Scalable storage support for data stream processing

Zoe Sebepou, K. Magoutis
{"title":"Scalable storage support for data stream processing","authors":"Zoe Sebepou, K. Magoutis","doi":"10.1109/MSST.2010.5496977","DOIUrl":null,"url":null,"abstract":"Continuous data stream processing systems have offered limited support for data persistence in the past, for three main reasons: First, online, real-time queries examine current streaming data and (under the assumption of no server failures) do not require access to past data; second, stable storage devices are commonly thought to be constraining system throughput and response times when compared to main memory, and are thus kept off the common path; finally, the use of scalable storage solutions which would be required to sustain high data streaming rates have not been thoroughly investigated in the past. Our work advances the state of the art by providing data streaming systems with a scalable path to persistent storage. This path has low impact in the performance properties of a scalable streaming system and allows two fundamental enhancements to their capabilities: First, it allows stream persistence for reference/archival purposes (in other words, queries can now be applied on past data on-demand); second, fault tolerance is achievable by checkpointing and stream replay schemes that are not constrained by the size of main memory.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSST.2010.5496977","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Continuous data stream processing systems have offered limited support for data persistence in the past, for three main reasons: First, online, real-time queries examine current streaming data and (under the assumption of no server failures) do not require access to past data; second, stable storage devices are commonly thought to be constraining system throughput and response times when compared to main memory, and are thus kept off the common path; finally, the use of scalable storage solutions which would be required to sustain high data streaming rates have not been thoroughly investigated in the past. Our work advances the state of the art by providing data streaming systems with a scalable path to persistent storage. This path has low impact in the performance properties of a scalable streaming system and allows two fundamental enhancements to their capabilities: First, it allows stream persistence for reference/archival purposes (in other words, queries can now be applied on past data on-demand); second, fault tolerance is achievable by checkpointing and stream replay schemes that are not constrained by the size of main memory.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
数据流处理的可扩展存储支持
过去,连续数据流处理系统对数据持久性提供的支持有限,主要有三个原因:首先,在线、实时查询检查当前流数据,并且(假设没有服务器故障)不需要访问过去的数据;其次,与主存相比,稳定的存储设备通常被认为限制了系统吞吐量和响应时间,因此被排除在公共路径之外;最后,使用可扩展的存储解决方案来维持高数据流速率在过去并没有得到彻底的研究。我们的工作通过为数据流系统提供通向持久存储的可扩展路径,推动了技术的发展。这条路径对可扩展流系统的性能影响很小,并允许对其功能进行两个基本的增强:首先,它允许用于参考/存档目的的流持久化(换句话说,现在可以按需对过去的数据应用查询);其次,容错可以通过不受主存大小限制的检查点和流重放方案来实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Automated lookahead data migration in SSD-enabled multi-tiered storage systems Write amplification reduction in NAND Flash through multi-write coding Leveraging disk drive acoustic modes for power management Achieving page-mapping FTL performance at block-mapping FTL cost by hiding address translation Energy and thermal aware buffer cache replacement algorithm
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1