Graph Database Query Translation for Accurate Multi-Language Processing
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Solution Overview
Problem
The lack of a uniform query language standard in graph databases leads to inefficiencies and inaccuracies when processing data, as different query languages require syntax-specific modifications, resulting in loss of description information and reduced accuracy in execution results.
Innovation Solution
A data processing method that determines to-be-queried objects and screening conditions in graph databases, performs semantic analysis to generate target nodes and sub-nodes, and executes database operations based on these to ensure accurate processing regardless of query language type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If different query languages are used to process graph database data, then the graph database can support multiple query syntaxes, but the processing accuracy decreases and description information is lost
Solution Approach 1:
The patent introduces an intermediary translation layer that converts various query language syntaxes into a unified internal representation. This mediator component receives queries in different languages, translates them to a standardized form, and executes them against the graph database, thereby maintaining both multi-language support and execution accuracy without direct loss of description information
Solution Approach 2:
Instead of having the graph database adapt to multiple query languages directly, the patent inverts the approach by having all query languages translate to a single unified internal query representation. This reversal of the adaptation direction preserves the original query semantics while enabling consistent accurate execution across different language types
2Adaptability or versatility
If syntax-specific modifications are made for different query languages, then the graph database can process various query formats, but data processing efficiency decreases
Solution Approach 1:
The patent creates a universal query processing architecture where a single unified query representation serves multiple query language types. This multi-functional internal representation handles all query operations consistently, eliminating the need for separate processing paths for different languages and thereby improving data processing efficiency while maintaining broad query format support
3Adaptability or versatility
If multiple query language types are supported, then the graph database becomes more versatile, but the complexity of the processing system increases
Solution Approach 1:
The patent extracts the language-specific syntax processing into a separate translation layer, isolating it from the core query execution engine. This extraction removes complexity from the main processing system by handling syntax variations in a dedicated component, allowing the core system to work with a simple unified representation while still supporting multiple query languages
Data Source
AI summary
A data processing method applied to a graph database, includes: determining each to-be-queried object in a received query statement and a screening condition for each to-be-queried object based on the query statement, wherein the to-be-queried object includes at least one of a graph data vertex or a graph data edge in the graph database; generating a target node corresponding to each to-be-queried object, performing semantic analysis on the screening condition for the to-be-queried object, determining a semantic query condition, and determining a sub-node of the target node based on each determined semantic query condition; determining, based on a sub-node of each target node, each database operation corresponding to the target node that needs to be performed by the graph database; and executing a data processing task corresponding to the query statement based on each database operation, and returning an execution result based on the query statement.