Region Clustering Based Multiple Query Optimization

DOI

10.2991/jiaet-18.2018.2How to use a DOI?

Keywords

multiple queries optimization, query sharing, region clustering

Abstract

In order to solve the problem of low efficiency in dealing with large numbers of queries in Hive, we propose a multi-queries region clustering (mqrc) method to improve the overall performance of Hive. By clustering the query set, we divide the query with high similarity into a set. Each group generates a preprocessing job, which divides the complete query region into multiple small query regions and reduces the search space of queries. The experimental results show that, when dealing with a large number of queries, the query execution efficiency is much better than that of traditional methods. It can reduce the overhead of I/O and shorten the time of queries.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Pei Xuan Fei
AU  - Cai Chen
AU  - Yi Liang
PY  - 2018/03
DA  - 2018/03
TI  - Region Clustering Based Multiple Query Optimization
BT  - Proceedings of the 2018 Joint International Advanced Engineering and Technology Research Conference (JIAET 2018)
PB  - Atlantis Press
SP  - 6
EP  - 12
SN  - 2352-5401
UR  - https://doi.org/10.2991/jiaet-18.2018.2
DO  - 10.2991/jiaet-18.2018.2
ID  - Fei2018/03
ER  -