CloudMdsQL多存储系统

B. Kolev, Carlyna Bondiombouy, P. Valduriez, R. Jiménez-Peris, Raquel Pau, José Pereira
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引用次数: 47

摘要

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。
The CloudMdsQL Multistore System
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.
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