MESH: A Flexible Distributed Hypergraph Processing System
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
MESH: A Flexible Distributed Hypergraph Processing System
Published Date
2016-12-05
Publisher
Type
Report
Abstract
With the rapid growth of large online social networks, the ability to analyze large-scale social structure and behavior has become critically important, and this has led to the development of several scalable graph processing systems. In reality, however, social interaction takes place not just between pairs of individuals as in the graph model, but rather in the context of multi-user groups. Research has shown that such group dynamics can be better modeled through a more general hypergraph model, resulting in the need to build scalable hypergraph processing systems. In this paper, we present MESH, a flexible distributed framework for scalable hypergraph processing. MESH provides an easy-to-use and expressive application programming interface that naturally extends the "think like a vertex" model common to many popular graph processing systems. Our framework provides a flexible implementation that enables different design choices for the key implementation issues of hypergraph representation and partitioning. We implement MESH on top of the popular GraphX graph processing framework in Apache Spark. Using a variety of real datasets, we experimentally demonstrate that MESH provides flexibility based on data and application characteristics, and is competitive in performance to HyperX, another hypergraph processing system based on Spark, showing that simplicity and flexibility need not come at the cost of performance.
Keywords
Description
Related to
Replaces
License
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Suggested citation
Heintz, Benjamin; Singh, Shivangi; Tesdahl, Corey; Chandra, Abhishek. (2016). MESH: A Flexible Distributed Hypergraph Processing System. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/216002.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.