications under a common architecture with shared access to both mainframe and big data environments, the system achieves high search accuracy for each query type while avoiding the complexity of completely separate independent systems.
3Reliability
If traditional mainframe systems are used for data storage, then data security and reliability are maintained, but query processing speed and flexibility deteriorate
Solution Approach 1:
The patent adds a new dimension to data storage by implementing both traditional mainframe systems and modern big data environments. This multi-dimensional storage architecture allows queries to be routed to the appropriate system based on requirements: mainframe for secure, reliable transactions and big data for high-speed, flexible analytical queries, thereby achieving both security and speed.
4Speed
If big data environments are used for data storage, then query processing speed and flexibility are improved, but data security and reliability deteriorate
Solution Approach 1:
The patent applies different quality characteristics to different data storage locations: mainframe systems maintain high security and reliability for sensitive transactional data, while big data environments provide high speed and flexibility for analytical processing. The search system intelligently routes queries to the appropriate environment based on the specific requirements of each query, ensuring both security and performance.
5Adaptability or versatility
If a unified search platform supports multiple search models, then adaptability and versatility are improved, but device complexity increases
Solution Approach 1:
The patent designs a unified search platform with multi-functional capabilities that can handle structured queries, unstructured queries, mainframe data, and big data through a common architecture. This universal platform achieves high adaptability and versatility while managing complexity through standardized interfaces and intelligent query routing mechanisms.
Data Source
AI summary
Embodiments include a search and match computing system configured to: access, from a third party computing system, a query regarding at least one entity; determine if the query is a structured query or an unstructured query; process the query with at least one of an application programming interface configured to receive structured queries or a second application programming interface receive unstructured queries; initiate a search and match application configured to execute queries on at least one of: a relational data scheme or a non-relational data scheme; receive search results from the at least one of: the relational data scheme or the non-relational data scheme; and process the received search results to generate an output data packet for access by the third party computing system.