Cypher-based Graph Pattern Matching in Gradoop
| Autor: | Max Kießling, André Petermann, Martin Junghanns, Alex Averbuch, Erhard Rahm |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Power graph analysis
Graph database Theoretical computer science Computer science 02 engineering and technology Query language computer.software_genre Graph 020204 information systems Clique-width Scalability 0202 electrical engineering electronic engineering information engineering Graph (abstract data type) 020201 artificial intelligence & image processing Pattern matching computer MathematicsofComputing_DISCRETEMATHEMATICS |
| Zdroj: | GRADES@SIGMOD/PODS |
| Popis: | Graph pattern matching is an important and challenging operation on graph data. Typical use cases are related to graph analytics. Since analysts are often non-programmers, a graph system will only gain acceptance, if there is a comprehensible way to declare pattern matching queries. However, respective query languages are currently only supported by graph databases but not by distributed graph processing systems. To enable pattern matching on a large scale, we implemented the declarative graph query language Cypher within the distributed graph analysis platform Gradoop. Using LDBC graph data, we show that our query engine is scalable for operational as well as analytical workloads. The implementation is open-source and easy to extend for further research. |
| Databáze: | OpenAIRE |
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