Query Evaluator Filters Composite Relationships in ER Models
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Solution Overview
Problem
In an Entity-Relationship (ER) model, users face difficulties in selecting meaningful composite relationships for aggregation due to the large number of possible relationships and the need for extensive knowledge of the schema and data, making it challenging to identify relevant candidates for analysis.
Innovation Solution
A method for evaluating and filtering composite relationships in a federated database system that optimizes query processing by selecting the best aggregation strategy based on the capabilities of underlying databases, recommending a ranked list of relevant composite relationships to users, and filtering out non-aggregatable ones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If all possible composite relationships are evaluated and presented to the user, then the user can choose from a comprehensive list, but the number of relationships becomes combinatorially large causing information overload
Solution Approach 1:
The patent extracts and filters only the most relevant composite relationships from the complete set of possible relationships. The query evaluator automatically identifies and presents a subset of relationships that are most likely to be meaningful for aggregation, removing unnecessary relationships from the presentation to the user.
Solution Approach 2:
The system changes the parameter of relationship selection from presenting all possible relationships to presenting only those that meet certain relevance criteria. The query evaluator uses heuristics and metadata to assess relationship quality and filters based on aggregation potential, transforming the output from a complete but overwhelming list to a curated relevant subset.
2Measurement precision
If the user selects composite relationships manually, then they can choose meaningful relationships, but the user needs extensive knowledge of the schema and data
Solution Approach 1:
The query evaluator performs self-service by automatically evaluating and filtering composite relationships without requiring user expertise. The system autonomously assesses relationship relevance, aggregation potential, and data distribution characteristics, then presents pre-filtered results to the user who simply needs to review and select from the curated list.
Solution Approach 2:
The query evaluator acts as an intermediary between the complete set of composite relationships and the user. It mediates the selection process by applying evaluation criteria, filtering algorithms, and relevance assessment to bridge the gap between raw data relationships and user-friendly selections, eliminating the need for users to have deep schema knowledge.
3Adaptability or versatility
If aggregate operations are computed on the client side, then flexibility is maintained, but query processing efficiency decreases
Solution Approach 1:
The system dynamically determines where aggregation should be performed based on the specific query and data characteristics. The query evaluator analyzes the composite relationship and underlying data distribution to decide whether aggregation is more efficiently performed on the server side or client side, allowing flexible adaptation to different scenarios while optimizing performance.
4Loss of information
If the system evaluates all composite relationships, then comprehensive analysis is possible, but query processing time increases
Solution Approach 1:
The query evaluator performs preliminary evaluation and filtering of composite relationships before the main aggregation computation. By pre-assessing relationship relevance, data distribution, and aggregation potential, the system eliminates obviously irrelevant relationships early in the process, maintaining analytical completeness for meaningful relationships while significantly reducing processing time by avoiding evaluation of irrelevant ones.
Data Source
AI summary
A computer-implemented method is disclosed for executing aggregate queries of composite relationships from an Entity-Relationship (ER) model which sources data from a plurality of heterogeneous and decentralised databases. The method comprises maintaining an ER model comprising a plurality of entities En for which data exists in one or more databases, and one or more relationships rn between those entities. An aggregate query is received relating to a composite relationship cr(r1, r2) involving entities E1, E2 and E3 wherein r1 is a relation between E1 and E2, and wherein r2 is a relation between E2 and E3. The computation of the aggregate query is optimized by selecting an aggregation strategy according to the relation between entities E1, E2 and E3, such that a single table aggregation strategy, a semi-join strategy or a join strategy is selected according to the relation between tables defining entities in the ER model.