Title :
The impact of cluster characteristics on HiveQL query optimization
Author :
Joldzic, Ognjen V. ; Vukovic, Dijana R.
Author_Institution :
Fac. of Electr. Eng., Univ. of Banja Luka, Banja Luka, Bosnia-Herzegovina
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.
Keywords :
Big Data; distributed databases; query processing; HiveQL query optimization; Sqoop; cluster characteristics; nonrelational databases; Data handling; File systems; Information management; Memory; Query processing; Relational databases; Apache Hadoop; HiveQL; distributed data storages; query optimization;
Conference_Titel :
Telecommunications Forum (TELFOR), 2013 21st
Conference_Location :
Belgrade
Print_ISBN :
978-1-4799-1419-7
DOI :
10.1109/TELFOR.2013.6716360