Actor Graph Vertices for Regular Path Query Evaluation
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Solution Overview
Problem
Current methods are inefficient for evaluating general regular path queries (RPQs) on large graphs due to scalability and concurrency issues, particularly in transforming queries and graphs into automata, and decomposing RPQs using rare labels.
Innovation Solution
The system employs an actor graph where vertices have processing functionality and executable logic, allowing them to send messages and evaluate regular expressions to discover paths that satisfy query conditions, enabling efficient pattern matching and relationship discovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the graph is transformed into an actor graph with processing functionality at vertices, then the evaluation efficiency and scalability of regular path queries improve, but the device complexity increases
Solution Approach 1:
Vertices in the actor graph are equipped with processing functionality and executable logic, enabling them to autonomously evaluate regular expressions and communicate with other vertices. This self-service capability eliminates the need for centralized query processing, allowing distributed evaluation across the graph structure and significantly improving evaluation efficiency for regular path queries.
Solution Approach 2:
The graph is transformed into an actor graph where processing functionality is segmented and distributed across individual vertices. Each vertex becomes an independent unit capable of executing logic and communicating with neighbors, dividing the overall query evaluation task into smaller, parallelizable units that can be processed concurrently, thus improving scalability and efficiency.
2Productivity
If vertices are given processing functionality and executable logic to send messages, then concurrency and scalability improve, but the device complexity and difficulty of implementation increase
Solution Approach 1:
Vertices in the actor graph are designed as universal units that can perform multiple functions: storing graph data, executing processing logic, evaluating regular expressions, and communicating with other vertices. This multi-functionality reduces the need for separate specialized components, making the system more scalable while managing implementation complexity through a unified vertex interface.
Data Source
AI summary
Methods and systems for pattern matching and relationship discovery in graphs. The graph may be adapted as an actor graph, where vertices may include processing functionality and executable logic. The vertices of an actor graph may send messages to other vertices to which they are connected. A first vertex may receive an initial regular expression. The first vertex may evaluate which of its edges and/or respective vertices connected to these edges satisfy a first condition in the initial regular expression. If the first condition is met by an edge and or its connected vertex, the initial regular expression may be modified, if necessary, to reflect that the first condition has been met. The modified expression is then communicated to the connected vertex. The identity of the edge and/or the connected vertex may be recorded. A subsequent vertex may then proceed in a similar manner as the first vertex.