Paper Info
Title
An Empirical Evaluation of In-Memory Multi-Version Concurrency Control.
Abstract
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.
Year
DOI
Venue
2017
10.14778/3067421.3067427
PVLDB
Field
DocType
Volume
Data mining,Isolation (database systems),Serializability,Concurrency control,Design choice,Computer science,Online transaction processing,Multiversion concurrency control,Garbage collection,Relational database management system,Database,Distributed computing
Journal
10
Issue
ISSN
Citations 
7
2150-8097
17
PageRank 
References 
Authors
0.61
35
5
Name
Order
Citations
PageRank
Yingjun Wu1652.27
Joy Arulraj218312.17
Jiexi Lin3431.67
Ran Xian4432.01
Andrew Pavlo51614122.03