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POSTER: IOGP: An Incremental Online Graph Partitioning for Large-Scale Distributed Graph Databases

Published:26 January 2017Publication History
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Abstract

Large-scale graphs are becoming critical in various domains such as social network, scientific application, knowledge discovery, and even system software, etc. Many of those use cases require large-scale high-performance graph databases, which are designed for serving continuous updates from the clients, and at the same time, answering complex queries towards the current graph in an on-line manner. Those operations in graph databases, also referred as OLTP (online transaction processing) operations, need specific design and implementation in graph partitioning algorithms. In this study, we designed an incremental online graph partitioning (IOGP), optimized for OLTP workloads. It is designed to achieve better locality, generate balanced partitions, and increase the parallelism for accessing hotspots of the graph. Our evaluation results on both real world and synthetic graphs in both simulation and real system confirm a better performance on graph queries (as much as 2X) with small overheads during graph insertion (less than 10%).

References

  1. G. Karypis and V. Kumar. A fast and high quality multilevel scheme for partitioning irregular graphs. phSIAM Journal on scientific Computing, 20 (1): 359--392, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. C. Tsourakakis, C. Gkantsidis, B. Radunovic, and M. Vojnovic. Fennel: Streaming graph partitioning for massive scale graphs. In phProceedings of the 7th ACM international conference on Web search and data mining, pages 333--342. ACM, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. POSTER: IOGP: An Incremental Online Graph Partitioning for Large-Scale Distributed Graph Databases

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        • Published in

          cover image ACM SIGPLAN Notices
          ACM SIGPLAN Notices  Volume 52, Issue 8
          PPoPP '17
          August 2017
          442 pages
          ISSN:0362-1340
          EISSN:1558-1160
          DOI:10.1145/3155284
          Issue’s Table of Contents
          • cover image ACM Conferences
            PPoPP '17: Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
            January 2017
            476 pages
            ISBN:9781450344937
            DOI:10.1145/3018743

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 26 January 2017

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