{"title":"Sketches of space: ownership accounting for shared storage","authors":"Jake Wires, P. Ganesan, A. Warfield","doi":"10.1145/3127479.3132021","DOIUrl":null,"url":null,"abstract":"Efficient snapshots are an important feature of modern storage systems. However, the implicit sharing underlying most snapshot implementations makes it difficult to answer basic questions about the storage costs of individual snapshots. Traditional techniques for answering these questions incur significant performance penalties due to expensive metadata overheads. We present a novel probabilistic data structure, compatible with existing storage systems, that can provide approximate answers about snapshot costs with very low computational and storage overheads while achieving better than 95% accuracy for real-world data sets.","PeriodicalId":20679,"journal":{"name":"Proceedings of the 2017 Symposium on Cloud Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 Symposium on Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3127479.3132021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Efficient snapshots are an important feature of modern storage systems. However, the implicit sharing underlying most snapshot implementations makes it difficult to answer basic questions about the storage costs of individual snapshots. Traditional techniques for answering these questions incur significant performance penalties due to expensive metadata overheads. We present a novel probabilistic data structure, compatible with existing storage systems, that can provide approximate answers about snapshot costs with very low computational and storage overheads while achieving better than 95% accuracy for real-world data sets.