Publication | Closed Access
PGX.D/Async
18
Citations
16
References
2017
Year
Unknown Venue
Cluster ComputingEngineeringComputer ArchitectureGraph DatabaseMap-reduceData ScienceGraph Query LanguageGraph Pattern MatchingData IntegrationParallel ComputingData ManagementComputer EngineeringComputer ScienceDistributed Query ProcessingPattern MatchingData-intensive ComputingGraph TheoryParallel ProgrammingGraph Querying
Graph querying and pattern matching is becoming an important feature of graph processing as it allows data analysts to easily collect and understand information about their graphs in a way similar to SQL for databases. One of the key challenges in graph pattern matching is to process increasingly large graphs that often do not fit in the memory of a single machine. In this paper, we present PGX.D/Async, a scalable distributed pattern matching engine for property graphs that is able to handle very large datasets. PGX.D/Async implements pattern matching operations with asynchronous depth-first traversal, allowing for a high degree of parallelism and precise control over memory consumption. In PGX.D/Async, developers can query graphs with PGQL, an SQL-like query language for property graphs. Essentially, PGX.D/Async provides an intuitive, distributed, in-memory pattern matching engine for very large graphs.
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