QMapper: a tool for SQL optimization on hive using query rewriting

Authors:
Yingzhong Xu;Songlin Hu
Affiliations:
University of Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China
Venue:
Proceedings of the 22nd international conference on World Wide Web companion
Year:
2013

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Abstract

Although HiveQL offers similar features with SQL, it is still difficult to map complex SQL queries into HiveQL and manual translation often leads to poor performance. A tool named QMapper is developed to address this problem by utilizing query rewriting rules and cost-based MapReduce flow evaluation on the basis of column statistics. Evaluation demonstrates that while assuring the correctness, QMapper improves the performance up to 42% in terms of execution time.