Hive: a warehousing solution over a map-reduce framework

  • Authors:
  • Ashish Thusoo;Joydeep Sen Sarma;Namit Jain;Zheng Shao;Prasad Chakka;Suresh Anthony;Hao Liu;Pete Wyckoff;Raghotham Murthy

  • Affiliations:
  • Facebook Data Infrastructure Team;Facebook Data Infrastructure Team;Facebook Data Infrastructure Team;Facebook Data Infrastructure Team;Facebook Data Infrastructure Team;Facebook Data Infrastructure Team;Facebook Data Infrastructure Team;Facebook Data Infrastructure Team;Facebook Data Infrastructure Team

  • Venue:
  • Proceedings of the VLDB Endowment
  • Year:
  • 2009

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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.