NDLI: The impact of cluster characteristics on HiveQL query optimization

Content Provider	IEEE Xplore Digital Library
Author	Joldzic, O.V. Vukovic, D.R.
Copyright Year	2013
Description	Author affiliation: Dept. of Telematics, Norwegian Univ. of Sci. & Technol., Trondheim, Norway (Vukovic, D.R.) \|\| Fac. of Electr. Eng., Univ. of Banja Luka, Banja Luka, Bosnia-Herzegovina (Joldzic, O.V.)
Abstract	Huge amount of data is stored by different kinds of applications for further analysis. Relational databases were used for decades as data storages, but in some cases they are not suitable for Big Data processing. To solve the problem, non-relational databases were developed. As a help for transferring data from relational databases to non-relational databases, adequate tools were developed. In this paper, a tool named Sqoop is presented. The issue of query optimization should be addressed by all applications that deal with large amounts of data, regardless of their field of application and scope. The impact of cluster characteristics on HiveQL query optimization is analyzed in this paper.
Starting Page	837
Ending Page	840
File Size	767735
Page Count	4
File Format	PDF
e-ISBN	9781479914203
DOI	10.1109/TELFOR.2013.6716360
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-26
Publisher Place	Serbia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	HiveQL File systems Query processing Data handling Memory Relational databases Distributed data storages Information management Apache Hadoop Query optimization
Content Type	Text
Resource Type	Article

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