Distributed block formation and layout for disk-based management of large-scale graphs

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dc.citation.epage53en_US
dc.citation.issueNumber1en_US
dc.citation.spage23en_US
dc.citation.volumeNumber35en_US
dc.contributor.authorYaşar, A.en_US
dc.contributor.authorGedik, B.en_US
dc.contributor.authorFerhatosmanoğlu, H.en_US
dc.date.accessioned2018-04-12T11:14:25Z
dc.date.available2018-04-12T11:14:25Z
dc.date.issued2017en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractWe are witnessing an enormous growth in social networks as well as in the volume of data generated by them. An important portion of this data is in the form of graphs. In recent years, several graph processing and management systems emerged to handle large-scale graphs. The primary goal of these systems is to run graph algorithms and queries in an efficient and scalable manner. Unlike relational data, graphs are semi-structured in nature. Thus, storing and accessing graph data using secondary storage requires new solutions that can provide locality of access for graph processing workloads. In this work, we propose a scalable block formation and layout technique for graphs, which aims at reducing the I/O cost of disk-based graph processing algorithms. To achieve this, we designed a scalable MapReduce-style method called ICBL, which can divide the graph into a series of disk blocks that contain sub-graphs with high locality. Furthermore, ICBL can order the resulting blocks on disk to further reduce non-local accesses. We experimentally evaluated ICBL to showcase its scalability, layout quality, as well as the effectiveness of automatic parameter tuning for ICBL. We deployed the graph layouts generated by ICBL on the Neo4j open source graph database, http://www.neo4j.org/ (2015) graph database management system. Our results show that the layout generated by ICBL reduces the query running times over Neo4j more than 2 × compared to the default layout. © 2017, Springer Science+Business Media New York.en_US
dc.identifier.doi10.1007/s10619-017-7191-3en_US
dc.identifier.issn0926-8782
dc.identifier.urihttp://hdl.handle.net/11693/37473
dc.language.isoEnglishen_US
dc.publisherSpringeren_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s10619-017-7191-3en_US
dc.source.titleDistributed and Parallel Databasesen_US
dc.subjectGraph management systemsen_US
dc.subjectDatabase systemsen_US
dc.subjectDigital storageen_US
dc.subjectGraphic methodsen_US
dc.subjectManagement information systemsen_US
dc.subjectOpen systemsen_US
dc.subjectQuery processingen_US
dc.subjectDatabase managementen_US
dc.subjectDistributed systemsen_US
dc.subjectLarge scale graphsen_US
dc.subjectLayouten_US
dc.subjectLocalityen_US
dc.subjectManagement systemsen_US
dc.subjectDistributed database systemsen_US
dc.titleDistributed block formation and layout for disk-based management of large-scale graphsen_US
dc.typeArticleen_US

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