Cited 0 time in
Scalable Database Logging for Multicores
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Jung, Hyungsoo | - |
| dc.contributor.author | Han, Hyuck | - |
| dc.contributor.author | Kang, Sooyong | - |
| dc.date.accessioned | 2022-07-13T05:03:24Z | - |
| dc.date.available | 2022-07-13T05:03:24Z | - |
| dc.date.created | 2021-05-12 | - |
| dc.date.issued | 2017-10 | - |
| dc.identifier.issn | 2150-8097 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/151517 | - |
| dc.description.abstract | Modern databases, guaranteeing atomicity and durability, store transaction logs in a volatile, central log buffer and then flush the log buffer to non-volatile storage by the write-ahead logging principle. Buffering logs in central log store has recently faced a severe multicore scalability problem, and log flushing has been challenged by synchronous I/O delay. We have designed and implemented a fast and scalable logging method, ELEDA, that can migrate a surge of transaction logs from volatile memory to stable storage without risking durable transaction atomicity. Our efficient implementation of ELEDA is enabled by a highly concurrent data structure, GRASSHOPPER, that eliminates a multicore scalability problem of centralized logging and enhances system utilization in the presence of synchronous I/O delay. We implemented ELEDA and plugged it to WiredTiger and Shore-MT by replacing their log managers. Our evaluation showed that ELEDA-based transaction systems improve performance up to 71 x, thus showing the applicability of ELEDA. | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | ASSOC COMPUTING MACHINERY | - |
| dc.title | Scalable Database Logging for Multicores | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Jung, Hyungsoo | - |
| dc.contributor.affiliatedAuthor | Kang, Sooyong | - |
| dc.identifier.doi | 10.14778/3149193.3149195 | - |
| dc.identifier.wosid | 000429424900002 | - |
| dc.identifier.bibliographicCitation | PROCEEDINGS OF THE VLDB ENDOWMENT, v.11, no.2, pp.135 - 148 | - |
| dc.relation.isPartOf | PROCEEDINGS OF THE VLDB ENDOWMENT | - |
| dc.citation.title | PROCEEDINGS OF THE VLDB ENDOWMENT | - |
| dc.citation.volume | 11 | - |
| dc.citation.number | 2 | - |
| dc.citation.startPage | 135 | - |
| dc.citation.endPage | 148 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Article | - |
| dc.description.journalClass | 1 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Computer Science | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
| dc.subject.keywordPlus | MEMORY | - |
| dc.subject.keywordPlus | LOCKING | - |
| dc.identifier.url | https://dl.acm.org/doi/10.14778/3149193.3149195 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1366
COPYRIGHT © 2024 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
