The CloudMdsQL Multistore System

B. Kolev, Carlyna Bondiombouy, P. Valduriez, R. Jiménez-Peris, Raquel Pau, José Pereira
{"title":"The CloudMdsQL Multistore System","authors":"B. Kolev, Carlyna Bondiombouy, P. Valduriez, R. Jiménez-Peris, Raquel Pau, José Pereira","doi":"10.1145/2882903.2899400","DOIUrl":null,"url":null,"abstract":"The blooming of different cloud data management infrastructures has turned multistore systems to a major topic in the nowadays cloud landscape. In this demonstration, we present a Cloud Multidatastore Query Language (CloudMdsQL), and its query engine. CloudMdsQL is a functional SQL-like language, capable of querying multiple heterogeneous data stores (relational and NoSQL) within a single query that may contain embedded invocations to each data store's native query interface. The major innovation is that a CloudMdsQL query can exploit the full power of local data stores, by simply allowing some local data store native queries (e.g. a breadth-first search query against a graph database) to be called as functions, and at the same time be optimized. Within our demonstration, we focus on two use cases each involving four diverse data stores (graph, document, relational, and key-value) with its corresponding CloudMdsQL queries. The query execution flows are visualized by an embedded real-time monitoring subsystem. The users can also try out different ad-hoc queries, not necessarily in the context of the use cases.","PeriodicalId":20483,"journal":{"name":"Proceedings of the 2016 International Conference on Management of Data","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 International Conference on Management of Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2882903.2899400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 47

Abstract

The blooming of different cloud data management infrastructures has turned multistore systems to a major topic in the nowadays cloud landscape. In this demonstration, we present a Cloud Multidatastore Query Language (CloudMdsQL), and its query engine. CloudMdsQL is a functional SQL-like language, capable of querying multiple heterogeneous data stores (relational and NoSQL) within a single query that may contain embedded invocations to each data store's native query interface. The major innovation is that a CloudMdsQL query can exploit the full power of local data stores, by simply allowing some local data store native queries (e.g. a breadth-first search query against a graph database) to be called as functions, and at the same time be optimized. Within our demonstration, we focus on two use cases each involving four diverse data stores (graph, document, relational, and key-value) with its corresponding CloudMdsQL queries. The query execution flows are visualized by an embedded real-time monitoring subsystem. The users can also try out different ad-hoc queries, not necessarily in the context of the use cases.
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
CloudMdsQL多存储系统
各种云数据管理基础设施的蓬勃发展使多存储系统成为当今云领域的一个主要话题。在这个演示中,我们介绍了一个云多数据存储查询语言(CloudMdsQL)及其查询引擎。CloudMdsQL是一种类似sql的函数式语言,能够在单个查询中查询多个异构数据存储(关系和NoSQL),该查询可能包含对每个数据存储的本机查询接口的嵌入式调用。主要的创新是,CloudMdsQL查询可以利用本地数据存储的全部功能,只需允许将一些本地数据存储的本地查询(例如针对图数据库的宽度优先搜索查询)作为函数调用,并同时进行优化。在我们的演示中,我们重点关注两个用例,每个用例涉及四个不同的数据存储(图、文档、关系和键值)及其相应的CloudMdsQL查询。查询执行流通过嵌入式实时监控子系统实现可视化。用户还可以尝试不同的特别查询,而不一定是在用例的上下文中。
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
An Experimental Comparison of Thirteen Relational Equi-Joins in Main Memory Rheem: Enabling Multi-Platform Task Execution Wander Join: Online Aggregation for Joins Graph Summarization for Geo-correlated Trends Detection in Social Networks Emma in Action: Declarative Dataflows for Scalable Data Analysis
×
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