Accelerating read atomic multi-partition transaction with remote direct memory access

Naofumi Murata, Hideyuki Kawashima, Osamu Tatebe

研究成果: Conference contribution

抄録

Many applications these days require data processing that is both efficient and reliable. Distributed databases are one way to meet these requirements, but must be updated using distributed transactions. To manage foreign key constraints, secondary indices, and materialized views in distributed environments, read atomic multi-partition (RAMP) transactions demonstrate high efficiency. RAMP transactions achieved high performance distributed transaction processing by relaxing the isolation level. However, the use of fast interconnect to accelerate performance has not yet been considered. This paper proposes the acceleration of RAMP transactions by exploiting remote direct memory access (RDMA) on the InfiniBand interconnect. We first present GET+ and PUT+ operations that accelerate the RAMP transaction by exploiting RDMA write operations. We then present the GET∗ operation, which further accelerates GET+ operations exploiting RDMA read operations. To evaluate the proposed methods, we implemented a prototype distributed in-memory key-value store in C/C++. The results of the experiments show that compared with RAMP transactions on IP over InfiniBand, GET∗ and PUT+ achieve a 2.67× performance improvement on the Yahoo! Cloud Serving Benchmark. All of our code is publicly available.

本文言語English
ホスト出版物のタイトル2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ239-246
ページ数8
ISBN(電子版)9781509030156
DOI
出版ステータスPublished - 2017 3 17
外部発表はい
イベント2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017 - Jeju Island, Korea, Republic of
継続期間: 2017 2 132017 2 16

出版物シリーズ

名前2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017

Other

Other2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017
国/地域Korea, Republic of
CityJeju Island
Period17/2/1317/2/16

ASJC Scopus subject areas

  • 情報システム
  • 人工知能
  • コンピュータ サイエンスの応用
  • コンピュータ ビジョンおよびパターン認識

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