poster

A two-tier index architecture for fast processing large RDF data over distributed memory

Authors:

Spyros Kotoulas,

Georgios TheodoropoulosAuthors Info & Claims

HT '14: Proceedings of the 25th ACM conference on Hypertext and social media

Pages 300 - 302

https://doi.org/10.1145/2631775.2631789

Published: 01 September 2014 Publication History

Abstract

We propose an efficient method for fast processing large RDF data over distributed memory. Our approach adopts a two-tier index architecture on each computation node: (1) a light-weight primary index, to keep loading times low, and (2) a dynamic, multi-level secondary index, calculated as a by-product of query execution, to decrease or remove inter-machine data movement for subsequent queries that contain the same graph patterns. Experimental results on a commodity cluster show that we can load large RDF data very quickly in memory while remaining within an interactive range for query processing with the secondary index.

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Cited By

Cheng LKotoulas SWard TTheodoropoulos G(2014)A fully parallel framework for analyzing RDF dataProceedings of the 2014 International Conference on Posters & Demonstrations Track - Volume 127210.5555/2878453.2878526(289-292)Online publication date: 21-Oct-2014
https://dl.acm.org/doi/10.5555/2878453.2878526

Index Terms

A two-tier index architecture for fast processing large RDF data over distributed memory
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
      2. Parallel and distributed DBMSs
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

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Information & Contributors

Information

Published In

cover image ACM Conferences

HT '14: Proceedings of the 25th ACM conference on Hypertext and social media

September 2014

346 pages

ISBN:9781450329545

DOI:10.1145/2631775

General Chairs:
Leo Ferres
University of Concepción, Chile
,
Gustavo Rossi
University of La Plata, Argentina
,
Program Chairs:
Virgilio Almeida
Federal University of Minas Gerais, Brazil
,
Eelco Herder
L3S Research Center, Germany

Copyright © 2014 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

In-Cooperation

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2014

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HT '14

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SIGWEB

HT '14: 25th ACM Conference on Hypertext and Social Media

September 1 - 4, 2014

Santiago, Chile

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HT '14 Paper Acceptance Rate 49 of 86 submissions, 57%;

Overall Acceptance Rate 378 of 1,158 submissions, 33%

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Cited By

Cheng LKotoulas SWard TTheodoropoulos G(2014)A fully parallel framework for analyzing RDF dataProceedings of the 2014 International Conference on Posters & Demonstrations Track - Volume 127210.5555/2878453.2878526(289-292)Online publication date: 21-Oct-2014
https://dl.acm.org/doi/10.5555/2878453.2878526

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