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Querying big data. / Novikov, Boris; Vassilieva, Natalia; Yarygina, Anna.

CompSysTech '12 Proceedings of the 13th International Conference on Computer Systems and Technologies. 2012. p. 1-10.

Research output: Chapter in Book/Report/Conference proceedingArticle in an anthologyResearchpeer-review

Harvard

Novikov, B, Vassilieva, N & Yarygina, A 2012, Querying big data. in CompSysTech '12 Proceedings of the 13th International Conference on Computer Systems and Technologies. pp. 1-10. <http://dl.acm.org/citation.cfm?doid=2383276.2383278>

APA

Novikov, B., Vassilieva, N., & Yarygina, A. (2012). Querying big data. In CompSysTech '12 Proceedings of the 13th International Conference on Computer Systems and Technologies (pp. 1-10) http://dl.acm.org/citation.cfm?doid=2383276.2383278

Vancouver

Novikov B, Vassilieva N, Yarygina A. Querying big data. In CompSysTech '12 Proceedings of the 13th International Conference on Computer Systems and Technologies. 2012. p. 1-10

Author

Novikov, Boris ; Vassilieva, Natalia ; Yarygina, Anna. / Querying big data. CompSysTech '12 Proceedings of the 13th International Conference on Computer Systems and Technologies. 2012. pp. 1-10

BibTeX

@inbook{fc957c1709c84dabb6fe5425ffb80382,
title = "Querying big data",
abstract = "The term {"}Big Data{"} became a buzzword and is widely used in both research and industrial worlds. Typically the concept of big data assumes a variety of different sources of information and velocity of complex analytical processing, rather than just a huge and growing volume of data. All variety, velocity, and volume create new research challenges, as nearly all techniques and tools commonly used in data processing have to be re-considered. Variety and uncertainty of big data require a mixture of exact and similarity search and grouping of complex objects based on different attributes. High-level declarative query languages are important in this context due to expressiveness and potential for optimization. In this talk we are mostly interested in an algebraic layer for complex query processing which resides between user interface (most likely, graphical) and execution engine in layered system architecture. We analyze the applicability of existing models and query languages. We describe a systematic approach t",
keywords = "Big data, complex query processing",
author = "Boris Novikov and Natalia Vassilieva and Anna Yarygina",
year = "2012",
language = "English",
isbn = "978-1-4503-1193-9",
pages = "1--10",
booktitle = "CompSysTech '12 Proceedings of the 13th International Conference on Computer Systems and Technologies",

}

RIS

TY - CHAP

T1 - Querying big data

AU - Novikov, Boris

AU - Vassilieva, Natalia

AU - Yarygina, Anna

PY - 2012

Y1 - 2012

N2 - The term "Big Data" became a buzzword and is widely used in both research and industrial worlds. Typically the concept of big data assumes a variety of different sources of information and velocity of complex analytical processing, rather than just a huge and growing volume of data. All variety, velocity, and volume create new research challenges, as nearly all techniques and tools commonly used in data processing have to be re-considered. Variety and uncertainty of big data require a mixture of exact and similarity search and grouping of complex objects based on different attributes. High-level declarative query languages are important in this context due to expressiveness and potential for optimization. In this talk we are mostly interested in an algebraic layer for complex query processing which resides between user interface (most likely, graphical) and execution engine in layered system architecture. We analyze the applicability of existing models and query languages. We describe a systematic approach t

AB - The term "Big Data" became a buzzword and is widely used in both research and industrial worlds. Typically the concept of big data assumes a variety of different sources of information and velocity of complex analytical processing, rather than just a huge and growing volume of data. All variety, velocity, and volume create new research challenges, as nearly all techniques and tools commonly used in data processing have to be re-considered. Variety and uncertainty of big data require a mixture of exact and similarity search and grouping of complex objects based on different attributes. High-level declarative query languages are important in this context due to expressiveness and potential for optimization. In this talk we are mostly interested in an algebraic layer for complex query processing which resides between user interface (most likely, graphical) and execution engine in layered system architecture. We analyze the applicability of existing models and query languages. We describe a systematic approach t

KW - Big data

KW - complex query processing

M3 - Article in an anthology

SN - 978-1-4503-1193-9

SP - 1

EP - 10

BT - CompSysTech '12 Proceedings of the 13th International Conference on Computer Systems and Technologies

ER -

ID: 4604033