Distributed high-dimensional index creation using Hadoop, HDFS and C++

Gylfi Pór Gudmundsson; Laurent Amsaleg; Björn Pór Jónsson

doi:10.1109/CBMI.2012.6269848

Distributed high-dimensional index creation using Hadoop, HDFS and C++

Gylfi Pór Gudmundsson^*, Laurent Amsaleg, Björn Pór Jónsson

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

This paper describes an initial study where the open-source Hadoop parallel and distributed run-time environment is used to speedup the construction phase of a large high-dimensional index. This paper first discusses the typical practical problems developers may run into when porting their code to Hadoop. It then presents early experimental results showing that the performance gains are substantial when indexing large data sets.

Original language	English
Title of host publication	2012 10th International Workshop on Content-Based Multimedia Indexing, CBMI 2012
Pages	83-88
Number of pages	6
DOIs	https://doi.org/10.1109/CBMI.2012.6269848
Publication status	Published - 2012
Event	2012 10th International Workshop on Content-Based Multimedia Indexing, CBMI 2012 - Annecy, Haute-Savoie, France Duration: 27 Jun 2012 → 29 Jun 2012

Publication series

Name	Proceedings - International Workshop on Content-Based Multimedia Indexing
ISSN (Print)	1949-3991

Conference

Conference	2012 10th International Workshop on Content-Based Multimedia Indexing, CBMI 2012
Country/Territory	France
City	Annecy, Haute-Savoie
Period	27/06/12 → 29/06/12

Access to Document

10.1109/CBMI.2012.6269848

Cite this

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title = "Distributed high-dimensional index creation using Hadoop, HDFS and C++",

abstract = "This paper describes an initial study where the open-source Hadoop parallel and distributed run-time environment is used to speedup the construction phase of a large high-dimensional index. This paper first discusses the typical practical problems developers may run into when porting their code to Hadoop. It then presents early experimental results showing that the performance gains are substantial when indexing large data sets.",

author = "Gudmundsson, {Gylfi P{\'o}r} and Laurent Amsaleg and J{\'o}nsson, {Bj{\"o}rn P{\'o}r}",

year = "2012",

doi = "10.1109/CBMI.2012.6269848",

language = "English",

isbn = "9781467323697",

series = "Proceedings - International Workshop on Content-Based Multimedia Indexing",

pages = "83--88",

booktitle = "2012 10th International Workshop on Content-Based Multimedia Indexing, CBMI 2012",

note = "2012 10th International Workshop on Content-Based Multimedia Indexing, CBMI 2012 ; Conference date: 27-06-2012 Through 29-06-2012",

}

Gudmundsson, GP, Amsaleg, L & Jónsson, BP 2012, Distributed high-dimensional index creation using Hadoop, HDFS and C++. in 2012 10th International Workshop on Content-Based Multimedia Indexing, CBMI 2012., 6269848, Proceedings - International Workshop on Content-Based Multimedia Indexing, pp. 83-88, 2012 10th International Workshop on Content-Based Multimedia Indexing, CBMI 2012, Annecy, Haute-Savoie, France, 27/06/12. https://doi.org/10.1109/CBMI.2012.6269848

Distributed high-dimensional index creation using Hadoop, HDFS and C++. / Gudmundsson, Gylfi Pór; Amsaleg, Laurent; Jónsson, Björn Pór.

2012 10th International Workshop on Content-Based Multimedia Indexing, CBMI 2012. 2012. p. 83-88 6269848 (Proceedings - International Workshop on Content-Based Multimedia Indexing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Jónsson, Björn Pór

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AB - This paper describes an initial study where the open-source Hadoop parallel and distributed run-time environment is used to speedup the construction phase of a large high-dimensional index. This paper first discusses the typical practical problems developers may run into when porting their code to Hadoop. It then presents early experimental results showing that the performance gains are substantial when indexing large data sets.

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Distributed high-dimensional index creation using Hadoop, HDFS and C++

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