SQL Query Translation for External Data Resources
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Solution Overview
Problem
Existing data processing systems struggle to efficiently access and retrieve data from external resources that are not relational database management systems, as they lack the necessary functionality to interpret and execute queries like SQL queries.
Innovation Solution
A data processing system converts SQL queries into computer programs, such as dataflow graphs, which include components that perform operations equivalent to the query operations, allowing it to communicate with external resources using configuration data and parameter values, even if the external resource does not have SQL query interpretation capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a data processing system uses traditional SQL query interpretation functionality, then it can efficiently access relational database management systems, but it cannot access external resources that do not have SQL query interpretation capabilities
Solution Approach 1:
The patent introduces an intermediary component that translates SQL queries into instructions compatible with external resources. This mediator converts the standard SQL query language into resource-specific instruction sets, enabling communication between relational database systems and external resources that use different data access protocols or formats.
Solution Approach 2:
The system dynamically changes query parameters and instruction formats based on the target resource type. By detecting the resource type and adjusting the query translation parameters accordingly, the system adapts SQL queries to work with diverse external resources without requiring a complete rewrite of the query language.
2Adaptability or versatility
If a data processing system generates resource-specific instructions from SQL queries, then it can communicate with external resources, but the system complexity increases due to translation and configuration requirements
Solution Approach 1:
The system performs preliminary actions by pre-configuring translation rules and instruction templates for different resource types. By establishing these translation mappings in advance, the system reduces the complexity of real-time query translation and enables faster adaptation to new external resources.
Solution Approach 2:
The patent creates a universal translation layer that handles multiple resource types through a common interface. This multi-functional approach allows the same SQL query processing mechanism to serve various external resources by applying different translation rules, thereby reducing overall system complexity despite the diversity of target resources.
3Adaptability or versatility
If external resources change data formats over time, then the system remains flexible, but the configuration data must be continuously updated
Solution Approach 1:
The system implements feedback mechanisms that monitor changes in external resource data formats and automatically trigger configuration updates. By continuously receiving feedback from resource interactions, the system can detect format changes and initiate translation rule updates without manual intervention, reducing the time loss associated with configuration maintenance.
Data Source
AI summary
Among other things, we describe a computer-implemented method, performed by a data processing system, of executing a computer program based on a query that is expressed in accordance with a query language applicable to a relational database, the computer program executed based at least in part on data stored in a tangible, non-transitory computer-readable medium, the executing including receiving a SQL query, where the SQL query includes an identifier associated with a resource that is external to the data processing system, generating a computer program based on the SQL query, and executing the computer program, causing transmitting one or more instructions to the resource, the instructions defining operations other than operations of the SQL query, and receiving data from the resource in response to the instructions.