Declarative stack for distributed graph processing

Radwa Elshawi, Arwa Aldhabaan, Sherif Sakr

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Recently, people, devices, processes and other entities have been more connected than at any other point in history. In general, graphs have been used to represent data sets in various application domains including computational biology, social science, telecommunications, astronomy, semantic web and protein networks among many others. In practice, systemsstacks of large scale graph processing platforms are suffering from the lack of declarative processing interface. They are mainly relying on low level programming abstractions which can be only used by sophisticated software developers and are not adequate for many users. In order to tackle this challenge and improve the performance and user acceptance of large scale graph processing frameworks, we present a declarative querying framework that can seamlessly integrate with various big graph processing system platforms. Our experimental evaluation shows the effectiveness and efficiency of our proposed framework.

Original languageEnglish
Pages (from-to)1083-1090
Number of pages8
JournalJournal of Theoretical and Applied Information Technology
Volume96
Issue number4
Publication statusPublished - 28 Feb 2018

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Graph in graph theory
Processing
Social sciences
Astronomy
Computational Biology
Social Sciences
Semantic Web
Telecommunications
Experimental Evaluation
Telecommunication
Programming
History
Integrate
Proteins
Protein
Software
Framework
Abstraction

Keywords

  • Big data
  • Big graph
  • Hadoop
  • Spark

Cite this

Elshawi, Radwa ; Aldhabaan, Arwa ; Sakr, Sherif. / Declarative stack for distributed graph processing. In: Journal of Theoretical and Applied Information Technology. 2018 ; Vol. 96, No. 4. pp. 1083-1090.
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Declarative stack for distributed graph processing. / Elshawi, Radwa; Aldhabaan, Arwa; Sakr, Sherif.

In: Journal of Theoretical and Applied Information Technology, Vol. 96, No. 4, 28.02.2018, p. 1083-1090.

Research output: Contribution to journalArticleResearchpeer-review

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