Lásaro J. Camargos, F. Pedone, A. Pilchin, M. Wieloch
{"title":"On-Demand Recovery in Middleware Storage Systems","authors":"Lásaro J. Camargos, F. Pedone, A. Pilchin, M. Wieloch","doi":"10.1109/SRDS.2010.31","DOIUrl":null,"url":null,"abstract":"This paper presents a recovery architecture for in-memory data management systems. Recovery in such systems boils down to solving two problems: retrieving and installing the last committed image of the crashed database on a new server and replaying the updates missing from the image. We improve recovery time with a novel technique called On-Demand Recovery, which removes the need to replay all missing updates before new transactions can be accepted. We have implemented and thoroughly evaluated the technique. We show in the paper that in some cases On-Demand Recovery can reduce recovery time by more than 50%.","PeriodicalId":219204,"journal":{"name":"2010 29th IEEE Symposium on Reliable Distributed Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 29th IEEE Symposium on Reliable Distributed Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SRDS.2010.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper presents a recovery architecture for in-memory data management systems. Recovery in such systems boils down to solving two problems: retrieving and installing the last committed image of the crashed database on a new server and replaying the updates missing from the image. We improve recovery time with a novel technique called On-Demand Recovery, which removes the need to replay all missing updates before new transactions can be accepted. We have implemented and thoroughly evaluated the technique. We show in the paper that in some cases On-Demand Recovery can reduce recovery time by more than 50%.
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