PARALLEL DATA LAB 

PDL Abstract

An Empirical Evaluation of InMemory MultiVersion Concurrency Control

Proceedings of the VLDB Endowment, vol. 10, iss. 7, pages. 781—792, March 2017.

Yingjun Wu*, Joy Arulraj, Jiexi Lin, Ran Xian, Andrew Pavlo

* National University of Singapore
Carnegie Mellon University

http://www.pdl.cmu.edu/

Multi-version concurrency control (MVCC) is currently the most popular transaction management scheme in modern database management systems (DBMSs). Although MVCC was discovered in the late 1970s, it is used in almost every major relational DBMS released in the last decade. Maintaining multiple versions of data potentially increases parallelism without sacrificing serializability when processing transactions. But scaling MVCC in a multi-core and in-memory setting is non-trivial: when there are a large number of threads running in parallel, the synchronization overhead can outweigh the benefits of multi-versioning.

To understand how MVCC perform when processing transactions in modern hardware settings, we conduct an extensive study of the scheme’s four key design decisions: concurrency control protocol, version storage, garbage collection, and index management. We implemented state-of-the-art variants of all of these in an in-memory DBMS and evaluated them using OLTP workloads. Our analysis identifies the fundamental bottlenecks of each design choice.

FULL PAPER: pdf