Treffer: Distributed Graph Layout with Spark

Title:
Distributed Graph Layout with Spark
Dessin de graphe distribué avec la bibliothèque Spark
Authors:
Hinge, Antoine, Auber, David
Contributors:
Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), Programme Investissement d'avenir : Big Data - Cloud Computing topic - PIA O18062-645401
Source:
Information Visualisation (iV). :271-276
Publisher Information:
CCSD, 2015.
Publication Year:
2015
Collection:
collection:CNRS
collection:ENSEIRB
collection:UNIV-BORDEAUX
collection:LABRI-MABIOVIS
collection:UNIVERSITE-BORDEAUX
Subject Terms:
Graph Drawing, MapReduce, Hadoop, GraphX, Spark, Distributed Computing, [INFO.INFO-DC]Computer Science [cs], Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-OH]Computer Science [cs], Other [cs.OH], [INFO.INFO-SI]Computer Science [cs], Social and Information Networks [cs.SI], [INFO.INFO-CG]Computer Science [cs], Computational Geometry [cs.CG], [INFO.INFO-DS]Computer Science [cs], Data Structures and Algorithms [cs.DS]
Subject Geographic:
Barcelone, Spain
Original Identifier:
HAL: hal-01187421
Document Type:
Konferenz conferenceObject<br />Conference papers
Language:
English
Access URL:
https://hal.science/hal-01187421
https://hal.science/hal-01187421v1/document
https://hal.science/hal-01187421v1/file/main.pdf
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.hal.01187421v1
Database:
HAL

Weitere Informationen

This paper presents a novel way to draw very large graphs, especially those too big to fit the memory of a single computer. This new method takes advantage of the recent progress in distributed computing, notably using the Apache MapReduce library called Spark. Our implementation of a force-directed graph drawing algorithm and the way to compute repulsive forces in MapReduce are exhibited. We demonstrate the horizontal scalability of this algorithm and show layouts computed on a Hadoop cluster with our method.