Analyzing the impact of system architecture on the scalability of OLTP engines for high-contention workloads

Author:

Appuswamy Raja1,Anadiotis Angelos C.1,Porobic Danica2,Iman Mustafa K.1,Ailamaki Anastasia3

Affiliation:

1. École Polytechnique Fédérale de Lausanne

2. Oracle and École Polytechnique Fédérale de Lausanne

3. École Polytechnique Fédérale de Lausanne and RAW Labs SA

Abstract

Main-memory OLTP engines are being increasingly deployed on multicore servers that provide abundant thread-level parallelism. However, recent research has shown that even the state-of-the-art OLTP engines are unable to exploit available parallelism for high contention workloads. While previous studies have shown the lack of scalability of all popular concurrency control protocols, they consider only one system architecture---a non-partitioned, shared everything one where transactions can be scheduled to run on any core and can access any data or metadata stored in shared memory. In this paper, we perform a thorough analysis of the impact of other architectural alternatives (Data-oriented transaction execution, Partitioned Serial Execution, and Delegation) on scalability under high contention scenarios. In doing so, we present Trireme, a main-memory OLTP engine testbed that implements four system architectures and several popular concurrency control protocols in a single code base. Using Trireme, we present an extensive experimental study to understand i) the impact of each system architecture on overall scalability, ii) the interaction between system architecture and concurrency control protocols, and iii) the pros and cons of new architectures that have been proposed recently to explicitly deal with high-contention workloads.

Publisher

VLDB Endowment

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Scalable and quantitative contention generation for performance evaluation on OLTP databases;Frontiers of Computer Science;2022-08-09

2. P4DB - The Case for In-Network OLTP;Proceedings of the 2022 International Conference on Management of Data;2022-06-10

3. GaccO - A GPU-accelerated OLTP DBMS;Proceedings of the 2022 International Conference on Management of Data;2022-06-10

4. The full story of 1000 cores;The VLDB Journal;2022-04-29

5. Caracal;Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles CD-ROM;2021-10-26

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