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Analyzing the impact of data compression in Hive
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
2014 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Executing expensive queries over many large tables can be prohibitively time consuming in conventional relational databases. Hadoop and its data warehouse Hive is a powerful alternative for large scale data processing. Conventionally, data is stored in Hive without compression. There is value in storing the data with compression, if the overhead of compression does not negatively impact the query processing time. This paper describes through experiments using imports, transformations and exports of Hive data in various file formats and with different compression techniques how this can be achieved.

Place, publisher, year, edition, pages
2014. , 36 p.
IT, 14074
National Category
Engineering and Technology
URN: urn:nbn:se:uu:diva-269235OAI: oai:DiVA.org:uu-269235DiVA: diva2:882559
Educational program
Bachelor Programme in Computer Science
Available from: 2015-12-15 Created: 2015-12-15 Last updated: 2016-02-11Bibliographically approved

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