Adaptable Adjacency Structure for Graph Data Querying

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Solution Overview

Problem

Relational databases face inefficiencies in executing graph algorithms due to the generation of excessive computational resources required for conventional adjacency structures that include superfluous data not needed for algorithm execution.

Innovation Solution

The implementation of an adaptable adjacency structure that only includes the data required to execute the graph algorithm, either by reusing existing structures or generating new ones based on the analysis of the programming code for the algorithm, thereby omitting unnecessary data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If conventional adjacency structures are generated to execute graph algorithms, then the algorithms can be executed, but excessive computational resources are consumed due to inclusion of superfluous data

Engineering Contradiction:

Improvegraph algorithm execution efficiencyVSAvoidcomputational resource consumption

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The patent extracts only the necessary data portions required for graph algorithm execution from the complete graph data structure. The system identifies and extracts specific vertex and edge data needed for the algorithm, excluding superfluous data that would otherwise be included in conventional adjacency structures, thereby reducing computational resource consumption while maintaining algorithm execution capability

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent segments the graph data structure into distinct components based on algorithm requirements. It divides the data into necessary portions (vertices, edges, attributes) and optional portions, creating a segmented adjacency structure that includes only what is needed for the specific graph algorithm, thus improving efficiency by eliminating unnecessary data processing

Inventive Principle:

Principle #1Segmentation

2Reliability

If conventional adjacency structures include all graph data, then data completeness is maintained, but the structure includes superfluous data not needed for algorithm execution

Engineering Contradiction:

Improvedata completenessVSAvoidadjacency structure complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements a dynamic adjacency structure that adapts its composition based on the specific graph algorithm being executed. The structure dynamically determines which data portions are necessary and includes only those, rather than maintaining a static complete structure. This dynamic adaptation maintains data completeness for the algorithm's needs while reducing structural complexity by excluding irrelevant data

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS10839012B2Adaptable adjacency structure for querying graph data

Publication Date: 2020.11.17 SAP SE

AI summary

A method for executing a graph algorithm is provided. The method may include responding to a request from a client to execute a graph algorithm on graph data stored in a database by determining data required to execute the graph algorithm. In response to determining that a first portion of the data required to execute the graph algorithm is absent from an existing adjacency structure that includes a second portion of the data required to execute the graph algorithm, the existing adjacency structure may be modified to include the first portion of data. The graph algorithm may be executed based on the modified adjacency structure. The execution of the graph algorithm may include querying, based on the modified adjacency structure, the graph data stored in the database. Related systems and articles of manufacture, including computer program products, are also provided.