Improving Hadoop Hive Query Response Times Through Efficient Virtual Resource Allocation

Date

2015-10-28

Author

Dokeroglu, Tansel
Cinar, Muhammet Serkan
SERT, SEYYİT ALPER
Coşar, Ahmet
Yazıcı, Adnan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The performance of the MapReduce-based Cloud data warehouses mainly depends on the virtual hardware resources allocated. Most of the time, the resources are values selected/given by the Cloud service providers. However, setting the right virtual resources in accordance with the workload demands of a query, such as the number of CPUs, the size of RAM, and the network bandwidth, will improve the response time when querying large data on an optimized system. In this study, we carried out a set of experiments with a well-known Mapreduce SQL-translator, Hadoop Hive, on benchmark decision support the TPC benchmark (TPC-H) database in order to analyze the performance sensitivity of the queries under different virtual resource settings. Our results provide valuable hints for the decision makers who design efficient MapReduce-based data warehouses on the Cloud.

Subject Keywords

Hadoop, Hive, Virtual resource allocation, Multi-objective query optimization

URI

https://hdl.handle.net/11511/31138

DOI

https://doi.org/10.1007/978-3-319-26154-6_17

Collections

Graduate School of Natural and Applied Sciences, Conference / Seminar

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Citation Formats

T. Dokeroglu, M. S. Cinar, S. A. SERT, A. Coşar, and A. Yazıcı, “Improving Hadoop Hive Query Response Times Through Efficient Virtual Resource Allocation,” 2015, vol. 400, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/31138.