LINKED DATA PARTITIONING FOR RDF PROCESSING ON APACHE SPARK

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Atashkar Amir Hossein; GHADIRI NASSER; Joodaki Mehdi

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2017 | Issue:3

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Title

LINKED DATA PARTITIONING FOR RDF PROCESSING ON APACHE SPARK

Author(s)

Atashkar Amir Hossein | GHADIRI NASSER | Joodaki Mehdi

Keywords

LINKED DATA

SCALABLE ALGORITHMS

NOSQL

BIG DATA

Abstract

RDF MODELS ARE WIDELY USED IN THE WEB OF DATA DUE TO THEIR FLEXIBILITY AND SIMILARITY TO GRAPH PATTERNS. BECAUSE OF GROWING USE OF RDFS, THEIR VOLUMES AND CONTENTS ARE INCREASING. THEREFORE, PROCESSING OF SUCH AMOUNT OF DATA ON A SINGLE MACHINE IS NOT EFFICIENT ENOUGH, BECAUSE OF THE RESPONSE TIME AND LIMITED HARDWARE RESOURCES. AS A RESULT, TO PROCESS THIS DATA MODEL, CLUSTER PROCESSING IS INTRODUCED. ONE OF THESE CLUSTER PROCESSING TOOLS IS APACHE HADOOP. BECAUSE OF USING TOO MUCH OF HARD DISKS, THE RESPONSE TIME IS USUALLY UNACCEPTABLE. IN THIS PAPER, ACCORDING TO THIS PROBLEM, WE USE APACHE SPARK FOR RAPID PROCESSING OF RDF DATA MODELS. ONE KEY FEATURE OF APACHE SPARK IS USING MAIN MEMORY INSTEAD OF HARD DISK, SO THE SPEED OF DATA PROCESSING IS IMPROVED. IN CONTINUES, WE WILL RUN SQL QUERY ON RDF DATA WHICH PARTITIONED ON THE CLUSTER.

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APA: Copy

Atashkar, Amir Hossein, GHADIRI, NASSER, & Joodaki, Mehdi. (2017). LINKED DATA PARTITIONING FOR RDF PROCESSING ON APACHE SPARK. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/946870/en

Vancouver: Copy

Atashkar Amir Hossein, GHADIRI NASSER, Joodaki Mehdi. LINKED DATA PARTITIONING FOR RDF PROCESSING ON APACHE SPARK. 2017. Available from: https://sid.ir/paper/946870/en

IEEE: Copy

Amir Hossein Atashkar, NASSER GHADIRI, and Mehdi Joodaki, “LINKED DATA PARTITIONING FOR RDF PROCESSING ON APACHE SPARK,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2017, [Online]. Available: https://sid.ir/paper/946870/en

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