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Title: Database isolation by scheduling
Transaction isolation is conventionally achieved by restricting access to the physical items in a database. To maximize performance, isolation functionality is often packaged with recovery, I/O, and data access methods in a monolithic transactional storage manager. While this design has historically afforded high performance in online transaction processing systems, industry trends indicate a growing need for a new approach in which intertwined components of the transactional storage manager are disaggregated into modular services. This paper presents a new method to modularize the isolation component. Our work builds on predicate locking, an isolation mechanism that enables this modularization by locking logical rather than physical items in a database. Predicate locking is rarely used as the core isolation mechanism because of its high theoretical complexity and perceived overhead. However, we show that this overhead can be substantially reduced in practice by optimizing for common predicate structures. We present DIBS, a transaction scheduler that employs our predicate locking optimizations to guarantee isolation as a modular service. We evaluate the performance of DIBS as the sole isolation mechanism in a data processing system. In this setting, DIBS scales up to 10.5 million transactions per second on a TATP workload. We also explore how DIBS can be applied to existing database systems to increase transaction throughput. DIBS reduces per-transaction file system writes by 90% on TATP in SQLite, resulting in a 3X improvement in throughput. Finally, DIBS reduces row contention on YCSB in MySQL, providing serializable isolation with a 1.4X improvement in throughput.  more » « less
Award ID(s):
1835446
NSF-PAR ID:
10309078
Author(s) / Creator(s):
 ;  ;  
Date Published:
Journal Name:
Proceedings of the VLDB Endowment
Volume:
14
Issue:
9
ISSN:
2150-8097
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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We used a variety of techniques such as the file locking mechanism, multithreading, circular buffers, real-time event decoding, and signal-decision plotting to realize the system. A video demonstrating the system is available at: https://www.isip.piconepress.com/projects/nsf_pfi_tt/resources/videos/realtime_eeg_analysis/v2.5.1/video_2.5.1.mp4. The final conference submission will include a more detailed analysis of the online performance of each module. ACKNOWLEDGMENTS Research reported in this publication was most recently supported by the National Science Foundation Partnership for Innovation award number IIP-1827565 and the Pennsylvania Commonwealth Universal Research Enhancement Program (PA CURE). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the official views of any of these organizations. REFERENCES [1] A. Craik, Y. He, and J. L. 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