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dc.contributor.authorYu, Xiangyao
dc.contributor.authorPavlo, Andrew
dc.contributor.authorSanchez, Daniel
dc.contributor.authorDevadas, Srinivas
dc.date.accessioned2018-05-11T17:24:26Z
dc.date.available2018-05-11T17:24:26Z
dc.date.issued2016-06
dc.identifier.issn978-1-4503-3531-7
dc.identifier.urihttp://hdl.handle.net/1721.1/115329
dc.description.abstractConcurrency control for on-line transaction processing (OLTP) database management systems (DBMSs) is a nasty game. Achieving higher performance on emerging many-core systems is difficult. Previous research has shown that timestamp management is the key scalability bottleneck in concurrency control algorithms. This prevents the system from scaling to large numbers of cores. In this paper we present TicToc, a new optimistic concurrency control algorithm that avoids the scalability and concurrency bottlenecks of prior T/O schemes. TicToc relies on a novel and provably correct data-driven timestamp management protocol. Instead of assigning timestamps to transactions, this protocol assigns read and write timestamps to data items and uses them to lazily compute a valid commit timestamp for each transaction. TicToc removes the need for centralized timestamp allocation, and commits transactions that would be aborted by conventional T/O schemes. We implemented TicToc along with four other concurrency control algorithms in an in-memory, shared-everything OLTP DBMS and compared their performance on different workloads. Our results show that TicToc achieves up to 92% better throughput while reducing the abort rate by 3.3x over these previous algorithms.en_US
dc.description.sponsorshipIntel Science and Technology Center for Big Dataen_US
dc.description.sponsorshipNational Science Foundation (U.S.) (CCF-1438955)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (CCF-1438967)en_US
dc.language.isoen_US
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/2882903.2882935en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT Web Domainen_US
dc.titleTicToc: Time Traveling Optimistic Concurrency Controlen_US
dc.typeArticleen_US
dc.identifier.citationYu, Xiangyao, Andrew Pavlo, Daniel Sanchez, and Srinivas Devadas. “TicToc: Time Traveling Optimistic Concurrency Control.” Proceedings of the 2016 International Conference on Management of Data - SIGMOD ’16 (2016), 26 June - 1 July, 2016, San Francisco, California, Association for Computing Machinery, 2016.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorYu, Xiangyao
dc.contributor.mitauthorSanchez, Daniel
dc.contributor.mitauthorDevadas, Srinivas
dc.relation.journalProceedings of the 2016 International Conference on Management of Data - SIGMOD '16en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsYu, Xiangyao; Pavlo, Andrew; Sanchez, Daniel; Devadas, Srinivasen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-4317-3457
dc.identifier.orcidhttps://orcid.org/0000-0001-8253-7714
mit.licenseOPEN_ACCESS_POLICYen_US


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