Graph data structures are widely used in computer science fields such as biometric information, navigational systems etc. Recently there has been significant research into quickly calculating the shortest path of a graph using the latest databases such as Neo4j, Spark, etc. Alternatively, the Frontier-Expand-Merge operator (FEM) provides a method to find the shortest path using only SQL in RDBMSs. However, the FEM utilizes sequential searching and iterative aggregate functions to find the shortest path. We propose parallel shortest path searching and table indexing as substitution for the aggregate function. To prove the effectiveness of this approach, we compared each method using experimentation and could demonstrate an improvement of up to 80% in processing speed with our proposal.
展开▼
