Scan and join optimization by exploiting internal parallelism of flash-based solid state drives

Authors:
Wenyu Lai;Yulei Fan;Xiaofeng Meng
Affiliations:
Renmin University of China, Beijing, China;Renmin University of China, Beijing, China;Renmin University of China, Beijing, China
Venue:
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Year:
2013

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Abstract

Nowadays, flash-based solid state drives (SSDs) are gradually replacing hard disk drives (HDDs) as the primary non-volatile storage in both desktop and enterprise applications because of their potential to speed up performance and reduce power consumption. However, database query processing engines are designed based on the fundamental characteristics of HDDs, so they may not benefit immediately from SSDs. Previous researches on optimizing database query processing on SSDs have mainly focused on leveraging the high random data access performance of SSDs and avoiding slow random writes whenever possible. However, they fail to exploit the rich internal parallelism of SSDs. In this paper, we focus on exploiting rich internal parallelism of SSDs to optimize scan and join operators. Firstly, we detect internal parallelism of SSDs seemed as black boxes. Then we propose a parallel table scan operator called ParaScan to take full advantage of internal parallelism of SSDs. Based on ParaScan, we also present an efficient parallel join operator called ParaHashJoin to accelerate database query processing. Experimental results on TPC-H datasets show that our ParaScan on SSD significantly outperforms the traditional table scan on SSD by 1X, and ParaHashJoin is 1.5X faster than traditional hash join operator especially when join selectivity is small.