Approaches for parallel data loading and data querying
Vlad Diaconita ()
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Vlad Diaconita: University of Economic Studies, Bucharest, Romania
Database Systems Journal, 2015, vol. 6, issue 1, 78-85
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)
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Persistent link: https://EconPapers.repec.org/RePEc:aes:dbjour:v:6:y:2015:i:1:p:78-85
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