Filter Class for Database Query Optimization
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Solution Overview
Problem
Database queries, especially in graph-based databases, experience performance degradation due to multi-table queries, leading to increased unnecessary transactions when multiple clients access data tables, which affects search responsiveness and system efficiency.
Innovation Solution
The use of filter classes to consolidate search filters and generate query arguments that reduce the number of database calls by associating tag values with data tables and filters, allowing for efficient retrieval of attribute values based on filter parameters in a single query.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multi-table queries are performed to retrieve data from multiple data tables, then comprehensive data retrieval capability is improved, but system performance and search responsiveness deteriorate
Solution Approach 1:
The patent segments the multi-table query operation into separate single-table queries. Instead of querying multiple tables simultaneously, the system performs individual queries on each data table and then combines the results. This segmentation reduces the complexity and performance overhead of multi-table queries while maintaining the ability to retrieve comprehensive data across multiple tables.
Solution Approach 2:
The patent applies partial action by retrieving only the specific attributes needed from each data table rather than entire tables. The system identifies and queries only the relevant attributes required by the query conditions, reducing data transmission and processing overhead while still providing complete information needed for the user's request.
2Ease of operation
If multiple clients access data tables concurrently, then system accessibility and user experience are improved, but unnecessary database transactions increase
Solution Approach 1:
The patent merges multiple filter parameters from different data tables into a unified query structure. By consolidating filter conditions and combining query operations, the system reduces the number of separate database transactions required when multiple clients access data concurrently. This merging approach maintains high accessibility while minimizing redundant database operations.
Solution Approach 2:
The patent performs preliminary filtering and data preparation before executing main query operations. By pre-processing filter parameters and identifying relevant data in advance, the system reduces the need for multiple transaction operations during concurrent client access, thereby reducing unnecessary database transactions while maintaining system accessibility.
3Measurement precision
If filter parameters are applied to multiple data tables, then query accuracy and data precision are improved, but query complexity and processing overhead increase
Solution Approach 1:
The patent applies local quality by optimizing filter parameter application for each specific data table based on its characteristics. Instead of applying a uniform complex filtering mechanism across all tables, the system tailors the filtering approach to each table's structure and data type, maintaining high query accuracy while reducing overall processing complexity.
Solution Approach 2:
The patent transforms and standardizes filter parameters into a unified format that simplifies processing. By converting diverse filter conditions from multiple data tables into a consistent parameter structure, the system maintains precise filtering capability across different tables while reducing the complexity of query processing and parameter management.
Data Source
AI summary
A data model identifying a first and second table may be stored, the first table comprising a first and second attribute, the second table comprising a third attribute. A first filter parameter of a first filter and a second filter parameter of a second filter may be obtained. A first tag value may be associated with the first and second filters. A set of filters including the first and second filters may be determined in response to a determination that the first and second filters are associated with the first tag value. An argument indicating the first and second filter parameters may be generated based on the set of filters. A call to the first table may be executed based on the argument, the execution of the call causing values of the first and second attributes to be obtained based on the first and second filter parameters.