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 only 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 based on an underlying graph processing system, and enables different design choices for the key implementation issues of partitioning a hypergraph representation. We implement MESH on top of the popular GraphX graph processing framework in Apache Spark. Using a variety of real datasets and experiments conducted on a local 8-node cluster as well as a 65-node Amazon AWS testbed, we demonstrate that MESH provides flexibility based on data and application characteristics, as well as scalability with cluster size. We further show that it is competitive in performance to HyperX, another hypergraph processing system based on Spark, while providing a much simpler implementation (requiring about 5X fewer lines of code), thus showing that simplicity and flexibility need not come at the cost of performance.
|Original language||English (US)|
|Title of host publication||Proceedings - 2019 IEEE International Conference on Cloud Engineering, IC2E 2019|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||11|
|State||Published - Jun 2019|
|Event||7th IEEE International Conference on Cloud Engineering, IC2E 2019 - Prague, Czech Republic|
Duration: Jun 24 2019 → Jun 27 2019
|Name||Proceedings - 2019 IEEE International Conference on Cloud Engineering, IC2E 2019|
|Conference||7th IEEE International Conference on Cloud Engineering, IC2E 2019|
|Period||6/24/19 → 6/27/19|
Bibliographical noteFunding Information:
This work is supported in part by NSF grant III-1422802.
© 2019 IEEE.
Copyright 2020 Elsevier B.V., All rights reserved.
- Distributed Processing System
- Hypergraph Processing System