Object-Attribute Query Dimensions for Complex Business Data Search
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Solution Overview
Problem
Large-scale application software faces challenges with low query efficiency and poor flexibility due to complex business processes and inconsistent data dimensions, leading to inefficient and inflexible data query methods.
Innovation Solution
A data query method and apparatus that utilizes a data query statement with sequenced first and second object fields to define a target query dimension, enabling efficient querying of business process data by constructing an object data model and optimizing syntax trees for improved search efficiency and flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data query methods are used in large-scale application software, then the system can handle complex business processes, but query efficiency becomes low and flexibility of query manner becomes poor
Solution Approach 1:
The patent segments the data query system into distinct components: expression fields for defining query dimensions, object fields representing data objects, and attribute fields representing data attributes. This segmentation allows the system to handle complex business processes by breaking them down into manageable query units, thereby improving query efficiency without overwhelming system complexity
Solution Approach 2:
The patent introduces a new dimensional structure for data queries by organizing queries around expression fields that combine object fields and attribute fields. This dimensional organization transforms the query approach from traditional flat methods to a multi-dimensional framework, enabling efficient querying across complex business processes while maintaining system manageability
2Adaptability or versatility
If traditional data query methods are used in large-scale application software, then the system can handle complex business processes, but flexibility of query manner becomes poor
Solution Approach 1:
The patent creates a universal query framework where expression fields can define various query dimensions by combining different object fields and attribute fields. This multi-functional structure allows the same query system to adapt to different business process complexities and query requirements, improving flexibility without proportionally increasing system complexity
Solution Approach 2:
The patent implements a dynamic query system where the structure of expression fields can be flexibly configured to match different business process requirements. The system can dynamically adjust query dimensions and combinations based on specific needs, enabling high adaptability while maintaining a manageable underlying system architecture
3Loss of time
If data query dimensions are not precisely defined, then the query system is simpler to implement, but search time consumption increases
Solution Approach 1:
The patent applies preliminary action by pre-defining expression fields with specific object fields and attribute fields that represent meaningful query dimensions. This pre-structuring of query dimensions allows the system to quickly process queries without ad-hoc analysis, reducing search time consumption while keeping the complexity contained within the predefined field structures
4Ease of operation
If traditional query methods are used, then the system architecture is simpler, but interaction efficiency in complex business processes becomes poor
Solution Approach 1:
The patent introduces expression fields as intermediary structures that mediate between the user's query intent and the underlying data structure. These expression fields serve as a convenient interface for defining query dimensions, improving interaction efficiency by providing a structured yet flexible way to express complex queries without directly confronting system complexity
Data Source
AI summary
Embodiments of the present disclosure provide a data query method and apparatus, an electronic device, and a storage medium. A data query statement inputted by a user is displayed. The data query statement includes at least one expression field, and the expression field includes a first object field and a second object field that are arranged in sequence, the first object field representing a data object, and the second object field representing a data attribute of the data object. The expression field is used to define a data query dimension of a target business process, and the query statement is used to represent a target query dimension formed by at least one data query dimension. Target data is obtained by responding to the data query statement. The target data is a result of querying business node data of the target business process based on the target query dimension.