Fast In-Memory Transaction Processing Using RDMA and HTM

Author:

Chen Haibo1ORCID,Chen Rong1,Wei Xingda1,Shi Jiaxin1,Chen Yanzhe1,Wang Zhaoguo1,Zang Binyu1,Guan Haibing1

Affiliation:

1. Shanghai Jiao Tong University, Shanghai, China

Abstract

DrTM is a fast in-memory transaction processing system that exploits advanced hardware features such as remote direct memory access (RDMA) and hardware transactional memory (HTM). To achieve high efficiency, it mostly offloads concurrency control such as tracking read/write accesses and conflict detection into HTM in a local machine and leverages the strong consistency between RDMA and HTM to ensure serializability among concurrent transactions across machines. To mitigate the high probability of HTM aborts for large transactions, we design and implement an optimized transaction chopping algorithm to decompose a set of large transactions into smaller pieces such that HTM is only required to protect each piece. We further build an efficient hash table for DrTM by leveraging HTM and RDMA to simplify the design and notably improve the performance. We describe how DrTM supports common database features like read-only transactions and logging for durability. Evaluation using typical OLTP workloads including TPC-C and SmallBank shows that DrTM has better single-node efficiency and scales well on a six-node cluster; it achieves greater than 1.51, 34 and 5.24, 138 million transactions per second for TPC-C and SmallBank on a single node and the cluster, respectively. Such numbers outperform a state-of-the-art single-node system (i.e., Silo) and a distributed transaction system (i.e., Calvin) by at least 1.9X and 29.6X for TPC-C.

Funder

Top-Notch Youth Talents Program of China, Shanghai Science and Technology Development Fund

Zhangjiang Hi-Tech Program

National Key Research 8 Development Program of China

China National Natural Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

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