Approaches for parallel data loading and data querying

Vlad Diaconita ()
Additional contact information
Vlad Diaconita: University of Economic Studies, Bucharest, Romania

Database Systems Journal, 2015, vol. 6, issue 1, 78-85

Abstract: This paper aims to bring contributions in data loading and data querying using products from the Apache Hadoop ecosystem. Currently, we talk about Big Data at up to zettabytes scale (1021 bytes). Research in this area is usually interdisciplinary combining elements from statistics, system integration, parallel processing and cloud computing.

Keywords: Hadoop; loading data; Sqoop; Tez (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.dbjournal.ro/archive/19/19_8.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aes:dbjour:v:6:y:2015:i:1:p:78-85

Access Statistics for this article

Database Systems Journal is currently edited by Ion Lungu

More articles in Database Systems Journal from Academy of Economic Studies - Bucharest, Romania Contact information at EDIRC.
Bibliographic data for series maintained by Adela Bara ().