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Scalable In-Memory Transaction Processing with HTM

Authors: 

Yingjun Wu and Kian-Lee Tan, National University of Singapore

Abstract: 

We propose a new HTM-assisted concurrency control protocol, called HTCC, that achieves high scalability and robustness when processing OLTP workloads. HTCC attains its goal using a two-pronged strategy that exploits the strengths of HTM. First, it distinguishes between hot and cold records, and deals with each type differently – while accesses to highly contended data are protected using conventional fine-grained locks, accesses to cold data are HTM-guarded. This remarkably reduces the database transaction abort rate and exploits HTM’s effectiveness in executing low-contention critical sections. Second, to minimize the overhead inherited from successive restarts of aborted database transactions, HTCC caches the internal execution states of a transaction for performing delta-restoration, which partially updates the maintained read/write set and bypasses redundant index lookups during transaction re-execution at best effort. This approach is greatly facilitated by HTM’s speedy hardware mechanism for ensuring atomicity and isolation. We evaluated HTCC in a main-memory database prototype running on a 4 socket machine (40 cores in total), and confirmed that HTCC can scale near-linearly, yielding high transaction rate even under highly contended workloads.

Yingjun Wu, National University of Singapore

Kian-Lee Tan, National University of Singapore

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BibTeX
@inproceedings {196239,
author = {Yingjun Wu and Kian-Lee Tan},
title = {Scalable {In-Memory} Transaction Processing with {HTM}},
booktitle = {2016 USENIX Annual Technical Conference (USENIX ATC 16)},
year = {2016},
isbn = {978-1-931971-30-0},
address = {Denver, CO},
pages = {365--377},
url = {https://www.usenix.org/conference/atc16/technical-sessions/presentation/wu},
publisher = {USENIX Association},
month = jun
}
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