Dynamic Query Parsing for Persistent Service Integration
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Solution Overview
Problem
The integration of Object and Relational Persistent Query Services into applications is time-consuming and laborious, often requiring manual changes and re-implementation, especially due to the need for resource files and static database schema-based approaches, which do not efficiently address increasing database access latency.
Innovation Solution
A dynamic method that parses SQL queries to determine table names, attributes, and relationships, generating related files and updating configuration files to automate the execution of object and relational persistent query services, allowing for efficient retrieval and caching of results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual integration of Object and Relational Persistent Query Services is performed, then system reliability is improved, but development time and labor requirements increase significantly
Solution Approach 1:
The system automatically generates object mapping files and program files by parsing SQL queries, eliminating the need for manual integration of Persistent Query Services. The query parser and code generator work autonomously to create necessary mapping files between database tables and object classes, reducing integration time while maintaining system reliability through automated configuration.
Solution Approach 2:
The invention changes the approach from static database schema-based mapping to dynamic query-based mapping. By parsing actual SQL queries to determine table names, attributes, and relationships, the system adapts mapping files to the specific query requirements, improving integration efficiency without compromising reliability.
2Stability of the object's composition
If static database schema-based mapping is used, then mapping consistency is improved, but adaptability to different queries decreases
Solution Approach 1:
The system transitions from static schema-based mapping to dynamic query-based mapping. The query parser analyzes actual SQL queries to determine table names, attributes, and relationships in real-time, generating mapping files that adapt to specific query requirements while maintaining consistency through automated generation based on parsed query structure.
Solution Approach 2:
The invention segments the mapping process into query parsing, table identification, attribute extraction, and mapping file generation. This modular approach allows the system to handle different query types independently while maintaining overall mapping consistency through a unified automated process.
3Quantity of substance
If brute force method creates mapping files for entire database, then mapping completeness is improved, but processing time and resource consumption increase
Solution Approach 1:
The system extracts only the necessary mapping information from the database schema by parsing specific SQL queries. Instead of generating mapping files for the entire database, the query parser identifies and processes only the tables, attributes, and relationships relevant to the current query, significantly reducing processing time while maintaining completeness for the required data.
Solution Approach 2:
The invention applies partial action by generating mapping files only for the portions of the database accessed by the SQL query. The query parser identifies the specific tables and attributes needed and creates mapping files only for those elements, avoiding the excessive processing of the entire database schema.
4Manufacturing precision
If manual changes are made in operational applications, then configuration accuracy is improved, but system availability decreases due to maintenance time
Solution Approach 1:
The system performs self-configuration by automatically generating and updating mapping files based on parsed SQL queries. This eliminates the need for manual configuration changes in operational applications, maintaining configuration accuracy through automated generation while preserving system availability by removing maintenance time requirements.
Solution Approach 2:
The query parser and code generator perform preliminary actions by automatically creating the necessary mapping files and configuration updates before the application needs to access the database. This pre-generation approach eliminates the need for manual configuration changes during operational maintenance, ensuring both accuracy and availability.
Data Source
AI summary
A method includes receiving a request for information from a relational database, translating the received request to at least one of an object and a relational persistent query, parsing the query to determine one or more of table names, attributes and attribute types, and generating at least one set of related files. The parsing results are used to update at least one configuration file to accept the related files for use by at least one of the object and the relational persistent query service, and execute at least one of the persistent query services based on the translated queries, wherein the persistent query services are programmed to receive the translated query. Based on the execution of the translated query, the results are either fetched from at least one of the object cache or retrieved from at least one of the database, stored, and the results are transmitted to the user.