S-Store: a streaming NewSQL system for big velocity applications
Name
Madden_S-store.pdf
Size
2.37 MB
Format
Adobe PDF
Checksum (MD5)
efdeaeb2dc0ae6dfb9ef7d32d421036a
Author(s)
Cetintemel, Ugur
Tufte, Kristin
Wang, Hao
Zdonik, Stanley
Du, Jiang
Kraska, Tim
Maier, David
Meehan, John
Pavlo, Andrew
Stonebraker, Michael
Date Issued
August 2014
Journal
Proceedings of the VLDB Endowment
Publisher
Association for Computing Machinery (ACM)
Citation
Ugur Cetintemel, Jiang Du, Tim Kraska, Samuel Madden, David Maier, John Meehan, Andrew Pavlo, Michael Stonebraker, Erik Sutherland, Nesime Tatbul, Kristin Tufte, Hao Wang, and Stanley Zdonik. 2014. S-Store: a streaming NewSQL system for big velocity applications. Proc. VLDB Endow. 7, 13 (August 2014), 1633-1636.
Version
Author's final manuscript
Abstract
First-generation streaming systems did not pay much attention to state management via ACID transactions (e.g., [3, 4]). S-Store is a data management system that combines OLTP transactions with stream processing. To create S-Store, we begin with H-Store, a main-memory transaction processing engine, and add primitives to support streaming. This includes triggers and transaction workflows to implement push-based processing, windows to provide a way to bound the computation, and tables with hidden state to implement scoping for proper isolation. This demo explores the benefits of this approach by showing how a naïve implementation of our benchmarks using only H-Store can yield incorrect results. We also show that by exploiting push-based semantics and our implementation of triggers, we can achieve significant improvement in transaction throughput. We demo two modern applications: (i) leaderboard maintenance for a version of "American Idol", and (ii) a city-scale bicycle rental scenario.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.14778/2733004.2733048
