Performing external join operator on PostgreSQL with data transfer approach

Ryota Takizawa, Hideyuki Kawashima, Ryuya Mitsuhashi, Osamu Tatebe

研究成果: Conference contribution

抄録

With the development of sensing devices, the size of data managed by human being has been rapidly increasing. To manage such huge data, relational database management system (RDBMS) plays a key role. RDBMS models the real world data as n-ary relational tables. Join operator is one of the most important relational operators, and its acceleration has been studied widely and deeply. How can an RDBMS provide such an efficient join operator? The performance improvement of join operator has been deeply studied for a decade, and many techniques are proposed already. The problem that we face is how to actually use such excellent techniques in real RDBMSs. We propose to implement an efficient join technique by the data transfer approach. The approach makes a hook point inside an RDBMS internal, and pulls data streams from the operator pipeline in the RDBMS, and applies our original join operator to the data, and finally returns the result to the operator pipeline in the RDBMS. The result of the experiment showed that our proposed method achieved 1.42x speedup compared with PostgreSQL. Our code is available on GitHub.

本文言語English
ホスト出版物のタイトルProceedings of International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2018
出版社Association for Computing Machinery
ページ271-277
ページ数7
ISBN(電子版)9781450353724
DOI
出版ステータスPublished - 2018 1 28
外部発表はい
イベント2018 International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2018 - Tokyo, Japan
継続期間: 2018 1 282018 1 31

出版物シリーズ

名前ACM International Conference Proceeding Series

Other

Other2018 International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2018
国/地域Japan
CityTokyo
Period18/1/2818/1/31

ASJC Scopus subject areas

  • ソフトウェア
  • 人間とコンピュータの相互作用
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ ネットワークおよび通信

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