BigDAWG version 0.1

V. Gadepally, K. O'Brien, Adam Dziedzic, Aaron J. Elmore, J. Kepner, S. Madden, T. Mattson, Jennie Duggan, Zuohao She, M. Stonebraker
{"title":"BigDAWG version 0.1","authors":"V. Gadepally, K. O'Brien, Adam Dziedzic, Aaron J. Elmore, J. Kepner, S. Madden, T. Mattson, Jennie Duggan, Zuohao She, M. Stonebraker","doi":"10.1109/HPEC.2017.8091077","DOIUrl":null,"url":null,"abstract":"A polystore system is a database management system composed of integrated heterogeneous database engines and multiple programming languages. By matching data to the storage engine best suited to its needs, complex analytics run faster and flexible storage choices helps improve data organization. BigDAWG (Big Data Working Group) is our prototype implementation of a polystore system. In this paper, we describe the current BigDAWG software release which supports PostgreSQL, Accumulo and SciDB. We describe the overall architecture, API and initial results of applying BigDAWG to the MIMIC II medical dataset.","PeriodicalId":364903,"journal":{"name":"2017 IEEE High Performance Extreme Computing Conference (HPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE High Performance Extreme Computing Conference (HPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC.2017.8091077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22

Abstract

A polystore system is a database management system composed of integrated heterogeneous database engines and multiple programming languages. By matching data to the storage engine best suited to its needs, complex analytics run faster and flexible storage choices helps improve data organization. BigDAWG (Big Data Working Group) is our prototype implementation of a polystore system. In this paper, we describe the current BigDAWG software release which supports PostgreSQL, Accumulo and SciDB. We describe the overall architecture, API and initial results of applying BigDAWG to the MIMIC II medical dataset.
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
BigDAWG版本0.1
多存储系统是由异构数据库引擎和多种编程语言集成而成的数据库管理系统。通过将数据匹配到最适合其需求的存储引擎,复杂的分析可以运行得更快,灵活的存储选择有助于改进数据组织。BigDAWG(大数据工作组)是我们多存储系统的原型实现。在本文中,我们描述了目前BigDAWG软件版本,它支持PostgreSQL, Accumulo和SciDB。我们描述了将BigDAWG应用于MIMIC II医疗数据集的总体架构、API和初步结果。
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
Optimized task graph mapping on a many-core neuromorphic supercomputer Software-defined extreme scale networks for bigdata applications Power-aware computing: Measurement, control, and performance analysis for Intel Xeon Phi xDCI, a data science cyberinfrastructure for interdisciplinary research Leakage energy reduction for hard real-time caches
×
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