Scalable layout of large graphs on disk

buir.advisorGüdükbay, Uğur
dc.contributor.authorYaşar, Abdurrahman
dc.date.accessioned2016-07-01T11:11:35Z
dc.date.available2016-07-01T11:11:35Z
dc.date.issued2015
dc.descriptionCataloged from PDF version of article.en_US
dc.description.abstractWe are witnessing an enormous growth in social networks as well as in the volume of data generated by them. As a consequence, processing this massive amount of data has become a major problem. 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 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 novel scalable disk layout technique for graphs, which aims at reducing the I/O cost of diskbased graph processing algorithms. To achieve this goal, we designed a scalable Map/Reduce-style method called ICBP, which can divide the graph into a series of disk blocks that contain sub-graphs with high locality. Furthermore, ICBP can order the resulting blocks on the disk to further reduce non-local accesses. We experimentally evaluated ICBP to showcase its scalability, layout quality, as well as the effectiveness of automatic parameter tuning for ICBP. We also deployed the graph layouts generated by ICBP to the Neo4j [1] graph database management system. Our experimental results show that the default layout results in 1.5 to 2.5 times higher running times compared to ICBP.en_US
dc.description.provenanceMade available in DSpace on 2016-07-01T11:11:35Z (GMT). No. of bitstreams: 1 0006990.pdf: 625344 bytes, checksum: a7e09b43823aadaefe5c8ceee616c3a5 (MD5) Previous issue date: 2015en
dc.description.statementofresponsibilityYaşar, Abdurrahmanen_US
dc.format.extentix, 46 leavesen_US
dc.identifier.itemidB150876
dc.identifier.urihttp://hdl.handle.net/11693/30063
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBlock formationen_US
dc.subjectDisk layouten_US
dc.subjectGraphen_US
dc.subject.lccB150876en_US
dc.titleScalable layout of large graphs on disken_US
dc.typeThesisen_US
thesis.degree.disciplineComputer Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

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