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- 1 August 2009
- journal article
- Published by Association for Computing Machinery (ACM) in Proceedings of the VLDB Endowment
- Vol. 2 (2) , 1626-1629
- https://doi.org/10.14778/1687553.1687609
Abstract
The size of data sets being collected and analyzed in the industry for business intelligence is growing rapidly, making traditional warehousing solutions prohibitively expensive. Hadoop [3] is a popular open-source map-reduce implementation which is being used as an alternative to store and process extremely large data sets on commodity hardware. However, the map-reduce programming model is very low level and requires developers to write custom programs which are hard to maintain and reuse.This publication has 2 references indexed in Scilit:
- A comparison of approaches to large-scale data analysisPublished by Association for Computing Machinery (ACM) ,2009
- SCOPEProceedings of the VLDB Endowment, 2008