The use of flashSSDs has increased rapidly in a wide range of areas due to their superior energy efficiency, shorter access time, and higher bandwidth when compared to HDDs. The internal parallelism created by multiple flash memory packages embedded in a flashSSDs, is one of the unique features of flashSSDs. Many new DBMS technologies have been developed for flashSSDs, but query processing for flashSSDs have drawn less attention than other DBMS technologies. Hash partitioning is popularly used in query processing algorithms to materialize their intermediate results in an efficient manner. In this paper, we propose a novel hash partitioning algorithm that exploits the internal parallelism of flashSSDs. The devised hash partitioning method outperforms the traditional hash partitioning technique regardless of the amount of available main memory independently from the buffer management strategies (blocked I/O vs page sized I/O). We implemented our method based on the source code of the PostgreSQL storage manager. PostgreSQL relation files created by the TPC-H workload were employed in the experiments. Our method was found to be up to 3.55 times faster than the traditional method with blocked I/O, and 2.36 times faster than the traditional method with pagesized I/O.
|Title of host publication||2016 Symposium on Applied Computing, SAC 2016|
|Publisher||Association for Computing Machinery|
|Number of pages||8|
|Publication status||Published - 2016 Apr 4|
|Event||31st Annual ACM Symposium on Applied Computing, SAC 2016 - Pisa, Italy|
Duration: 2016 Apr 4 → 2016 Apr 8
|Name||Proceedings of the ACM Symposium on Applied Computing|
|Other||31st Annual ACM Symposium on Applied Computing, SAC 2016|
|Period||16/4/4 → 16/4/8|
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) (NRF-2015R1A2A1A05001845).
All Science Journal Classification (ASJC) codes